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translation | transformers |
### opus-mt-war-es
* source languages: war
* target languages: es
* OPUS readme: [war-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/war-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-war-es | null | [
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"has_space",
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #war #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-war-es
* source languages: war
* target languages: es
* OPUS readme: war-es
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 28.7, ch... | [
"### opus-mt-war-es\n\n\n* source languages: war\n* target languages: es\n* OPUS readme: war-es\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #war #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-war-es\n\n\n* source languages: war\n* target languages: es\n* OPUS readme: war-es\n* dataset: opus\n* model: transformer-al... | [
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translation | transformers |
### opus-mt-war-fi
* source languages: war
* target languages: fi
* OPUS readme: [war-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/war-fi/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-24.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-war-fi | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #war #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-war-fi
* source languages: war
* target languages: fi
* OPUS readme: war-fi
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 26.9, ch... | [
"### opus-mt-war-fi\n\n\n* source languages: war\n* target languages: fi\n* OPUS readme: war-fi\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #war #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-war-fi\n\n\n* source languages: war\n* target languages: fi\n* OPUS readme: war-fi\n* dataset: opus\n* model: transformer-al... | [
51,
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translation | transformers |
### opus-mt-war-fr
* source languages: war
* target languages: fr
* OPUS readme: [war-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/war-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-war-fr | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #war #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-war-fr
* source languages: war
* target languages: fr
* OPUS readme: war-fr
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 30.2, ch... | [
"### opus-mt-war-fr\n\n\n* source languages: war\n* target languages: fr\n* OPUS readme: war-fr\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #war #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-war-fr\n\n\n* source languages: war\n* target languages: fr\n* OPUS readme: war-fr\n* dataset: opus\n* model: transformer-al... | [
51,
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #war #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-war-fr\n\n\n* source languages: war\n* target languages: fr\n* OPUS readme: war-fr\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-war-sv
* source languages: war
* target languages: sv
* OPUS readme: [war-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/war-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-war-sv | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #war #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-war-sv
* source languages: war
* target languages: sv
* OPUS readme: war-sv
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 31.4, ch... | [
"### opus-mt-war-sv\n\n\n* source languages: war\n* target languages: sv\n* OPUS readme: war-sv\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #war #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-war-sv\n\n\n* source languages: war\n* target languages: sv\n* OPUS readme: war-sv\n* dataset: opus\n* model: transformer-al... | [
51,
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #war #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-war-sv\n\n\n* source languages: war\n* target languages: sv\n* OPUS readme: war-sv\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-wls-en
* source languages: wls
* target languages: en
* OPUS readme: [wls-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/wls-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-wls-en | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #wls #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-wls-en
* source languages: wls
* target languages: en
* OPUS readme: wls-en
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 31.8, ch... | [
"### opus-mt-wls-en\n\n\n* source languages: wls\n* target languages: en\n* OPUS readme: wls-en\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #wls #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-wls-en\n\n\n* source languages: wls\n* target languages: en\n* OPUS readme: wls-en\n* dataset: opus\n* model: transformer-al... | [
52,
109
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #wls #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-wls-en\n\n\n* source languages: wls\n* target languages: en\n* OPUS readme: wls-en\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-wls-fr
* source languages: wls
* target languages: fr
* OPUS readme: [wls-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/wls-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-wls-fr | null | [
"transformers",
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"wls",
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #wls #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-wls-fr
* source languages: wls
* target languages: fr
* OPUS readme: wls-fr
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 22.6, ch... | [
"### opus-mt-wls-fr\n\n\n* source languages: wls\n* target languages: fr\n* OPUS readme: wls-fr\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #wls #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-wls-fr\n\n\n* source languages: wls\n* target languages: fr\n* OPUS readme: wls-fr\n* dataset: opus\n* model: transformer-al... | [
52,
109
] | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #wls #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-wls-fr\n\n\n* source languages: wls\n* target languages: fr\n* OPUS readme: wls-fr\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-wls-sv
* source languages: wls
* target languages: sv
* OPUS readme: [wls-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/wls-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-wls-sv | null | [
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"wls",
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"license:apache-2.0",
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"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #wls #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-wls-sv
* source languages: wls
* target languages: sv
* OPUS readme: wls-sv
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 23.8, ch... | [
"### opus-mt-wls-sv\n\n\n* source languages: wls\n* target languages: sv\n* OPUS readme: wls-sv\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #wls #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-wls-sv\n\n\n* source languages: wls\n* target languages: sv\n* OPUS readme: wls-sv\n* dataset: opus\n* model: transformer-al... | [
52,
109
] | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #wls #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-wls-sv\n\n\n* source languages: wls\n* target languages: sv\n* OPUS readme: wls-sv\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-xh-en
* source languages: xh
* target languages: en
* OPUS readme: [xh-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/xh-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-xh-en | null | [
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #xh #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-xh-en
* source languages: xh
* target languages: en
* OPUS readme: xh-en
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 45.8, chr-F... | [
"### opus-mt-xh-en\n\n\n* source languages: xh\n* target languages: en\n* OPUS readme: xh-en\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #xh #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-xh-en\n\n\n* source languages: xh\n* target languages: en\n* OPUS readme: xh-en\n* dataset: opus\n* model: transformer-align\... | [
52,
108
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #xh #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-xh-en\n\n\n* source languages: xh\n* target languages: en\n* OPUS readme: xh-en\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-xh-es
* source languages: xh
* target languages: es
* OPUS readme: [xh-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/xh-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-xh-es | null | [
"transformers",
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"translation",
"xh",
"es",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #xh #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-xh-es
* source languages: xh
* target languages: es
* OPUS readme: xh-es
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 32.3, chr-F... | [
"### opus-mt-xh-es\n\n\n* source languages: xh\n* target languages: es\n* OPUS readme: xh-es\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #xh #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-xh-es\n\n\n* source languages: xh\n* target languages: es\n* OPUS readme: xh-es\n* dataset: opus\n* model: transformer-align\... | [
52,
108
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #xh #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-xh-es\n\n\n* source languages: xh\n* target languages: es\n* OPUS readme: xh-es\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-xh-fr
* source languages: xh
* target languages: fr
* OPUS readme: [xh-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/xh-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-xh-fr | null | [
"transformers",
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"translation",
"xh",
"fr",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #xh #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-xh-fr
* source languages: xh
* target languages: fr
* OPUS readme: xh-fr
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 30.6, chr-F... | [
"### opus-mt-xh-fr\n\n\n* source languages: xh\n* target languages: fr\n* OPUS readme: xh-fr\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
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"### opus-mt-xh-fr\n\n\n* source languages: xh\n* target languages: fr\n* OPUS readme: xh-fr\n* dataset: opus\n* model: transformer-align\... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #xh #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-xh-fr\n\n\n* source languages: xh\n* target languages: fr\n* OPUS readme: xh-fr\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-xh-sv
* source languages: xh
* target languages: sv
* OPUS readme: [xh-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/xh-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-xh-sv | null | [
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#transformers #pytorch #tf #marian #text2text-generation #translation #xh #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-xh-sv
* source languages: xh
* target languages: sv
* OPUS readme: xh-sv
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 33.1, chr-F... | [
"### opus-mt-xh-sv\n\n\n* source languages: xh\n* target languages: sv\n* OPUS readme: xh-sv\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
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"### opus-mt-xh-sv\n\n\n* source languages: xh\n* target languages: sv\n* OPUS readme: xh-sv\n* dataset: opus\n* model: transformer-align\... | [
52,
109
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #xh #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-xh-sv\n\n\n* source languages: xh\n* target languages: sv\n* OPUS readme: xh-sv\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-yap-en
* source languages: yap
* target languages: en
* OPUS readme: [yap-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yap-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yap-en | null | [
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#transformers #pytorch #tf #marian #text2text-generation #translation #yap #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yap-en
* source languages: yap
* target languages: en
* OPUS readme: yap-en
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 30.2, ch... | [
"### opus-mt-yap-en\n\n\n* source languages: yap\n* target languages: en\n* OPUS readme: yap-en\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yap #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yap-en\n\n\n* source languages: yap\n* target languages: en\n* OPUS readme: yap-en\n* dataset: opus\n* model: transformer-al... | [
52,
109
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yap #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yap-en\n\n\n* source languages: yap\n* target languages: en\n* OPUS readme: yap-en\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-yap-fr
* source languages: yap
* target languages: fr
* OPUS readme: [yap-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yap-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yap-fr | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #yap #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yap-fr
* source languages: yap
* target languages: fr
* OPUS readme: yap-fr
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 22.2, ch... | [
"### opus-mt-yap-fr\n\n\n* source languages: yap\n* target languages: fr\n* OPUS readme: yap-fr\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yap #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yap-fr\n\n\n* source languages: yap\n* target languages: fr\n* OPUS readme: yap-fr\n* dataset: opus\n* model: transformer-al... | [
52,
108
] | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yap #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yap-fr\n\n\n* source languages: yap\n* target languages: fr\n* OPUS readme: yap-fr\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-yap-sv
* source languages: yap
* target languages: sv
* OPUS readme: [yap-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yap-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yap-sv | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #yap #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yap-sv
* source languages: yap
* target languages: sv
* OPUS readme: yap-sv
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 22.6, ch... | [
"### opus-mt-yap-sv\n\n\n* source languages: yap\n* target languages: sv\n* OPUS readme: yap-sv\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yap #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yap-sv\n\n\n* source languages: yap\n* target languages: sv\n* OPUS readme: yap-sv\n* dataset: opus\n* model: transformer-al... | [
52,
109
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yap #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yap-sv\n\n\n* source languages: yap\n* target languages: sv\n* OPUS readme: yap-sv\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### opus-mt-yo-en
* source languages: yo
* target languages: en
* OPUS readme: [yo-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yo-en/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yo-en | null | [
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"has_space",
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #yo #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yo-en
* source languages: yo
* target languages: en
* OPUS readme: yo-en
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 33.8, chr-F... | [
"### opus-mt-yo-en\n\n\n* source languages: yo\n* target languages: en\n* OPUS readme: yo-en\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yo-en\n\n\n* source languages: yo\n* target languages: en\n* OPUS readme: yo-en\n* dataset: opus\n* model: transformer-align\... | [
51,
106
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yo-en\n\n\n* source languages: yo\n* target languages: en\n* OPUS readme: yo-en\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-yo-es
* source languages: yo
* target languages: es
* OPUS readme: [yo-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yo-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yo-es | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #yo #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yo-es
* source languages: yo
* target languages: es
* OPUS readme: yo-es
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 22.0, chr-F... | [
"### opus-mt-yo-es\n\n\n* source languages: yo\n* target languages: es\n* OPUS readme: yo-es\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yo-es\n\n\n* source languages: yo\n* target languages: es\n* OPUS readme: yo-es\n* dataset: opus\n* model: transformer-align\... | [
51,
106
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yo-es\n\n\n* source languages: yo\n* target languages: es\n* OPUS readme: yo-es\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-yo-fi
* source languages: yo
* target languages: fi
* OPUS readme: [yo-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yo-fi/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yo-fi | null | [
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"has_space",
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] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #yo #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yo-fi
* source languages: yo
* target languages: fi
* OPUS readme: yo-fi
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 21.5, chr-F... | [
"### opus-mt-yo-fi\n\n\n* source languages: yo\n* target languages: fi\n* OPUS readme: yo-fi\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yo-fi\n\n\n* source languages: yo\n* target languages: fi\n* OPUS readme: yo-fi\n* dataset: opus\n* model: transformer-align\... | [
51,
106
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yo-fi\n\n\n* source languages: yo\n* target languages: fi\n* OPUS readme: yo-fi\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-yo-fr
* source languages: yo
* target languages: fr
* OPUS readme: [yo-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yo-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yo-fr | null | [
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #yo #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yo-fr
* source languages: yo
* target languages: fr
* OPUS readme: yo-fr
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 24.1, chr-F... | [
"### opus-mt-yo-fr\n\n\n* source languages: yo\n* target languages: fr\n* OPUS readme: yo-fr\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yo-fr\n\n\n* source languages: yo\n* target languages: fr\n* OPUS readme: yo-fr\n* dataset: opus\n* model: transformer-align\... | [
51,
106
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yo-fr\n\n\n* source languages: yo\n* target languages: fr\n* OPUS readme: yo-fr\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-yo-sv
* source languages: yo
* target languages: sv
* OPUS readme: [yo-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/yo-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](http... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-yo-sv | null | [
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #yo #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-yo-sv
* source languages: yo
* target languages: sv
* OPUS readme: yo-sv
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 25.2, chr-F... | [
"### opus-mt-yo-sv\n\n\n* source languages: yo\n* target languages: sv\n* OPUS readme: yo-sv\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntestset:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-yo-sv\n\n\n* source languages: yo\n* target languages: sv\n* OPUS readme: yo-sv\n* dataset: opus\n* model: transformer-align\... | [
51,
106
] | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #yo #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-yo-sv\n\n\n* source languages: yo\n* target languages: sv\n* OPUS readme: yo-sv\n* dataset: opus\n* model: transformer-align\n* pre... |
translation | transformers |
### opus-mt-zai-es
* source languages: zai
* target languages: es
* OPUS readme: [zai-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/zai-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zai-es | null | [
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zai #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-zai-es
* source languages: zai
* target languages: es
* OPUS readme: zai-es
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 20.8, ch... | [
"### opus-mt-zai-es\n\n\n* source languages: zai\n* target languages: es\n* OPUS readme: zai-es\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zai #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### opus-mt-zai-es\n\n\n* source languages: zai\n* target languages: es\n* OPUS readme: zai-es\n* dataset: opus\n* model: transformer-al... | [
52,
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] | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zai #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### opus-mt-zai-es\n\n\n* source languages: zai\n* target languages: es\n* OPUS readme: zai-es\n* dataset: opus\n* model: transformer-align\n*... |
translation | transformers |
### zho-bul
* source group: Chinese
* target group: Bulgarian
* OPUS readme: [zho-bul](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-bul/README.md)
* model: transformer
* source language(s): cmn cmn_Hans cmn_Hant zho zho_Hans zho_Hant
* target language(s): bul
* model: transformer
* pr... | {"language": ["zh", "bg"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-bg | null | [
"transformers",
"pytorch",
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"translation",
"zh",
"bg",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"bg"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #bg #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-bul
* source group: Chinese
* target group: Bulgarian
* OPUS readme: zho-bul
* model: transformer
* source language(s): cmn cmn\_Hans cmn\_Hant zho zho\_Hans zho\_Hant
* target language(s): bul
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: UR... | [
"### zho-bul\n\n\n* source group: Chinese\n* target group: Bulgarian\n* OPUS readme: zho-bul\n* model: transformer\n* source language(s): cmn cmn\\_Hans cmn\\_Hant zho zho\\_Hans zho\\_Hant\n* target language(s): bul\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download ... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #bg #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-bul\n\n\n* source group: Chinese\n* target group: Bulgarian\n* OPUS readme: zho-bul\n* model: transformer\n* source language(s): ... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #bg #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-bul\n\n\n* source group: Chinese\n* target group: Bulgarian\n* OPUS readme: zho-bul\n* model: transformer\n* source language(s): cmn cm... |
translation | transformers |
### zho-deu
* source group: Chinese
* target group: German
* OPUS readme: [zho-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-deu/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hang cmn_Hani cmn_Hira cmn_Kana cmn_Latn lzh_Hani wuu_Hani yue_Hani
* targe... | {"language": ["zh", "de"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-de | null | [
"transformers",
"pytorch",
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"translation",
"zh",
"de",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"de"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #de #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-deu
* source group: Chinese
* target group: German
* OPUS readme: zho-deu
* model: transformer-align
* source language(s): cmn cmn\_Bopo cmn\_Hang cmn\_Hani cmn\_Hira cmn\_Kana cmn\_Latn lzh\_Hani wuu\_Hani yue\_Hani
* target language(s): deu
* model: transformer-align
* pre-processing: normalization + Senten... | [
"### zho-deu\n\n\n* source group: Chinese\n* target group: German\n* OPUS readme: zho-deu\n* model: transformer-align\n* source language(s): cmn cmn\\_Bopo cmn\\_Hang cmn\\_Hani cmn\\_Hira cmn\\_Kana cmn\\_Latn lzh\\_Hani wuu\\_Hani yue\\_Hani\n* target language(s): deu\n* model: transformer-align\n* pre-processing... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #de #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-deu\n\n\n* source group: Chinese\n* target group: German\n* OPUS readme: zho-deu\n* model: transformer-align\n* source language(s... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #de #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-deu\n\n\n* source group: Chinese\n* target group: German\n* OPUS readme: zho-deu\n* model: transformer-align\n* source language(s): cmn... |
translation | transformers |
### zho-eng
## Table of Contents
- [Model Details](#model-details)
- [Uses](#uses)
- [Risks, Limitations and Biases](#risks-limitations-and-biases)
- [Training](#training)
- [Evaluation](#evaluation)
- [Citation Information](#citation-information)
- [How to Get Started With the Model](#how-to-get-started-with-the-mod... | {"language": ["zh", "en"], "license": "cc-by-4.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-en | null | [
"transformers",
"pytorch",
"tf",
"rust",
"marian",
"text2text-generation",
"translation",
"zh",
"en",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"en"
] | TAGS
#transformers #pytorch #tf #rust #marian #text2text-generation #translation #zh #en #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-eng
Table of Contents
-----------------
* Model Details
* Uses
* Risks, Limitations and Biases
* Training
* Evaluation
* Citation Information
* How to Get Started With the Model
Model Details
-------------
* Model Description:
* Developed by: Language Technology Research Group at the University of Helsi... | [
"### zho-eng\n\n\nTable of Contents\n-----------------\n\n\n* Model Details\n* Uses\n* Risks, Limitations and Biases\n* Training\n* Evaluation\n* Citation Information\n* How to Get Started With the Model\n\n\nModel Details\n-------------\n\n\n* Model Description:\n* Developed by: Language Technology Research Group ... | [
"TAGS\n#transformers #pytorch #tf #rust #marian #text2text-generation #translation #zh #en #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-eng\n\n\nTable of Contents\n-----------------\n\n\n* Model Details\n* Uses\n* Risks, Limitations and Biases\n* Training\n* E... | [
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"TAGS\n#transformers #pytorch #tf #rust #marian #text2text-generation #translation #zh #en #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-eng\n\n\nTable of Contents\n-----------------\n\n\n* Model Details\n* Uses\n* Risks, Limitations and Biases\n* Training\n* Evaluat... |
translation | transformers |
### zho-fin
* source group: Chinese
* target group: Finnish
* OPUS readme: [zho-fin](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-fin/README.md)
* model: transformer-align
* source language(s): cmn_Bopo cmn_Hani cmn_Latn nan_Hani yue yue_Hani
* target language(s): fin
* model: transfo... | {"language": ["zh", "fi"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-fi | null | [
"transformers",
"pytorch",
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"translation",
"zh",
"fi",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"fi"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-fin
* source group: Chinese
* target group: Finnish
* OPUS readme: zho-fin
* model: transformer-align
* source language(s): cmn\_Bopo cmn\_Hani cmn\_Latn nan\_Hani yue yue\_Hani
* target language(s): fin
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download orig... | [
"### zho-fin\n\n\n* source group: Chinese\n* target group: Finnish\n* OPUS readme: zho-fin\n* model: transformer-align\n* source language(s): cmn\\_Bopo cmn\\_Hani cmn\\_Latn nan\\_Hani yue yue\\_Hani\n* target language(s): fin\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-fin\n\n\n* source group: Chinese\n* target group: Finnish\n* OPUS readme: zho-fin\n* model: transformer-align\n* source language(... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-fin\n\n\n* source group: Chinese\n* target group: Finnish\n* OPUS readme: zho-fin\n* model: transformer-align\n* source language(s): cm... |
translation | transformers |
### zho-heb
* source group: Chinese
* target group: Hebrew
* OPUS readme: [zho-heb](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-heb/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hang cmn_Hani cmn_Hira cmn_Kana cmn_Latn cmn_Yiii lzh lzh_Bopo lzh_Hang lzh... | {"language": ["zh", "he"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-he | null | [
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"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
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] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #he #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-heb
* source group: Chinese
* target group: Hebrew
* OPUS readme: zho-heb
* model: transformer-align
* source language(s): cmn cmn\_Bopo cmn\_Hang cmn\_Hani cmn\_Hira cmn\_Kana cmn\_Latn cmn\_Yiii lzh lzh\_Bopo lzh\_Hang lzh\_Hani lzh\_Hira lzh\_Kana lzh\_Yiii
* target language(s): heb
* model: transformer-al... | [
"### zho-heb\n\n\n* source group: Chinese\n* target group: Hebrew\n* OPUS readme: zho-heb\n* model: transformer-align\n* source language(s): cmn cmn\\_Bopo cmn\\_Hang cmn\\_Hani cmn\\_Hira cmn\\_Kana cmn\\_Latn cmn\\_Yiii lzh lzh\\_Bopo lzh\\_Hang lzh\\_Hani lzh\\_Hira lzh\\_Kana lzh\\_Yiii\n* target language(s): h... | [
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"### zho-heb\n\n\n* source group: Chinese\n* target group: Hebrew\n* OPUS readme: zho-heb\n* model: transformer-align\n* source language(s... | [
52,
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #he #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-heb\n\n\n* source group: Chinese\n* target group: Hebrew\n* OPUS readme: zho-heb\n* model: transformer-align\n* source language(s): cmn... |
translation | transformers |
### zho-ita
* source group: Chinese
* target group: Italian
* OPUS readme: [zho-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-ita/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hang cmn_Hani cmn_Hira cmn_Kana cmn_Latn lzh lzh_Hang lzh_Hani lzh_Hira lz... | {"language": ["zh", "it"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-it | null | [
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"license:apache-2.0",
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"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"it"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-ita
* source group: Chinese
* target group: Italian
* OPUS readme: zho-ita
* model: transformer-align
* source language(s): cmn cmn\_Bopo cmn\_Hang cmn\_Hani cmn\_Hira cmn\_Kana cmn\_Latn lzh lzh\_Hang lzh\_Hani lzh\_Hira lzh\_Yiii wuu\_Bopo wuu\_Hani wuu\_Latn yue\_Hani
* target language(s): ita
* model: tra... | [
"### zho-ita\n\n\n* source group: Chinese\n* target group: Italian\n* OPUS readme: zho-ita\n* model: transformer-align\n* source language(s): cmn cmn\\_Bopo cmn\\_Hang cmn\\_Hani cmn\\_Hira cmn\\_Kana cmn\\_Latn lzh lzh\\_Hang lzh\\_Hani lzh\\_Hira lzh\\_Yiii wuu\\_Bopo wuu\\_Hani wuu\\_Latn yue\\_Hani\n* target la... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-ita\n\n\n* source group: Chinese\n* target group: Italian\n* OPUS readme: zho-ita\n* model: transformer-align\n* source language(... | [
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translation | transformers |
### zho-msa
* source group: Chinese
* target group: Malay (macrolanguage)
* OPUS readme: [zho-msa](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-msa/README.md)
* model: transformer-align
* source language(s): cmn_Bopo cmn_Hani cmn_Latn hak_Hani yue_Bopo yue_Hani
* target language(s): i... | {"language": ["zh", "ms"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-ms | null | [
"transformers",
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"zh",
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"license:apache-2.0",
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
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] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #ms #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-msa
* source group: Chinese
* target group: Malay (macrolanguage)
* OPUS readme: zho-msa
* model: transformer-align
* source language(s): cmn\_Bopo cmn\_Hani cmn\_Latn hak\_Hani yue\_Bopo yue\_Hani
* target language(s): ind zsm\_Latn
* model: transformer-align
* pre-processing: normalization + SentencePiece (... | [
"### zho-msa\n\n\n* source group: Chinese\n* target group: Malay (macrolanguage)\n* OPUS readme: zho-msa\n* model: transformer-align\n* source language(s): cmn\\_Bopo cmn\\_Hani cmn\\_Latn hak\\_Hani yue\\_Bopo yue\\_Hani\n* target language(s): ind zsm\\_Latn\n* model: transformer-align\n* pre-processing: normaliza... | [
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"### zho-msa\n\n\n* source group: Chinese\n* target group: Malay (macrolanguage)\n* OPUS readme: zho-msa\n* model: transformer-align\n* so... | [
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translation | transformers |
### zho-nld
* source group: Chinese
* target group: Dutch
* OPUS readme: [zho-nld](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-nld/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hani cmn_Hira cmn_Kana cmn_Latn
* target language(s): nld
* model: transform... | {"language": ["zh", "nl"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-nl | null | [
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"translation",
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"nl",
"license:apache-2.0",
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"nl"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #nl #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-nld
* source group: Chinese
* target group: Dutch
* OPUS readme: zho-nld
* model: transformer-align
* source language(s): cmn cmn\_Bopo cmn\_Hani cmn\_Hira cmn\_Kana cmn\_Latn
* target language(s): nld
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download origin... | [
"### zho-nld\n\n\n* source group: Chinese\n* target group: Dutch\n* OPUS readme: zho-nld\n* model: transformer-align\n* source language(s): cmn cmn\\_Bopo cmn\\_Hani cmn\\_Hira cmn\\_Kana cmn\\_Latn\n* target language(s): nld\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm32... | [
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"### zho-nld\n\n\n* source group: Chinese\n* target group: Dutch\n* OPUS readme: zho-nld\n* model: transformer-align\n* source language(s)... | [
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translation | transformers |
### zho-swe
* source group: Chinese
* target group: Swedish
* OPUS readme: [zho-swe](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-swe/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hani cmn_Latn
* target language(s): swe
* model: transformer-align
* pre-p... | {"language": ["zh", "sv"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-sv | null | [
"transformers",
"pytorch",
"tf",
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"translation",
"zh",
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"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"sv"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-swe
* source group: Chinese
* target group: Swedish
* OPUS readme: zho-swe
* model: transformer-align
* source language(s): cmn cmn\_Bopo cmn\_Hani cmn\_Latn
* target language(s): swe
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* ... | [
"### zho-swe\n\n\n* source group: Chinese\n* target group: Swedish\n* OPUS readme: zho-swe\n* model: transformer-align\n* source language(s): cmn cmn\\_Bopo cmn\\_Hani cmn\\_Latn\n* target language(s): swe\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download origi... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-swe\n\n\n* source group: Chinese\n* target group: Swedish\n* OPUS readme: zho-swe\n* model: transformer-align\n* source language(... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-swe\n\n\n* source group: Chinese\n* target group: Swedish\n* OPUS readme: zho-swe\n* model: transformer-align\n* source language(s): cm... |
translation | transformers |
### zho-ukr
* source group: Chinese
* target group: Ukrainian
* OPUS readme: [zho-ukr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-ukr/README.md)
* model: transformer-align
* source language(s): cmn cmn_Bopo cmn_Hang cmn_Hani cmn_Kana cmn_Latn cmn_Yiii yue_Bopo yue_Hang yue_Hani yue_... | {"language": ["zh", "uk"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-uk | null | [
"transformers",
"pytorch",
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"marian",
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"translation",
"zh",
"uk",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"uk"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #uk #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-ukr
* source group: Chinese
* target group: Ukrainian
* OPUS readme: zho-ukr
* model: transformer-align
* source language(s): cmn cmn\_Bopo cmn\_Hang cmn\_Hani cmn\_Kana cmn\_Latn cmn\_Yiii yue\_Bopo yue\_Hang yue\_Hani yue\_Hira yue\_Kana
* target language(s): ukr
* model: transformer-align
* pre-processing:... | [
"### zho-ukr\n\n\n* source group: Chinese\n* target group: Ukrainian\n* OPUS readme: zho-ukr\n* model: transformer-align\n* source language(s): cmn cmn\\_Bopo cmn\\_Hang cmn\\_Hani cmn\\_Kana cmn\\_Latn cmn\\_Yiii yue\\_Bopo yue\\_Hang yue\\_Hani yue\\_Hira yue\\_Kana\n* target language(s): ukr\n* model: transforme... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #uk #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-ukr\n\n\n* source group: Chinese\n* target group: Ukrainian\n* OPUS readme: zho-ukr\n* model: transformer-align\n* source languag... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #uk #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-ukr\n\n\n* source group: Chinese\n* target group: Ukrainian\n* OPUS readme: zho-ukr\n* model: transformer-align\n* source language(s): ... |
translation | transformers |
### zho-vie
* source group: Chinese
* target group: Vietnamese
* OPUS readme: [zho-vie](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zho-vie/README.md)
* model: transformer-align
* source language(s): cmn_Hani cmn_Latn
* target language(s): vie
* model: transformer-align
* pre-processing:... | {"language": ["zh", "vi"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zh-vi | null | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"zh",
"vi",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh",
"vi"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #zh #vi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zho-vie
* source group: Chinese
* target group: Vietnamese
* OPUS readme: zho-vie
* model: transformer-align
* source language(s): cmn\_Hani cmn\_Latn
* target language(s): vie
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set tr... | [
"### zho-vie\n\n\n* source group: Chinese\n* target group: Vietnamese\n* OPUS readme: zho-vie\n* model: transformer-align\n* source language(s): cmn\\_Hani cmn\\_Latn\n* target language(s): vie\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weights:... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #vi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zho-vie\n\n\n* source group: Chinese\n* target group: Vietnamese\n* OPUS readme: zho-vie\n* model: transformer-align\n* source langua... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #zh #vi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zho-vie\n\n\n* source group: Chinese\n* target group: Vietnamese\n* OPUS readme: zho-vie\n* model: transformer-align\n* source language(s):... |
translation | transformers |
### zle-eng
* source group: East Slavic languages
* target group: English
* OPUS readme: [zle-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zle-eng/README.md)
* model: transformer
* source language(s): bel bel_Latn orv_Cyrl rue rus ukr
* target language(s): eng
* model: transformer
* ... | {"language": ["be", "ru", "uk", "zle", "en"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zle-en | null | [
"transformers",
"pytorch",
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"text2text-generation",
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"ru",
"uk",
"zle",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"be",
"ru",
"uk",
"zle",
"en"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #be #ru #uk #zle #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zle-eng
* source group: East Slavic languages
* target group: English
* OPUS readme: zle-eng
* model: transformer
* source language(s): bel bel\_Latn orv\_Cyrl rue rus ukr
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: UR... | [
"### zle-eng\n\n\n* source group: East Slavic languages\n* target group: English\n* OPUS readme: zle-eng\n* model: transformer\n* source language(s): bel bel\\_Latn orv\\_Cyrl rue rus ukr\n* target language(s): eng\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download or... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #be #ru #uk #zle #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zle-eng\n\n\n* source group: East Slavic languages\n* target group: English\n* OPUS readme: zle-eng\n* model: transforme... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #be #ru #uk #zle #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zle-eng\n\n\n* source group: East Slavic languages\n* target group: English\n* OPUS readme: zle-eng\n* model: transformer\n* s... |
translation | transformers |
### zle-zle
* source group: East Slavic languages
* target group: East Slavic languages
* OPUS readme: [zle-zle](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zle-zle/README.md)
* model: transformer
* source language(s): bel bel_Latn orv_Cyrl rus ukr
* target language(s): bel bel_Latn orv_... | {"language": ["be", "ru", "uk", "zle"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zle-zle | null | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"be",
"ru",
"uk",
"zle",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"be",
"ru",
"uk",
"zle"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #be #ru #uk #zle #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zle-zle
* source group: East Slavic languages
* target group: East Slavic languages
* OPUS readme: zle-zle
* model: transformer
* source language(s): bel bel\_Latn orv\_Cyrl rus ukr
* target language(s): bel bel\_Latn orv\_Cyrl rus ukr
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,s... | [
"### zle-zle\n\n\n* source group: East Slavic languages\n* target group: East Slavic languages\n* OPUS readme: zle-zle\n* model: transformer\n* source language(s): bel bel\\_Latn orv\\_Cyrl rus ukr\n* target language(s): bel bel\\_Latn orv\\_Cyrl rus ukr\n* model: transformer\n* pre-processing: normalization + Sent... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #be #ru #uk #zle #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zle-zle\n\n\n* source group: East Slavic languages\n* target group: East Slavic languages\n* OPUS readme: zle-zle\n* model: ... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #be #ru #uk #zle #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zle-zle\n\n\n* source group: East Slavic languages\n* target group: East Slavic languages\n* OPUS readme: zle-zle\n* model: transf... |
translation | transformers |
### zls-eng
* source group: South Slavic languages
* target group: English
* OPUS readme: [zls-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zls-eng/README.md)
* model: transformer
* source language(s): bos_Latn bul bul_Latn hrv mkd slv srp_Cyrl srp_Latn
* target language(s): eng
* mo... | {"language": ["hr", "mk", "bg", "sl", "zls", "en"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zls-en | null | [
"transformers",
"pytorch",
"tf",
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"bg",
"sl",
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"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"hr",
"mk",
"bg",
"sl",
"zls",
"en"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #hr #mk #bg #sl #zls #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zls-eng
* source group: South Slavic languages
* target group: English
* OPUS readme: zls-eng
* model: transformer
* source language(s): bos\_Latn bul bul\_Latn hrv mkd slv srp\_Cyrl srp\_Latn
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download... | [
"### zls-eng\n\n\n* source group: South Slavic languages\n* target group: English\n* OPUS readme: zls-eng\n* model: transformer\n* source language(s): bos\\_Latn bul bul\\_Latn hrv mkd slv srp\\_Cyrl srp\\_Latn\n* target language(s): eng\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #hr #mk #bg #sl #zls #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zls-eng\n\n\n* source group: South Slavic languages\n* target group: English\n* OPUS readme: zls-eng\n* model: trans... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #hr #mk #bg #sl #zls #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zls-eng\n\n\n* source group: South Slavic languages\n* target group: English\n* OPUS readme: zls-eng\n* model: transformer... |
translation | transformers |
### zls-zls
* source group: South Slavic languages
* target group: South Slavic languages
* OPUS readme: [zls-zls](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zls-zls/README.md)
* model: transformer
* source language(s): bul mkd srp_Cyrl
* target language(s): bul mkd srp_Cyrl
* model: tr... | {"language": ["hr", "mk", "bg", "sl", "zls"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zls-zls | null | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"hr",
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"bg",
"sl",
"zls",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"hr",
"mk",
"bg",
"sl",
"zls"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #hr #mk #bg #sl #zls #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zls-zls
* source group: South Slavic languages
* target group: South Slavic languages
* OPUS readme: zls-zls
* model: transformer
* source language(s): bul mkd srp\_Cyrl
* target language(s): bul mkd srp\_Cyrl
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* a sentence initia... | [
"### zls-zls\n\n\n* source group: South Slavic languages\n* target group: South Slavic languages\n* OPUS readme: zls-zls\n* model: transformer\n* source language(s): bul mkd srp\\_Cyrl\n* target language(s): bul mkd srp\\_Cyrl\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n*... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #hr #mk #bg #sl #zls #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zls-zls\n\n\n* source group: South Slavic languages\n* target group: South Slavic languages\n* OPUS readme: zls-zls\n* m... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #hr #mk #bg #sl #zls #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zls-zls\n\n\n* source group: South Slavic languages\n* target group: South Slavic languages\n* OPUS readme: zls-zls\n* model: ... |
translation | transformers |
### zlw-eng
* source group: West Slavic languages
* target group: English
* OPUS readme: [zlw-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zlw-eng/README.md)
* model: transformer
* source language(s): ces csb_Latn dsb hsb pol
* target language(s): eng
* model: transformer
* pre-proce... | {"language": ["pl", "cs", "zlw", "en"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zlw-en | null | [
"transformers",
"pytorch",
"tf",
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"text2text-generation",
"translation",
"pl",
"cs",
"zlw",
"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"pl",
"cs",
"zlw",
"en"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #pl #cs #zlw #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zlw-eng
* source group: West Slavic languages
* target group: English
* OPUS readme: zlw-eng
* model: transformer
* source language(s): ces csb\_Latn dsb hsb pol
* target language(s): eng
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test s... | [
"### zlw-eng\n\n\n* source group: West Slavic languages\n* target group: English\n* OPUS readme: zlw-eng\n* model: transformer\n* source language(s): ces csb\\_Latn dsb hsb pol\n* target language(s): eng\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weig... | [
"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #pl #cs #zlw #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zlw-eng\n\n\n* source group: West Slavic languages\n* target group: English\n* OPUS readme: zlw-eng\n* model: transformer\n*... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #pl #cs #zlw #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zlw-eng\n\n\n* source group: West Slavic languages\n* target group: English\n* OPUS readme: zlw-eng\n* model: transformer\n* sourc... |
translation | transformers | ### zlw-fiu
* source language name: West Slavic languages
* target language name: Finno-Ugrian languages
* OPUS readme: [README.md](https://object.pouta.csc.fi/Tatoeba-MT-models/zlw-fiu/README.md)
* model: transformer
* source language codes: dsb, cs, csb_Latn, hsb, pl, zlw
* target language codes: hu, vro, fi, liv_Lat... | {"language": ["dsb", "cs", "csb_Latn", "hsb", "pl", "zlw", "hu", "vro", "fi", "liv_Latn", "mdf", "krl", "fkv_Latn", "mhr", "et", "sma", "udm", "vep", "myv", "kpv", "se", "izh", "fiu"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zlw-fiu | null | [
"transformers",
"pytorch",
"tf",
"safetensors",
"marian",
"text2text-generation",
"translation",
"zlw",
"fiu",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"dsb",
"cs",
"csb_Latn",
"hsb",
"pl",
"zlw",
"hu",
"vro",
"fi",
"liv_Latn",
"mdf",
"krl",
"fkv_Latn",
"mhr",
"et",
"sma",
"udm",
"vep",
"myv",
"kpv",
"se",
"izh",
"fiu"
] | TAGS
#transformers #pytorch #tf #safetensors #marian #text2text-generation #translation #zlw #fiu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zlw-fiu
* source language name: West Slavic languages
* target language name: Finno-Ugrian languages
* OPUS readme: URL
* model: transformer
* source language codes: dsb, cs, csb_Latn, hsb, pl, zlw
* target language codes: hu, vro, fi, liv_Latn, mdf, krl, fkv_Latn, mhr, et, sma, udm, vep, myv, kpv, se, izh, fiu
* d... | [
"### zlw-fiu\n* source language name: West Slavic languages\n* target language name: Finno-Ugrian languages\n* OPUS readme: URL\n* model: transformer\n* source language codes: dsb, cs, csb_Latn, hsb, pl, zlw\n* target language codes: hu, vro, fi, liv_Latn, mdf, krl, fkv_Latn, mhr, et, sma, udm, vep, myv, kpv, se, i... | [
"TAGS\n#transformers #pytorch #tf #safetensors #marian #text2text-generation #translation #zlw #fiu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### zlw-fiu\n* source language name: West Slavic languages\n* target language name: Finno-Ugrian languages\n* OPUS readme:... | [
58,
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"TAGS\n#transformers #pytorch #tf #safetensors #marian #text2text-generation #translation #zlw #fiu #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### zlw-fiu\n* source language name: West Slavic languages\n* target language name: Finno-Ugrian languages\n* OPUS readme: URL\n... |
translation | transformers |
### zlw-zlw
* source group: West Slavic languages
* target group: West Slavic languages
* OPUS readme: [zlw-zlw](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/zlw-zlw/README.md)
* model: transformer
* source language(s): ces dsb hsb pol
* target language(s): ces dsb hsb pol
* model: transf... | {"language": ["pl", "cs", "zlw"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zlw-zlw | null | [
"transformers",
"pytorch",
"marian",
"text2text-generation",
"translation",
"pl",
"cs",
"zlw",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"pl",
"cs",
"zlw"
] | TAGS
#transformers #pytorch #marian #text2text-generation #translation #pl #cs #zlw #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### zlw-zlw
* source group: West Slavic languages
* target group: West Slavic languages
* OPUS readme: zlw-zlw
* model: transformer
* source language(s): ces dsb hsb pol
* target language(s): ces dsb hsb pol
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* a sentence initial lang... | [
"### zlw-zlw\n\n\n* source group: West Slavic languages\n* target group: West Slavic languages\n* OPUS readme: zlw-zlw\n* model: transformer\n* source language(s): ces dsb hsb pol\n* target language(s): ces dsb hsb pol\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* a sente... | [
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"### zlw-zlw\n\n\n* source group: West Slavic languages\n* target group: West Slavic languages\n* OPUS readme: zlw-zlw\n* model: transfor... | [
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translation | transformers |
### opus-mt-zne-es
* source languages: zne
* target languages: es
* OPUS readme: [zne-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/zne-es/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zne-es | null | [
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#transformers #pytorch #tf #marian #text2text-generation #translation #zne #es #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-zne-es
* source languages: zne
* target languages: es
* OPUS readme: zne-es
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 21.1, ch... | [
"### opus-mt-zne-es\n\n\n* source languages: zne\n* target languages: es\n* OPUS readme: zne-es\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
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"### opus-mt-zne-es\n\n\n* source languages: zne\n* target languages: es\n* OPUS readme: zne-es\n* dataset: opus\n* model: transformer-al... | [
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translation | transformers |
### opus-mt-zne-fi
* source languages: zne
* target languages: fi
* OPUS readme: [zne-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/zne-fi/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zne-fi | null | [
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#transformers #pytorch #tf #marian #text2text-generation #translation #zne #fi #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-zne-fi
* source languages: zne
* target languages: fi
* OPUS readme: zne-fi
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 22.8, ch... | [
"### opus-mt-zne-fi\n\n\n* source languages: zne\n* target languages: fi\n* OPUS readme: zne-fi\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
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"### opus-mt-zne-fi\n\n\n* source languages: zne\n* target languages: fi\n* OPUS readme: zne-fi\n* dataset: opus\n* model: transformer-al... | [
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translation | transformers |
### opus-mt-zne-fr
* source languages: zne
* target languages: fr
* OPUS readme: [zne-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/zne-fr/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zne-fr | null | [
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#transformers #pytorch #tf #marian #text2text-generation #translation #zne #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-zne-fr
* source languages: zne
* target languages: fr
* OPUS readme: zne-fr
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 25.3, ch... | [
"### opus-mt-zne-fr\n\n\n* source languages: zne\n* target languages: fr\n* OPUS readme: zne-fr\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
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"### opus-mt-zne-fr\n\n\n* source languages: zne\n* target languages: fr\n* OPUS readme: zne-fr\n* dataset: opus\n* model: transformer-al... | [
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translation | transformers |
### opus-mt-zne-sv
* source languages: zne
* target languages: sv
* OPUS readme: [zne-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/zne-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: [opus-2020-01-16.zip](... | {"license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-mt-zne-sv | null | [
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#transformers #pytorch #tf #marian #text2text-generation #translation #zne #sv #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### opus-mt-zne-sv
* source languages: zne
* target languages: sv
* OPUS readme: zne-sv
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* download original weights: URL
* test set translations: URL
* test set scores: URL
Benchmarks
----------
testset: URL, BLEU: 25.2, ch... | [
"### opus-mt-zne-sv\n\n\n* source languages: zne\n* target languages: sv\n* OPUS readme: zne-sv\n* dataset: opus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece\n* download original weights: URL\n* test set translations: URL\n* test set scores: URL\n\n\nBenchmarks\n----------\n\n\ntests... | [
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"### opus-mt-zne-sv\n\n\n* source languages: zne\n* target languages: sv\n* OPUS readme: zne-sv\n* dataset: opus\n* model: transformer-al... | [
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translation | transformers | ### af-ru
* source group: Afrikaans
* target group: Russian
* OPUS readme: [afr-rus](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afr-rus/README.md)
* model: transformer-align
* source language(s): afr
* target language(s): rus
* model: transformer-align
* pre-processing: normalization + S... | {"language": ["af", "ru"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-af-ru | null | [
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"has_space",
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] | null | 2022-03-02T23:29:04+00:00 | [] | [
"af",
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] | TAGS
#transformers #pytorch #safetensors #marian #text2text-generation #translation #af #ru #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### af-ru
* source group: Afrikaans
* target group: Russian
* OPUS readme: afr-rus
* model: transformer-align
* source language(s): afr
* target language(s): rus
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* t... | [
"### af-ru\n\n\n* source group: Afrikaans\n* target group: Russian\n* OPUS readme: afr-rus\n* model: transformer-align\n* source language(s): afr\n* target language(s): rus\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weights: URL\n* test set tran... | [
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"### af-ru\n\n\n* source group: Afrikaans\n* target group: Russian\n* OPUS readme: afr-rus\n* model: transformer-align\n* source ... | [
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translation | transformers | ### de-ro
* source group: German
* target group: Romanian
* OPUS readme: [deu-ron](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-ron/README.md)
* model: transformer-align
* source language(s): deu
* target language(s): mol ron
* raw source language(s): deu
* raw target language(s): mol ... | {"language": ["de", "ro"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-de-ro | null | [
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"has_space",
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] | null | 2022-03-02T23:29:04+00:00 | [] | [
"de",
"ro"
] | TAGS
#transformers #pytorch #tf #safetensors #marian #text2text-generation #translation #de #ro #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### de-ro
* source group: German
* target group: Romanian
* OPUS readme: deu-ron
* model: transformer-align
* source language(s): deu
* target language(s): mol ron
* raw source language(s): deu
* raw target language(s): mol ron
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)... | [
"### de-ro\n\n\n* source group: German\n* target group: Romanian\n* OPUS readme: deu-ron\n* model: transformer-align\n* source language(s): deu\n* target language(s): mol ron\n* raw source language(s): deu\n* raw target language(s): mol ron\n* model: transformer-align\n* pre-processing: normalization + SentencePiec... | [
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"### de-ro\n\n\n* source group: German\n* target group: Romanian\n* OPUS readme: deu-ron\n* model: transformer-align\n* sourc... | [
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translation | transformers | ### en-ja
* source group: English
* target group: Japanese
* OPUS readme: [eng-jpn](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-jpn/README.md)
* model: transformer-align
* source language(s): eng
* target language(s): jpn
* model: transformer-align
* pre-processing: normalization + Se... | {"language": ["en", "ja"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-en-ja | null | [
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"en",
"ja"
] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #ja #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### en-ja
* source group: English
* target group: Japanese
* OPUS readme: eng-jpn
* model: transformer-align
* source language(s): eng
* target language(s): jpn
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: opus+URL
* test set translations: opu... | [
"### en-ja\n\n\n* source group: English\n* target group: Japanese\n* OPUS readme: eng-jpn\n* model: transformer-align\n* source language(s): eng\n* target language(s): jpn\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weights: opus+URL\n* test set ... | [
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translation | transformers | ### en-ro
* source group: English
* target group: Romanian
* OPUS readme: [eng-ron](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-ron/README.md)
* model: transformer-align
* source language(s): eng
* target language(s): mol ron
* model: transformer-align
* pre-processing: normalization ... | {"language": ["en", "ro"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-en-ro | null | [
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"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"en",
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] | TAGS
#transformers #pytorch #safetensors #marian #text2text-generation #translation #en #ro #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### en-ro
* source group: English
* target group: Romanian
* OPUS readme: eng-ron
* model: transformer-align
* source language(s): eng
* target language(s): mol ron
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* a sentence initial language token is required in the form of... | [
"### en-ro\n\n\n* source group: English\n* target group: Romanian\n* OPUS readme: eng-ron\n* model: transformer-align\n* source language(s): eng\n* target language(s): mol ron\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* a sentence initial language token is require... | [
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"### en-ro\n\n\n* source group: English\n* target group: Romanian\n* OPUS readme: eng-ron\n* model: transformer-align\n* source l... | [
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translation | transformers | ### en-tr
* source group: English
* target group: Turkish
* OPUS readme: [eng-tur](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-tur/README.md)
* model: transformer-align
* source language(s): eng
* target language(s): tur
* model: transformer-align
* pre-processing: normalization + Sen... | {"language": ["en", "tr"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-en-tr | null | [
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"has_space",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"en",
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] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #en #tr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### en-tr
* source group: English
* target group: Turkish
* OPUS readme: eng-tur
* model: transformer-align
* source language(s): eng
* target language(s): tur
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: opus+URL
* test set translations: opus... | [
"### en-tr\n\n\n* source group: English\n* target group: Turkish\n* OPUS readme: eng-tur\n* model: transformer-align\n* source language(s): eng\n* target language(s): tur\n* model: transformer-align\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weights: opus+URL\n* test set t... | [
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"### en-tr\n\n\n* source group: English\n* target group: Turkish\n* OPUS readme: eng-tur\n* model: transformer-align\n* source language(s)... | [
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"TAGS\n#transformers #pytorch #tf #marian #text2text-generation #translation #en #tr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n### en-tr\n\n\n* source group: English\n* target group: Turkish\n* OPUS readme: eng-tur\n* model: transformer-align\n* source language(s): eng\... |
translation | transformers | ### es-zh
* source group: Spanish
* target group: Chinese
* OPUS readme: [spa-zho](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/spa-zho/README.md)
* model: transformer
* source language(s): spa
* target language(s): cjy_Hans cjy_Hant cmn cmn_Hans cmn_Hant hsn hsn_Hani lzh nan wuu yue_Hans ... | {"language": ["es", "zh"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-es-zh | null | [
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| ### es-zh
* source group: Spanish
* target group: Chinese
* OPUS readme: spa-zho
* model: transformer
* source language(s): spa
* target language(s): cjy\_Hans cjy\_Hant cmn cmn\_Hans cmn\_Hant hsn hsn\_Hani lzh nan wuu yue\_Hans yue\_Hant
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,s... | [
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translation | transformers | ### fi-en
* source group: Finnish
* target group: English
* OPUS readme: [fin-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fin-eng/README.md)
* model: transformer-align
* source language(s): fin
* target language(s): eng
* model: transformer-align
* pre-processing: normalization + Sen... | {"language": ["fi", "en"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-fi-en | null | [
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| ### fi-en
* source group: Finnish
* target group: English
* OPUS readme: fin-eng
* model: transformer-align
* source language(s): fin
* target language(s): eng
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: opusTCv20210807+URL
* test set transla... | [
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translation | transformers | ### fr-it
* source group: French
* target group: Italian
* OPUS readme: [fra-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/fra-ita/README.md)
* model: transformer-align
* source language(s): fra
* target language(s): ita
* raw source language(s): fra
* raw target language(s): ita
* mod... | {"language": ["fr", "it"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-fr-it | null | [
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#transformers #pytorch #tf #marian #text2text-generation #translation #fr #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### fr-it
* source group: French
* target group: Italian
* OPUS readme: fra-ita
* model: transformer-align
* source language(s): fra
* target language(s): ita
* raw source language(s): fra
* raw target language(s): ita
* model: transformer-align
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* downlo... | [
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translation | transformers | ### he-fr
* source group: Hebrew
* target group: French
* OPUS readme: [heb-fra](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/heb-fra/README.md)
* model: transformer
* source language(s): heb
* target language(s): fra
* model: transformer
* pre-processing: normalization + SentencePiece (sp... | {"language": ["he", "fr"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-he-fr | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [
"he",
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] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #he #fr #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### he-fr
* source group: Hebrew
* target group: French
* OPUS readme: heb-fra
* model: transformer
* source language(s): heb
* target language(s): fra
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* test set scores: ... | [
"### he-fr\n\n\n* source group: Hebrew\n* target group: French\n* OPUS readme: heb-fra\n* model: transformer\n* source language(s): heb\n* target language(s): fra\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weights: URL\n* test set translations: URL\n*... | [
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translation | transformers | ### he-it
* source group: Hebrew
* target group: Italian
* OPUS readme: [heb-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/heb-ita/README.md)
* model: transformer
* source language(s): heb
* target language(s): ita
* model: transformer
* pre-processing: normalization + SentencePiece (s... | {"language": ["he", "it"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-he-it | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [
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] | TAGS
#transformers #pytorch #marian #text2text-generation #translation #he #it #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### he-it
* source group: Hebrew
* target group: Italian
* OPUS readme: heb-ita
* model: transformer
* source language(s): heb
* target language(s): ita
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* test set scores:... | [
"### he-it\n\n\n* source group: Hebrew\n* target group: Italian\n* OPUS readme: heb-ita\n* model: transformer\n* source language(s): heb\n* target language(s): ita\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weights: URL\n* test set translations: URL\n... | [
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translation | transformers | ### it-he
* source group: Italian
* target group: Hebrew
* OPUS readme: [ita-heb](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ita-heb/README.md)
* model: transformer
* source language(s): ita
* target language(s): heb
* model: transformer
* pre-processing: normalization + SentencePiece (s... | {"language": ["it", "he"], "license": "apache-2.0", "tags": ["translation"]} | Helsinki-NLP/opus-tatoeba-it-he | null | [
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"has_space",
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] | null | 2022-03-02T23:29:04+00:00 | [] | [
"it",
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] | TAGS
#transformers #pytorch #tf #marian #text2text-generation #translation #it #he #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| ### it-he
* source group: Italian
* target group: Hebrew
* OPUS readme: ita-heb
* model: transformer
* source language(s): ita
* target language(s): heb
* model: transformer
* pre-processing: normalization + SentencePiece (spm32k,spm32k)
* download original weights: URL
* test set translations: URL
* test set scores:... | [
"### it-he\n\n\n* source group: Italian\n* target group: Hebrew\n* OPUS readme: ita-heb\n* model: transformer\n* source language(s): ita\n* target language(s): heb\n* model: transformer\n* pre-processing: normalization + SentencePiece (spm32k,spm32k)\n* download original weights: URL\n* test set translations: URL\n... | [
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fill-mask | transformers | Thanks for checking this out! <br />
This video explains the ideas behind KerasBERT (still very much a work in progress)
https://www.youtube.com/watch?v=J3P8WLAELqk | {} | HenryAI/KerasBERTv1 | null | [
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"roberta",
"fill-mask",
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#transformers #pytorch #roberta #fill-mask #autotrain_compatible #endpoints_compatible #has_space #region-us
| Thanks for checking this out! <br />
This video explains the ideas behind KerasBERT (still very much a work in progress)
URL | [] | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-finetuned-scitldr
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "t5-base-finetuned-scitldr", "results": []}]} | HenryHXR/t5-base-finetuned-scitldr | null | [
"transformers",
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"tensorboard",
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"generated_from_trainer",
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"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| t5-base-finetuned-scitldr
=========================
This model is a fine-tuned version of t5-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.0232
* Rouge1: 35.2134
* Rouge2: 16.8919
* Rougel: 30.8442
* Rougelsum: 30.9316
* Gen Len: 18.7981
Model description
---------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 3e-06\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 2\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2\n* mixed\\_precis... | [
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text-classification | transformers |
This model predicts the time period given a synopsis of about 200 Chinese characters.
The model is trained on TV and Movie datasets and takes simplified Chinese as input.
We trained the model from the "hfl/chinese-bert-wwm-ext" checkpoint.
#### Sample Usage
from transformers import BertTokenizer, BertForSequence... | {"language": ["zh"], "license": "apache-2.0", "tags": ["classification"], "datasets": ["Custom"], "metrics": ["rouge"]} | Herais/pred_genre | null | [
"transformers",
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"text-classification",
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"zh",
"dataset:Custom",
"license:apache-2.0",
"autotrain_compatible",
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"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh"
] | TAGS
#transformers #pytorch #bert #text-classification #classification #zh #dataset-Custom #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
This model predicts the time period given a synopsis of about 200 Chinese characters.
The model is trained on TV and Movie datasets and takes simplified Chinese as input.
We trained the model from the "hfl/chinese-bert-wwm-ext" checkpoint.
#### Sample Usage
from transformers import BertTokenizer, BertForSequence... | [
"#### Sample Usage\n from transformers import BertTokenizer, BertForSequenceClassification\n \n device = URL(\"cuda\" if URL.is_available() else \"cpu\")\n checkpoint = \"Herais/pred_genre\"\n tokenizer = BertTokenizer.from_pretrained(checkpoint, \n proble... | [
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text-classification | transformers | This model predicts the time period given a synopsis of about 200 Chinese characters.
The model is trained on TV and Movie datasets and takes simplified Chinese as input.
We trained the model from the "hfl/chinese-bert-wwm-ext" checkpoint.
#### Sample Usage
from transformers import BertTokenizer, BertForSequenceC... | {"language": ["zh"], "license": "apache-2.0", "tags": ["classification"], "datasets": ["Custom"], "metrics": ["rouge"]} | Herais/pred_timeperiod | null | [
"transformers",
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"bert",
"text-classification",
"classification",
"zh",
"dataset:Custom",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"zh"
] | TAGS
#transformers #pytorch #safetensors #bert #text-classification #classification #zh #dataset-Custom #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| This model predicts the time period given a synopsis of about 200 Chinese characters.
The model is trained on TV and Movie datasets and takes simplified Chinese as input.
We trained the model from the "hfl/chinese-bert-wwm-ext" checkpoint.
#### Sample Usage
from transformers import BertTokenizer, BertForSequenceC... | [
"#### Sample Usage\n from transformers import BertTokenizer, BertForSequenceClassification\n \n device = URL(\"cuda\" if URL.is_available() else \"cpu\")\n checkpoint = \"Herais/pred_timeperiod\"\n tokenizer = BertTokenizer.from_pretrained(checkpoint, \n p... | [
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text2text-generation | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# marian-finetuned-hi-hinglish
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-hi-en](https://huggingface.co/Helsinki-NLP/op... | {"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "marian-finetuned-hi-hinglish", "results": []}]} | Hetarth/marian-finetuned-hi-hinglish | null | [
"transformers",
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"marian",
"text2text-generation",
"generated_from_keras_callback",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #tf #marian #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
| marian-finetuned-hi-hinglish
============================
This model is a fine-tuned version of Helsinki-NLP/opus-mt-hi-en on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 4.1869
* Validation Loss: 4.0607
* Epoch: 0
Model description
-----------------
More informatio... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'AdamWeightDecay', 'learning\\_rate': {'class\\_name': 'PolynomialDecay', 'config': {'initial\\_learning\\_rate': 5e-05, 'decay\\_steps': 279, 'end\\_learning\\_rate': 0.0, 'power': 1.0, 'cycle': F... | [
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text2text-generation | transformers | Create README.md
## ByT5 Base Portuguese Product Reviews
#### Model Description
This is a finetuned version from ByT5 Base by Google for Sentimental Analysis from Product Reviews in Portuguese.
##### Paper: https://arxiv.org/abs/2105.13626
#### Training data
It was trained from products reviews from a Americanas.com.... | {} | HeyLucasLeao/byt5-base-pt-product-reviews | null | [
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] | [] | TAGS
#transformers #pytorch #t5 #text2text-generation #arxiv-2105.13626 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| Create URL
## ByT5 Base Portuguese Product Reviews
#### Model Description
This is a finetuned version from ByT5 Base by Google for Sentimental Analysis from Product Reviews in Portuguese.
##### Paper: URL
#### Training data
It was trained from products reviews from a URL. You can found the data here: URL
#### Traini... | [
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text2text-generation | transformers | Create README.md
## ByT5 Small Portuguese Product Reviews
#### Model Description
This is a finetuned version from ByT5 Small by Google for Sentimental Analysis from Product Reviews in Portuguese.
##### Paper: https://arxiv.org/abs/2105.13626
#### Training data
It was trained from products reviews from a Americanas.co... | {} | HeyLucasLeao/byt5-small-pt-product-reviews | null | [
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| Create URL
## ByT5 Small Portuguese Product Reviews
#### Model Description
This is a finetuned version from ByT5 Small by Google for Sentimental Analysis from Product Reviews in Portuguese.
##### Paper: URL
#### Training data
It was trained from products reviews from a URL. You can found the data here: URL
#### Trai... | [
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text-generation | transformers | Create README.md
## Emo Bot
#### Model Description
This is a finetuned version from GPT-Neo-125M for Generating Music Lyrics by Emo Genre.
#### Training data
It was trained with 2381 songs by 15 bands that were important to emo culture in the early 2000s, not necessary directly playing on the genre.
#### Training Pr... | {} | HeyLucasLeao/gpt-neo-small-emo-lyrics | null | [
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#transformers #pytorch #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #has_space #region-us
| Create URL
## Emo Bot
#### Model Description
This is a finetuned version from GPT-Neo-125M for Generating Music Lyrics by Emo Genre.
#### Training data
It was trained with 2381 songs by 15 bands that were important to emo culture in the early 2000s, not necessary directly playing on the genre.
#### Training Procedur... | [
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text-generation | transformers | ## GPT-Neo Small Portuguese
#### Model Description
This is a finetuned version from GPT-Neo 125M by EletheurAI to Portuguese language.
#### Training data
It was trained from 227,382 selected texts from a PTWiki Dump. You can found all the data from here: https://archive.org/details/ptwiki-dump-20210520
#### Trainin... | {} | HeyLucasLeao/gpt-neo-small-portuguese | null | [
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#transformers #pytorch #gpt_neo #text-generation #autotrain_compatible #endpoints_compatible #region-us
| ## GPT-Neo Small Portuguese
#### Model Description
This is a finetuned version from GPT-Neo 125M by EletheurAI to Portuguese language.
#### Training data
It was trained from 227,382 selected texts from a PTWiki Dump. You can found all the data from here: URL
#### Training Procedure
Every text was passed through a G... | [
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null | null | # Convert Fairseq Wav2Vec2 to HF
This repo has two scripts that can show how to convert a fairseq checkpoint to HF Transformers.
It's important to always check in a forward pass that the two checkpoints are the same. The procedure should be as follows:
1. Download original model
2. Create HF version of the model:
``... | {} | HfSpeechUtils/convert_wav2vec2_to_hf | null | [
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#region-us
| # Convert Fairseq Wav2Vec2 to HF
This repo has two scripts that can show how to convert a fairseq checkpoint to HF Transformers.
It's important to always check in a forward pass that the two checkpoints are the same. The procedure should be as follows:
1. Download original model
2. Create HF version of the model:
3... | [
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null | null | # Run any CTC model
```python
./run_ctc_model.py "yourModelId" "yourLanguageCode" "yourPhonemeLang" "NumSamplesToDecode"
```
| {} | HfSpeechUtils/run_ctc_common_voice.py | null | [
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-cola
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["matthews_correlation"], "model_index": [{"name": "distilbert-base-uncased-finetuned-cola", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "glue", "type": "glue", "ar... | Hinova/distilbert-base-uncased-finetuned-cola | null | [
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| distilbert-base-uncased-finetuned-cola
======================================
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset.
It achieves the following results on the evaluation set:
* Loss: 0.8301
* Matthews Correlation: 0.5481
Model description
-----------------
More informa... | [
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question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["squad"]} | Hoang/distilbert-base-uncased-finetuned-squad | null | [
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| distilbert-base-uncased-finetuned-squad
=======================================
This model is a fine-tuned version of distilbert-base-uncased on the squad dataset.
It achieves the following results on the evaluation set:
* Loss: 1.1582
Model description
-----------------
More information needed
Intended uses ... | [
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text-generation | transformers | KOD file | {} | HoeioUser/kod | null | [
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token-classification | transformers | Testing NER | {} | Holako/NER_CAMELBERT | null | [
"transformers",
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"bert",
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"region:us"
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#transformers #pytorch #bert #token-classification #autotrain_compatible #endpoints_compatible #region-us
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token-classification | transformers |
#### How to use
You can use this model with Transformers *pipeline* for NER.
```python
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("Holako/NER_model_holako")
model = AutoModelForTokenClassification.from_pretrained("... | {} | Holako/NER_model_holako | null | [
"transformers",
"pytorch",
"xlm-roberta",
"token-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #xlm-roberta #token-classification #autotrain_compatible #endpoints_compatible #region-us
| #### How to use
You can use this model with Transformers *pipeline* for NER.
#### Limitations and bias
This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.
=======
#### Limitations and... | [
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text-generation | transformers |
# Harry Potter DialoGPT Model | {"tags": ["conversational"]} | MagnusChase7/DialoGPT-medium-harrypotter | null | [
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"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
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token-classification | transformers |
# AlbertNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covered te... | {"language": "fa"} | HooshvareLab/albert-fa-zwnj-base-v2-ner | null | [
"transformers",
"pytorch",
"tf",
"albert",
"token-classification",
"fa",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #tf #albert #token-classification #fa #autotrain_compatible #endpoints_compatible #region-us
| AlbertNER
=========
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from ARMAN, PEYMA, and WikiANN that covered ten types of entities:
* Date (DAT)
* Event (EVE)
* Facility (FAC)
* Location (LOC)
* Money (MON)
* Organization (ORG)
* Percent (PCT)
* Person (PER)
* P... | [
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] |
fill-mask | transformers |
# ALBERT-Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
> Call it little_berty
### BibTeX entry and citation info
Please cite in your publication as the following:
```bibtex
@misc{ALBERTPersian,
author = {Hooshvare Team},
tit... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/albert-fa-zwnj-base-v2 | null | [
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"tf",
"albert",
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"fa",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"fa"
] | TAGS
#transformers #pytorch #tf #albert #fill-mask #fa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# ALBERT-Persian
A Lite BERT for Self-supervised Learning of Language Representations for the Persian Language
> میتونی بهش بگی برت_کوچولو
> Call it little_berty
### BibTeX entry and citation info
Please cite in your publication as the following:
## Questions?
Post a Github issue on the ALBERT-Persian repo. | [
"# ALBERT-Persian\n\nA Lite BERT for Self-supervised Learning of Language Representations for the Persian Language\n\n> میتونی بهش بگی برت_کوچولو\n\n> Call it little_berty",
"### BibTeX entry and citation info\n\nPlease cite in your publication as the following:",
"## Questions?\nPost a Github issue on the ALBE... | [
"TAGS\n#transformers #pytorch #tf #albert #fill-mask #fa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"# ALBERT-Persian\n\nA Lite BERT for Self-supervised Learning of Language Representations for the Persian Language\n\n> میتونی بهش بگی برت_کوچولو\n\n> Call it little_berty",
"... | [
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"TAGS\n#transformers #pytorch #tf #albert #fill-mask #fa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# ALBERT-Persian\n\nA Lite BERT for Self-supervised Learning of Language Representations for the Persian Language\n\n> میتونی بهش بگی برت_کوچولو\n\n> Call it little_berty### BibTeX e... |
token-classification | transformers |
## ParsBERT: Transformer-based Model for Persian Language Understanding
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: [arXiv:2005.12515](https://arxiv.org/abs/2005.12515)
All the models (downstream tasks) are uncas... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-base-parsbert-armanner-uncased | null | [
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| ParsBERT: Transformer-based Model for Persian Language Understanding
--------------------------------------------------------------------
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: arXiv:2005.12515
All the mode... | [
"### ARMAN\n\n\nARMAN dataset holds 7,682 sentences with 250,015 sentences tagged over six different classes.\n\n\n1. Organization\n2. Location\n3. Facility\n4. Event\n5. Product\n6. Person\n\n\n\nDownload\nYou can download the dataset from here\n\n\nResults\n-------\n\n\nThe following table summarizes the F1 score... | [
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token-classification | transformers |
## ParsBERT: Transformer-based Model for Persian Language Understanding
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: [arXiv:2005.12515](https://arxiv.org/abs/2005.12515)
All the models (downstream tasks) are uncas... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-base-parsbert-ner-uncased | null | [
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| ParsBERT: Transformer-based Model for Persian Language Understanding
--------------------------------------------------------------------
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: arXiv:2005.12515
All the mode... | [
"### PEYMA\n\n\nPEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes.\n\n\n1. Organization\n2. Money\n3. Location\n4. Date\n5. Time\n6. Person\n7. Percent\n\n\n\nDownload\nYou can download the dataset from here\n\n\n\n\n---",
"### A... | [
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token-classification | transformers |
## ParsBERT: Transformer-based Model for Persian Language Understanding
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: [arXiv:2005.12515](https://arxiv.org/abs/2005.12515)
All the models (downstream tasks) are uncas... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-base-parsbert-peymaner-uncased | null | [
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| ParsBERT: Transformer-based Model for Persian Language Understanding
--------------------------------------------------------------------
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: arXiv:2005.12515
All the mode... | [
"### PEYMA\n\n\nPEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes.\n\n\n1. Organization\n2. Money\n3. Location\n4. Date\n5. Time\n6. Person\n7. Percent\n\n\n\nDownload\nYou can download the dataset from here\n\n\nResults\n-------\n... | [
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fill-mask | transformers | ## ParsBERT: Transformer-based Model for Persian Language Understanding
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: [arXiv:2005.12515](https://arxiv.org/abs/2005.12515)
All the models (downstream tasks) are uncase... | {} | HooshvareLab/bert-base-parsbert-uncased | null | [
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| ParsBERT: Transformer-based Model for Persian Language Understanding
--------------------------------------------------------------------
ParsBERT is a monolingual language model based on Google’s BERT architecture with the same configurations as BERT-Base.
Paper presenting ParsBERT: arXiv:2005.12515
All the mode... | [
"### Sentiment Analysis (SA) task",
"### Text Classification (TC) task",
"### Named Entity Recognition (NER) task\n\n\n\nIf you tested ParsBERT on a public dataset and you want to add your results to the table above, open a pull request or contact us. Also make sure to have your code available online so we can ... | [
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text-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) r... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-clf-digimag | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### DigiMag\n\n\nA total of 8,515 articles scraped from Digikala Online Magazine. This dataset includes seven different classes.\n\n\n1. Video Games\n2. Shopping Guide\n3. Health Beauty\n4. Science Technology\n5. General\n6. Art Cinema\n7. Books Literature\n\n\n\nDownload\nYou can download the dataset from here\n\... | [
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text-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) r... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-clf-persiannews | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### Persian News\n\n\nA dataset of various news articles scraped from different online news agencies' websites. The total number of articles is 16,438, spread over eight different classes.\n\n\n1. Economic\n2. International\n3. Political\n4. Science Technology\n5. Cultural Art\n6. Sport\n7. Medical\n\n\n\nDownload... | [
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token-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) re... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-ner-arman | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### ARMAN\n\n\nARMAN dataset holds 7,682 sentences with 250,015 sentences tagged over six different classes.\n\n\n1. Organization\n2. Location\n3. Facility\n4. Event\n5. Product\n6. Person\n\n\n\nDownload\nYou can download the dataset from here\n\n\nResults\n-------\n\n\nThe following table summarizes the F1 score... | [
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token-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) re... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-ner-peyma | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### PEYMA\n\n\nPEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes.\n\n\n1. Organization\n2. Money\n3. Location\n4. Date\n5. Time\n6. Person\n7. Percent\n\n\n\nDownload\nYou can download the dataset from here\n\n\nResults\n-------\n... | [
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text-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) re... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-binary | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### DeepSentiPers\n\n\nwhich is a balanced and augmented version of SentiPers, contains 12,138 user opinions about digital products labeled with five different classes; two positives (i.e., happy and delighted), two negatives (i.e., furious and angry) and one neutral class. Therefore, this dataset can be utilized ... | [
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text-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) re... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### DeepSentiPers\n\n\nwhich is a balanced and augmented version of SentiPers, contains 12,138 user opinions about digital products labeled with five different classes; two positives (i.e., happy and delighted), two negatives (i.e., furious and angry) and one neutral class. Therefore, this dataset can be utilized ... | [
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text-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) re... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-sentiment-digikala | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### Digikala\n\n\nDigikala user comments provided by Open Data Mining Program (ODMP). This dataset contains 62,321 user comments with three labels:\n\n\n\nDownload\nYou can download the dataset from here\n\n\nResults\n-------\n\n\nThe following table summarizes the F1 score obtained by ParsBERT as compared to othe... | [
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"### Digikala\n\n\nDigikala user comments provided by Open Data Mining Program (ODMP). This dataset contains 62,321 user comments with three labels:\n\n\n\nDownload... | [
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"TAGS\n#transformers #pytorch #tf #jax #bert #text-classification #fa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n### Digikala\n\n\nDigikala user comments provided by Open Data Mining Program (ODMP). This dataset contains 62,321 user comments with three labels:\n\n\n\nDownload\nYou ... |
text-classification | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) re... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-base-uncased-sentiment-snappfood | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### SnappFood\n\n\nSnappfood (an online food delivery company) user comments containing 70,000 comments with two labels (i.e. polarity classification):\n\n\n1. Happy\n2. Sad\n\n\n\nDownload\nYou can download the dataset from here\n\n\nResults\n-------\n\n\nThe following table summarizes the F1 score obtained by Pa... | [
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fill-mask | transformers |
# ParsBERT (v2.0)
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the [ParsBERT](https://github.com/hooshvare/parsbert) r... | {"language": "fa", "license": "apache-2.0", "tags": ["bert-fa", "bert-persian", "persian-lm"]} | HooshvareLab/bert-fa-base-uncased | null | [
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| ParsBERT (v2.0)
===============
A Transformer-based Model for Persian Language Understanding
We reconstructed the vocabulary and fine-tuned the ParsBERT v1.1 on the new Persian corpora in order to provide some functionalities for using ParsBERT in other scopes!
Please follow the ParsBERT repo for the latest informa... | [
"### How to use",
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"#### Pytorch\n\n\nTraining\n--------\n\n\nParsBERT trained on a massive amount of public corpora (Persian Wikidumps, MirasText) and six other manually crawled text data from a various type of websites (BigBang Page 'scientific', Chetor 'lifestyle', Eligasht 'itinerary',... | [
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token-classification | transformers |
# BertNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covered ten ... | {"language": "fa"} | HooshvareLab/bert-fa-zwnj-base-ner | null | [
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#transformers #pytorch #tf #jax #bert #token-classification #fa #autotrain_compatible #endpoints_compatible #region-us
| BertNER
=======
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from ARMAN, PEYMA, and WikiANN that covered ten types of entities:
* Date (DAT)
* Event (EVE)
* Facility (FAC)
* Location (LOC)
* Money (MON)
* Organization (ORG)
* Percent (PCT)
* Person (PER)
* Produ... | [
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"### How to predict using pipeline\n\n\nQuestions?\n----------\n\n\nPost a Github issue on the ParsNER Issues repo."
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] |
fill-mask | transformers |
# ParsBERT (v3.0)
A Transformer-based Model for Persian Language Understanding
The new version of BERT v3.0 for Persian is available today and can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Introduction
Par... | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/bert-fa-zwnj-base | null | [
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|
# ParsBERT (v3.0)
A Transformer-based Model for Persian Language Understanding
The new version of BERT v3.0 for Persian is available today and can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Introduction
Par... | [
"# ParsBERT (v3.0)\nA Transformer-based Model for Persian Language Understanding\n\nThe new version of BERT v3.0 for Persian is available today and can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.",
"## Introdu... | [
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token-classification | transformers |
# DistilbertNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covere... | {"language": "fa"} | HooshvareLab/distilbert-fa-zwnj-base-ner | null | [
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"token-classification",
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"fa"
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#transformers #pytorch #tf #distilbert #token-classification #fa #autotrain_compatible #endpoints_compatible #region-us
| DistilbertNER
=============
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from ARMAN, PEYMA, and WikiANN that covered ten types of entities:
* Date (DAT)
* Event (EVE)
* Facility (FAC)
* Location (LOC)
* Money (MON)
* Organization (ORG)
* Percent (PCT)
* Person (... | [
"### Installing requirements",
"### How to predict using pipeline\n\n\nQuestions?\n----------\n\n\nPost a Github issue on the ParsNER Issues repo."
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] |
fill-mask | transformers |
# DistilBERT
This model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Questions?
Post a Github issue on the [ParsBERT Issues](https://github.com/hooshvare/parsbert/issues) repo. | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/distilbert-fa-zwnj-base | null | [
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] | null | 2022-03-02T23:29:04+00:00 | [] | [
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|
# DistilBERT
This model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Questions?
Post a Github issue on the ParsBERT Issues repo. | [
"# DistilBERT\n\nThis model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.",
"## Questions?\nPost a Github issue on the ParsBERT Issues repo."
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text-generation | transformers |
# Persian Comment Generator
The model can generate comments based on your aspects, and the model was fine-tuned on [persiannlp/parsinlu](https://github.com/persiannlp/parsinlu). Currently, the model only supports aspects in the food and movie scope. You can see the whole aspects in the following section.
## Commen... | {"language": "fa", "license": "apache-2.0", "widget": [{"text": "<s>\u0646\u0645\u0648\u0646\u0647 \u062f\u06cc\u062f\u06af\u0627\u0647 \u0647\u0645 \u062e\u0648\u0628 \u0647\u0645 \u0628\u062f \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc <sep>"}, {"text": "<s>\u0646\u0645\u0648\u0646\u0647 \u062f\u06cc\u062f\u06... | HooshvareLab/gpt2-fa-comment | null | [
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|
# Persian Comment Generator
The model can generate comments based on your aspects, and the model was fine-tuned on persiannlp/parsinlu. Currently, the model only supports aspects in the food and movie scope. You can see the whole aspects in the following section.
## Comments Aspects
## Questions?
Post a Github ... | [
"# Persian Comment Generator \n\nThe model can generate comments based on your aspects, and the model was fine-tuned on persiannlp/parsinlu. Currently, the model only supports aspects in the food and movie scope. You can see the whole aspects in the following section.",
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text-generation | transformers |
# Persian Poet GPT2
## Poets
The model can generate poetry based on your favorite poet, and you need to add one of the following lines as the input the box on the right side or follow the [fine-tuning notebook](https://colab.research.google.com/github/hooshvare/parsgpt/blob/master/notebooks/Persian_Poetry_FineTuning... | {"language": "fa", "license": "apache-2.0", "widget": [{"text": "<s>\u0631\u0648\u062f\u06a9\u06cc<|startoftext|>"}, {"text": "<s>\u0641\u0631\u062f\u0648\u0633\u06cc<|startoftext|>"}, {"text": "<s>\u062e\u06cc\u0627\u0645<|startoftext|>"}, {"text": "<s>\u0639\u0637\u0627\u0631<|startoftext|>"}, {"text": "<s>\u0646\u06... | HooshvareLab/gpt2-fa-poetry | null | [
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|
# Persian Poet GPT2
## Poets
The model can generate poetry based on your favorite poet, and you need to add one of the following lines as the input the box on the right side or follow the fine-tuning notebook.
## Questions?
Post a Github issue on the ParsGPT2 Issues repo. | [
"# Persian Poet GPT2",
"## Poets\nThe model can generate poetry based on your favorite poet, and you need to add one of the following lines as the input the box on the right side or follow the fine-tuning notebook.",
"## Questions?\nPost a Github issue on the ParsGPT2 Issues repo."
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text-generation | transformers |
# ParsGPT2
### BibTeX entry and citation info
Please cite in publications as the following:
```bibtex
@misc{ParsGPT2,
author = {Hooshvare Team},
title = {ParsGPT2 the Persian version of GPT2},
year = {2021},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/ho... | {"language": "fa", "license": "apache-2.0", "widget": [{"text": "\u062f\u0631 \u06cc\u06a9 \u0627\u062a\u0641\u0627\u0642 \u0634\u06af\u0641\u062a \u0627\u0646\u06af\u06cc\u0632\u060c \u067e\u0698\u0648\u0647\u0634\u06af\u0631\u0627\u0646"}, {"text": "\u06af\u0631\u0641\u062a\u06af\u06cc \u0628\u06cc\u0646\u06cc \u062f... | HooshvareLab/gpt2-fa | null | [
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|
# ParsGPT2
### BibTeX entry and citation info
Please cite in publications as the following:
## Questions?
Post a Github issue on the ParsGPT2 Issues repo. | [
"# ParsGPT2",
"### BibTeX entry and citation info\n\nPlease cite in publications as the following:",
"## Questions?\nPost a Github issue on the ParsGPT2 Issues repo."
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"# ParsGPT2",
"### BibTeX entry and citation info\n\nPlease cite in publications as the following:",
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token-classification | transformers |
# RobertaNER
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from [ARMAN](https://github.com/HaniehP/PersianNER), [PEYMA](http://nsurl.org/2019-2/tasks/task-7-named-entity-recognition-ner-for-farsi/), and [WikiANN](https://elisa-ie.github.io/wikiann/) that covered t... | {"language": "fa"} | HooshvareLab/roberta-fa-zwnj-base-ner | null | [
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#transformers #pytorch #tf #jax #roberta #token-classification #fa #autotrain_compatible #endpoints_compatible #region-us
| RobertaNER
==========
This model fine-tuned for the Named Entity Recognition (NER) task on a mixed NER dataset collected from ARMAN, PEYMA, and WikiANN that covered ten types of entities:
* Date (DAT)
* Event (EVE)
* Facility (FAC)
* Location (LOC)
* Money (MON)
* Organization (ORG)
* Percent (PCT)
* Person (PER)
*... | [
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] |
fill-mask | transformers |
# Roberta
This model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Questions?
Post a Github issue on the [ParsRoBERTa Issues](https://github.com/hooshvare/parsbert/issues) repo. | {"language": "fa", "license": "apache-2.0"} | HooshvareLab/roberta-fa-zwnj-base | null | [
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#transformers #pytorch #tf #jax #roberta #fill-mask #fa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# Roberta
This model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.
## Questions?
Post a Github issue on the ParsRoBERTa Issues repo. | [
"# Roberta\nThis model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.",
"## Questions?\nPost a Github issue on the ParsRoBERTa Issues repo."
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"TAGS\n#transformers #pytorch #tf #jax #roberta #fill-mask #fa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us \n# Roberta\nThis model can tackle the zero-width non-joiner character for Persian writing. Also, the model was trained on new multi-types corpora with a new set of vocabulary.##... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-base-bne-finetuned-amazon_reviews_multi
This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggin... | {"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "datasets": ["amazon_reviews_multi"], "metrics": ["accuracy"], "model_index": [{"name": "roberta-base-bne-finetuned-amazon_reviews_multi", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "dataset": {"name": "amazon_reviews... | Hormigo/roberta-base-bne-finetuned-amazon_reviews_multi | null | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"text-classification",
"generated_from_trainer",
"dataset:amazon_reviews_multi",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-amazon_reviews_multi #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us
| roberta-base-bne-finetuned-amazon\_reviews\_multi
=================================================
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the amazon\_reviews\_multi dataset.
It achieves the following results on the evaluation set:
* Loss: 0.2275
* Accuracy: 0.9335
Model description
--... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 2",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #dataset-amazon_reviews_multi #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\... | [
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text-generation | transformers |
# SpongeBob DialoGPT Model | {"tags": ["conversational"]} | Htenn/DialoGPT-small-spongebob | null | [
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"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
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] |
text-generation | transformers |
# SpongeBob DialoGPT Model | {"tags": ["conversational"]} | Htenn/DialoGPT-small-spongebobv2 | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# SpongeBob DialoGPT Model | [
"# SpongeBob DialoGPT Model"
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] |
text-generation | transformers |
#Rick Sanchez DiaoloGPT Model | {"tags": ["conversational"]} | HueJanus/DialoGPT-small-ricksanchez | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"conversational",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [] | TAGS
#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
#Rick Sanchez DiaoloGPT Model | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
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39
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"TAGS\n#transformers #pytorch #gpt2 #text-generation #conversational #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
token-classification | spacy | | Feature | Description |
| --- | --- |
| **Name** | `en_roberta_base_leetspeak_ner` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.2.1,<3.3.0` |
| **Default Pipeline** | `transformer`, `ner` |
| **Components** | `transformer`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | [roberta-b... | {"language": ["en"], "license": "apache-2.0", "tags": ["spacy", "token-classification"], "widget": [{"text": "But one other thing that we have to re;think is the way that we dy\u00a3 our #c!l.o|th?\u00a3+s.", "example_title": "Word camouflage detection"}]} | Huertas97/en_roberta_base_leetspeak_ner | null | [
"spacy",
"token-classification",
"en",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"en"
] | TAGS
#spacy #token-classification #en #license-apache-2.0 #model-index #region-us
|
### Label Scheme
View label scheme (4 labels for 1 components)
### Accuracy
| [
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"### Accuracy"
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] |
token-classification | spacy | | Feature | Description |
| --- | --- |
| **Name** | `es_roberta_base_bne_leetspeak_ner` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.2.1,<3.3.0` |
| **Default Pipeline** | `transformer`, `ner` |
| **Components** | `transformer`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | [PlanT... | {"language": ["es"], "license": "apache-2.0", "tags": ["spacy", "token-classification"], "widget": [{"text": "La C0v!d es un 3ng@\u00f1o de los G0b!3rno$", "example_title": "Word camouflage detection"}]} | Huertas97/es_roberta_base_bne_leetspeak_ner | null | [
"spacy",
"token-classification",
"es",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2022-03-02T23:29:04+00:00 | [] | [
"es"
] | TAGS
#spacy #token-classification #es #license-apache-2.0 #model-index #region-us
|
### Label Scheme
View label scheme (4 labels for 1 components)
### Accuracy
| [
"### Label Scheme\n\n\n\nView label scheme (4 labels for 1 components)",
"### Accuracy"
] | [
"TAGS\n#spacy #token-classification #es #license-apache-2.0 #model-index #region-us \n",
"### Label Scheme\n\n\n\nView label scheme (4 labels for 1 components)",
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"TAGS\n#spacy #token-classification #es #license-apache-2.0 #model-index #region-us \n### Label Scheme\n\n\n\nView label scheme (4 labels for 1 components)### Accuracy"
] |
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