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fill-mask | transformers |
# HPLT Bert for Danish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["da"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_da | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"da",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:14:47+00:00 | [
"2403.14009"
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"da"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #da #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Danish
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Danish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
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fill-mask | transformers |
# HPLT Bert for German
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["de"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_de | null | [
"transformers",
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"fill-mask",
"BERT",
"HPLT",
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"custom_code",
"de",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:15:14+00:00 | [
"2403.14009"
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"de"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #de #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for German
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for German\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #de #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for German\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models train... | [
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fill-mask | transformers |
# HPLT Bert for Greek
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["el"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_el | null | [
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"el",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:15:37+00:00 | [
"2403.14009"
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"el"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #el #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Greek
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
"# HPLT Bert for Greek\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT ... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #el #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
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null | null | GGUF-IQ-Imatrix quants for NLPark/Test1_SLIDE as requested in [#28](https://huggingface.co/Lewdiculous/Model-Requests/discussions/28).
> [!WARNING]
> Recommended presets [here](https://huggingface.co/Lewdiculous/Model-Requests/tree/main/data/presets/cope-llama-3-0.1) or [here](https://huggingface.co/Virt-io/SillyTaver... | {"license": "apache-2.0"} | Lewdiculous/Test2_SLIDE-GGUF-IQ-Imatrix | null | [
"gguf",
"license:apache-2.0",
"region:us"
] | null | 2024-04-22T01:16:02+00:00 | [] | [] | TAGS
#gguf #license-apache-2.0 #region-us
| GGUF-IQ-Imatrix quants for NLPark/Test1_SLIDE as requested in #28.
> [!WARNING]
> Recommended presets here or here. <br>
> Use the latest version of KoboldCpp. Use the provided presets. <br>
> This is all still highly experimental, modified configs were used to avoid the tokenizer issues.
"Due to the poor performance... | [] | [
"TAGS\n#gguf #license-apache-2.0 #region-us \n"
] | [
17
] | [
"TAGS\n#gguf #license-apache-2.0 #region-us \n"
] |
fill-mask | transformers |
# HPLT Bert for Esperanto
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we use... | {"language": ["eo"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_eo | null | [
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"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"eo",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:16:06+00:00 | [
"2403.14009"
] | [
"eo"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #eo #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Esperanto
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is... | [
"# HPLT Bert for Esperanto\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-B... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #eo #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
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text-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. -->
# ppo_zephyr1
This model is a fine-tuned version of [HuggingFaceH4/mistral-7b-sft-beta](https://huggingface.co/HuggingFaceH4/mistr... | {"license": "mit", "tags": ["generated_from_trainer"], "base_model": "HuggingFaceH4/mistral-7b-sft-beta", "model-index": [{"name": "ppo_zephyr1", "results": []}]} | vwxyzjn/ppo_zephyr1 | null | [
"transformers",
"tensorboard",
"safetensors",
"mistral",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:HuggingFaceH4/mistral-7b-sft-beta",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-22T01:16:21+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #mistral #text-generation #generated_from_trainer #conversational #base_model-HuggingFaceH4/mistral-7b-sft-beta #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# ppo_zephyr1
This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperpar... | [
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"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training proced... | [
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fill-mask | transformers |
# HPLT Bert for Spanish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["es"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_es | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"es",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:16:32+00:00 | [
"2403.14009"
] | [
"es"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #es #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Spanish
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Spanish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #es #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Spanish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #es #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Spanish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Estonian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["et"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_et | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
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"et",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:16:56+00:00 | [
"2403.14009"
] | [
"et"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #et #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Estonian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
"# HPLT Bert for Estonian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BE... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #et #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Estonian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tra... | [
72,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #et #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Estonian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained a... |
fill-mask | transformers |
# HPLT Bert for Basque
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["eu"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_eu | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"eu",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:17:19+00:00 | [
"2403.14009"
] | [
"eu"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #eu #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Basque
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Basque\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #eu #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Basque\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models train... | [
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #eu #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Basque\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as ... |
reinforcement-learning | null |
# **Reinforce** Agent playing **Pixelcopter-PLE-v0**
This is a trained model of a **Reinforce** agent playing **Pixelcopter-PLE-v0** .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit4/introduction
| {"tags": ["Pixelcopter-PLE-v0", "reinforce", "reinforcement-learning", "custom-implementation", "deep-rl-class"], "model-index": [{"name": "Reinforce-Unit4", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "Pixelcopter-PLE-v0", "type": "Pixelcopter-PLE-v0"}... | Saraaaaaaaaa/Reinforce-Unit4 | null | [
"Pixelcopter-PLE-v0",
"reinforce",
"reinforcement-learning",
"custom-implementation",
"deep-rl-class",
"model-index",
"region:us"
] | null | 2024-04-22T01:17:36+00:00 | [] | [] | TAGS
#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us
|
# Reinforce Agent playing Pixelcopter-PLE-v0
This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .
To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL
| [
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of the Deep Reinforcement Learning Course: URL"
] | [
"TAGS\n#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n",
"# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of ... | [
37,
56
] | [
"TAGS\n#Pixelcopter-PLE-v0 #reinforce #reinforcement-learning #custom-implementation #deep-rl-class #model-index #region-us \n# Reinforce Agent playing Pixelcopter-PLE-v0\n This is a trained model of a Reinforce agent playing Pixelcopter-PLE-v0 .\n To learn to use this model and train yours check Unit 4 of the De... |
fill-mask | transformers |
# HPLT Bert for Persian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["fa"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_fa | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"fa",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:17:43+00:00 | [
"2403.14009"
] | [
"fa"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fa #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Persian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Persian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fa #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Persian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fa #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Persian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Finnish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["fi"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_fi | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"fi",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:18:04+00:00 | [
"2403.14009"
] | [
"fi"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fi #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Finnish
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Finnish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fi #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Finnish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fi #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Finnish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
text-generation | null |
## Llamacpp iMatrix Quantizations of Meta-Llama-3-8B-Instruct
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b2710">b2710</a> for quantization.
Original model: https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct
All q... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Date: April 18, 2024\n\"Agreemen... | nitsuai/Meta-Llama-3-8B-Instruct-GGUF | null | [
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"text-generation",
"en",
"license:other",
"region:us"
] | null | 2024-04-22T01:18:13+00:00 | [] | [
"en"
] | TAGS
#gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us
| Llamacpp iMatrix Quantizations of Meta-Llama-3-8B-Instruct
----------------------------------------------------------
Using <a href="URL release <a href="URL for quantization.
Original model: URL
All quants made using imatrix option with dataset provided by Kalomaze here
Prompt format
-------------
Download a... | [] | [
"TAGS\n#gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us \n"
] | [
36
] | [
"TAGS\n#gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us \n"
] |
fill-mask | transformers |
# HPLT Bert for French
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["fr"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_fr | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"fr",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:18:33+00:00 | [
"2403.14009"
] | [
"fr"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fr #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for French
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for French\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fr #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for French\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models train... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #fr #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for French\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as ... |
fill-mask | transformers |
# HPLT Bert for Irish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["ga"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ga | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"ga",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:19:07+00:00 | [
"2403.14009"
] | [
"ga"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ga #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Irish
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
"# HPLT Bert for Irish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT ... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ga #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Irish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models traine... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ga #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Irish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a... |
text-generation | null |
## Llamacpp Quantizations of Meta-Llama-3-70B-Instruct
Since official Llama 3 support has arrived to llama.cpp release, I will be remaking this entirely and uploading as soon as it's done.
This model has the <|eot_id|> token set to not-special, which seems to work better with current inference engines.
Using <a hre... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Date: April 18, 2024\n\"Agreemen... | nitsuai/Meta-Llama-3-70B-Instruct-GGUF | null | [
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"text-generation",
"en",
"license:other",
"region:us"
] | null | 2024-04-22T01:19:26+00:00 | [] | [
"en"
] | TAGS
#gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us
| Llamacpp Quantizations of Meta-Llama-3-70B-Instruct
---------------------------------------------------
Since official Llama 3 support has arrived to URL release, I will be remaking this entirely and uploading as soon as it's done.
This model has the <|eot\_id|> token set to not-special, which seems to work better ... | [] | [
"TAGS\n#gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us \n"
] | [
36
] | [
"TAGS\n#gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #en #license-other #region-us \n"
] |
fill-mask | transformers |
# HPLT Bert for Galician
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["gl"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_gl | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"gl",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:19:30+00:00 | [
"2403.14009"
] | [
"gl"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #gl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Galician
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
"# HPLT Bert for Galician\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BE... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #gl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Galician\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tra... | [
73,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #gl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Galician\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained a... |
fill-mask | transformers |
# HPLT Bert for Gujarati
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["gu"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_gu | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"gu",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:19:55+00:00 | [
"2403.14009"
] | [
"gu"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #gu #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Gujarati
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
"# HPLT Bert for Gujarati\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BE... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #gu #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Gujarati\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tra... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #gu #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Gujarati\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained a... |
fill-mask | transformers |
# HPLT Bert for Serbo-Croatian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, w... | {"language": ["hbs"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_hbs | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"hbs",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:20:19+00:00 | [
"2403.14009"
] | [
"hbs"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #hbs #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Serbo-Croatian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT mod... | [
"# HPLT Bert for Serbo-Croatian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual ... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #hbs #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Serbo-Croatian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language mod... | [
73,
203,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #hbs #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Serbo-Croatian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tr... |
null | null |
```
e88 88e d8
d888 888b 8888 8888 ,"Y88b 888 8e d88
C8888 8888D 8888 8888 "8" 888 888 88b d88888
Y888 888P Y888 888P ,ee 888 888 888 888
"88 88" "88 88" "88 888 888 888 888
b
8b, ... | {"license": "cc-by-nc-4.0"} | Quant-Cartel/Llama-3-8B-Instruct-DADA-exl2-rpcal | null | [
"license:cc-by-nc-4.0",
"region:us"
] | null | 2024-04-22T01:20:37+00:00 | [] | [] | TAGS
#license-cc-by-nc-4.0 #region-us
|
# Llama-3-8B-Instruct-DADA-exl2-rpcal
Quantized using 200 samples of 8192 tokens from an RP-oriented PIPPA dataset.
Branches:
- 'main' -- 'URL'
- '8b8h' -- 8bpw, 8bit lm_head
- '6b6h' -- 6bpw, 6bit lm_head
- '4b6h' -- 4bpw, 6bit lm_head
Original model link: Envoid/Llama-3-8B-Instruct-DADA
Original model README be... | [
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fill-mask | transformers |
# HPLT Bert for Hebrew
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["he"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_he | null | [
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|
# HPLT Bert for Hebrew
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | epiverseai/test1 | null | [
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# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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fill-mask | transformers |
# HPLT Bert for Hindi
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["hi"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_hi | null | [
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# HPLT Bert for Hindi
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
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fill-mask | transformers |
# HPLT Bert for Hungarian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we use... | {"language": ["hu"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_hu | null | [
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|
# HPLT Bert for Hungarian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is... | [
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text-generation | transformers |
## Llamacpp iMatrix Quantizations of llama-3-neural-chat-v1-8b
This model has the <|eot_id|> token set to not-special, which seems to work better with current inference engines.
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> fork from pcuenca <a href="https://github.com/pcuenca/llama.cpp/tree/... | {"license": "other", "library_name": "transformers", "datasets": ["mlabonne/orpo-dpo-mix-40k", "Open-Orca/SlimOrca-Dedup", "jondurbin/airoboros-3.2", "microsoft/orca-math-word-problems-200k", "m-a-p/Code-Feedback", "MaziyarPanahi/WizardLM_evol_instruct_V2_196k"], "base_model": "meta-llama/Meta-Llama-3-8B", "quantized_b... | nitsuai/llama-3-neural-chat-v1-8b-GGUF | null | [
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-----------------------------------------------------------
This model has the <|eot\_id|> token set to not-special, which seems to work better with current inference engines.
Using <a href="URL fork from pcuenca <a href="URL for quantization.
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned-adapters_Gpt4_t1_tiny_Seed103 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Shared by [optional]:
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- Language(s) (NLP):
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- Finetuned from model [optional]:
### Model Sources [optional]
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fill-mask | transformers |
# HPLT Bert for Armenian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["hy"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_hy | null | [
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|
# HPLT Bert for Armenian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_Gpt4_t1_tiny_Seed103 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Shared by [optional]:
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- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | relu-ntnu/bart-large-cnn_v4_trained_on_1000_lr_1e-4 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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fill-mask | transformers |
# HPLT Bert for Indonesian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we us... | {"language": ["id"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_id | null | [
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"region:us"
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#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #id #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Indonesian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model i... | [
"# HPLT Bert for Indonesian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #id #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Indonesian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models t... | [
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #id #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Indonesian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained... |
fill-mask | transformers |
# HPLT Bert for Icelandic
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we use... | {"language": ["is"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_is | null | [
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"region:us"
] | null | 2024-04-22T01:22:54+00:00 | [
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"is"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #is #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Icelandic
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is... | [
"# HPLT Bert for Icelandic\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-B... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #is #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Icelandic\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tr... | [
72,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #is #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Icelandic\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained ... |
fill-mask | transformers |
# HPLT Bert for Italian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["it"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_it | null | [
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"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:23:18+00:00 | [
"2403.14009"
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"it"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #it #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Italian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Italian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #it #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Italian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #it #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Italian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Japanese
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["ja"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ja | null | [
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"custom_code",
"ja",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:23:44+00:00 | [
"2403.14009"
] | [
"ja"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ja #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Japanese
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
"# HPLT Bert for Japanese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BE... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ja #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Japanese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tra... | [
72,
200,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ja #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Japanese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained a... |
fill-mask | transformers |
# HPLT Bert for Georgian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["ka"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ka | null | [
"transformers",
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"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"ka",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:24:12+00:00 | [
"2403.14009"
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"ka"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ka #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Georgian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
"# HPLT Bert for Georgian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BE... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ka #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Georgian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tra... | [
72,
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112,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ka #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Georgian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained a... |
visual-question-answering | transformers |
[Comes with two line fixes for multi-GPUs](https://github.com/OpenGVLab/InternVL/issues/96)
# Original Model Card for InternVL-Chat-V1.5
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/D60YzQBIzvoCvLRp2gZ0A.jpeg" alt="Image Description" width="300" height=... | {"license": "mit", "datasets": ["laion/laion2B-en", "laion/laion-coco", "laion/laion2B-multi", "kakaobrain/coyo-700m", "conceptual_captions", "wanng/wukong100m"], "pipeline_tag": "visual-question-answering"} | failspy/InternVL-Chat-V1-5-quantable | null | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"visual-question-answering",
"custom_code",
"dataset:laion/laion2B-en",
"dataset:laion/laion-coco",
"dataset:laion/laion2B-multi",
"dataset:kakaobrain/coyo-700m",
"dataset:conceptual_captions",
"dataset:wanng/wukong100m",
... | null | 2024-04-22T01:24:14+00:00 | [
"2312.14238"
] | [] | TAGS
#transformers #safetensors #internvl_chat #feature-extraction #visual-question-answering #custom_code #dataset-laion/laion2B-en #dataset-laion/laion-coco #dataset-laion/laion2B-multi #dataset-kakaobrain/coyo-700m #dataset-conceptual_captions #dataset-wanng/wukong100m #arxiv-2312.14238 #license-mit #region-us
| Comes with two line fixes for multi-GPUs
Original Model Card for InternVL-Chat-V1.5
==========================================
>
> *Two interns holding hands, symbolizing the integration of InternViT and InternLM.*
>
>
>
[Paper] [GitHub] [Chat Demo] [中文解读]
We introduce InternVL 1.5, an op... | [] | [
"TAGS\n#transformers #safetensors #internvl_chat #feature-extraction #visual-question-answering #custom_code #dataset-laion/laion2B-en #dataset-laion/laion-coco #dataset-laion/laion2B-multi #dataset-kakaobrain/coyo-700m #dataset-conceptual_captions #dataset-wanng/wukong100m #arxiv-2312.14238 #license-mit #region-us... | [
115
] | [
"TAGS\n#transformers #safetensors #internvl_chat #feature-extraction #visual-question-answering #custom_code #dataset-laion/laion2B-en #dataset-laion/laion-coco #dataset-laion/laion2B-multi #dataset-kakaobrain/coyo-700m #dataset-conceptual_captions #dataset-wanng/wukong100m #arxiv-2312.14238 #license-mit #region-us... |
fill-mask | transformers |
# HPLT Bert for Kazakh
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["kk"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_kk | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"kk",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:24:41+00:00 | [
"2403.14009"
] | [
"kk"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #kk #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Kazakh
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Kazakh\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #kk #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Kazakh\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models train... | [
73,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #kk #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Kazakh\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as ... |
fill-mask | transformers |
# HPLT Bert for Kannada
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["kn"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_kn | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"kn",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:25:08+00:00 | [
"2403.14009"
] | [
"kn"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #kn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Kannada
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Kannada\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #kn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Kannada\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
4
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #kn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Kannada\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Korean
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["ko"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ko | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"ko",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:25:31+00:00 | [
"2403.14009"
] | [
"ko"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ko #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Korean
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
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null | peft |
<!-- 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. -->
# outputs
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-I... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "outputs", "results": []}]} | franknnind/outputs | null | [
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#peft #tensorboard #safetensors #generated_from_trainer #base_model-mistralai/Mistral-7B-Instruct-v0.2 #license-apache-2.0 #region-us
|
# outputs
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparame... | [
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text-generation | transformers | # About this model
This model can handle (limited) TSF content. If you Character Card have complex plot, maybe you should try other model (maybe bigger parameter?).
- Another version of [main model](https://huggingface.co/Alsebay/Narumashi-11B), which have lora rank is 128 to reduce underfitting.
Do you know TSF, TS... | {"language": ["en"], "license": "cc-by-nc-4.0", "tags": ["text-generation-inference", "transformers", "unsloth", "llama", "trl", "sft", "Roleplay", "roleplay"], "base_model": "Sao10K/Fimbulvetr-11B-v2"} | Alsebay/Narumashi-11B-v1.1 | null | [
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| # About this model
This model can handle (limited) TSF content. If you Character Card have complex plot, maybe you should try other model (maybe bigger parameter?).
- Another version of main model, which have lora rank is 128 to reduce underfitting.
Do you know TSF, TS, TG? A lot of model don't really know about tha... | [
"# About this model\n\nThis model can handle (limited) TSF content. If you Character Card have complex plot, maybe you should try other model (maybe bigger parameter?).\n\n- Another version of main model, which have lora rank is 128 to reduce underfitting.\n\nDo you know TSF, TS, TG? A lot of model don't really kno... | [
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fill-mask | transformers |
# HPLT Bert for Kyrgyz
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["ky"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ky | null | [
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|
# HPLT Bert for Kyrgyz
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
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fill-mask | transformers |
# HPLT Bert for Latin
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["la"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_la | null | [
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#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #la #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Latin
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
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fill-mask | transformers |
# HPLT Bert for Lithuanian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we us... | {"language": ["lt"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_lt | null | [
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] | null | 2024-04-22T01:26:43+00:00 | [
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#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #lt #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Lithuanian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model i... | [
"# HPLT Bert for Lithuanian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #lt #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
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fill-mask | transformers |
# HPLT Bert for Latvian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["lv"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_lv | null | [
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|
# HPLT Bert for Latvian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Latvian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
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fill-mask | transformers |
# HPLT Bert for Macedonian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we us... | {"language": ["mk"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_mk | null | [
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|
# HPLT Bert for Macedonian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model i... | [
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fill-mask | transformers |
# HPLT Bert for Malayalam
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we use... | {"language": ["ml"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ml | null | [
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|
# HPLT Bert for Malayalam
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is... | [
"# HPLT Bert for Malayalam\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-B... | [
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text-to-image | null | # SDXL Lightning - Onnx Olive DirectML Optimized
## Original Model
https://huggingface.co/ByteDance/SDXL-Lightning
## C# Inference Demo
https://github.com/saddam213/OnnxStack
```csharp
// Create Pipeline
var pipeline = StableDiffusionXLPipeline.CreatePipeline("D:\\Repositories\\SDXL-Lightning-onnx");
// Prompt
var... | {"pipeline_tag": "text-to-image"} | saddam213/SDXL-Lightning-onnx | null | [
"onnx",
"text-to-image",
"region:us"
] | null | 2024-04-22T01:28:16+00:00 | [] | [] | TAGS
#onnx #text-to-image #region-us
| # SDXL Lightning - Onnx Olive DirectML Optimized
## Original Model
URL
## C# Inference Demo
URL
## Inference Result
!Intro Image | [
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fill-mask | transformers |
# HPLT Bert for Mongolian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we use... | {"language": ["mn"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_mn | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"mn",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:28:20+00:00 | [
"2403.14009"
] | [
"mn"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Mongolian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is... | [
"# HPLT Bert for Mongolian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-B... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Mongolian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tr... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Mongolian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained ... |
fill-mask | transformers |
# HPLT Bert for Marathi
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["mr"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_mr | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"mr",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:28:48+00:00 | [
"2403.14009"
] | [
"mr"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mr #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Marathi
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Marathi\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mr #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Marathi\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mr #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Marathi\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Malay
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["ms"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ms | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"ms",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:29:16+00:00 | [
"2403.14009"
] | [
"ms"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ms #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Malay
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
"# HPLT Bert for Malay\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT ... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ms #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Malay\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models traine... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ms #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Malay\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a... |
fill-mask | transformers |
# HPLT Bert for Maltese
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["mt"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_mt | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"mt",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:29:42+00:00 | [
"2403.14009"
] | [
"mt"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mt #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Maltese
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Maltese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mt #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Maltese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #mt #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Maltese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Burmese
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["my"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_my | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"my",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:30:04+00:00 | [
"2403.14009"
] | [
"my"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #my #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Burmese
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Burmese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #my #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Burmese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #my #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Burmese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Norwegian Bokmål
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular,... | {"language": ["nb"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_nb | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"nb",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:30:28+00:00 | [
"2403.14009"
] | [
"nb"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nb #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Norwegian Bokmål
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT m... | [
"# HPLT Bert for Norwegian Bokmål\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingua... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nb #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Norwegian Bokmål\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language mo... | [
73,
203,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nb #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Norwegian Bokmål\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models t... |
fill-mask | transformers |
# HPLT Bert for Nepali
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["ne"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ne | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"ne",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:30:52+00:00 | [
"2403.14009"
] | [
"ne"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ne #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Nepali
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Nepali\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ne #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Nepali\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models train... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ne #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Nepali\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as ... |
fill-mask | transformers |
# HPLT Bert for Dutch
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["nl"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_nl | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"nl",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:31:23+00:00 | [
"2403.14009"
] | [
"nl"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Dutch
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
"# HPLT Bert for Dutch\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT ... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Dutch\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models traine... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Dutch\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a... |
fill-mask | transformers |
# HPLT Bert for Norwegian Nynorsk
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular... | {"language": ["nn"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_nn | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"nn",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:31:46+00:00 | [
"2403.14009"
] | [
"nn"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Norwegian Nynorsk
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT ... | [
"# HPLT Bert for Norwegian Nynorsk\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingu... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Norwegian Nynorsk\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language m... | [
73,
203,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #nn #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Norwegian Nynorsk\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models ... |
fill-mask | transformers |
# HPLT Bert for Panjabi
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["pa"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_pa | null | [
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|
# HPLT Bert for Panjabi
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Panjabi\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
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null | null | This is SmartEdit-7B checkpoint.
---
license: apache-2.0
---
| {} | TencentARC/SmartEdit-7B | null | [
"region:us"
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#region-us
| This is SmartEdit-7B checkpoint.
---
license: apache-2.0
---
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fill-mask | transformers |
# HPLT Bert for Polish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["pl"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_pl | null | [
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|
# HPLT Bert for Polish
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
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null | null | This is SmartEdit-13B checkpoint.
---
license: apache-2.0
---
| {} | TencentARC/SmartEdit-13B | null | [
"region:us"
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#region-us
| This is SmartEdit-13B checkpoint.
---
license: apache-2.0
---
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fill-mask | transformers |
# HPLT Bert for Pushto
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["ps"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ps | null | [
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"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:32:54+00:00 | [
"2403.14009"
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"ps"
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#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ps #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Pushto
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Pushto\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
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null | peft |
<!-- 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. -->
# zephyr-7b-sft-qlora
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-v0.1", "model-index": [{"name": "zephyr-7b-sft-qlora", "results": []}]} | SF-Foundation/zephyr-7b-sft-qlora | null | [
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"base_model:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"4-bit",
"region:us"
] | null | 2024-04-22T01:32:55+00:00 | [] | [] | TAGS
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| zephyr-7b-sft-qlora
===================
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0585
Model description
-----------------
More information needed
Intended uses & limitations
--------------------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 4\n* eval\\_batch\\_size: 8\n* seed: 42\n* distributed\\_type: multi-GPU\n* gradient\\_accumulation\\_steps: 2\n* total\\_train\\_batch\\_size: 8\n* optimizer: Adam wit... | [
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null | peft |
<!-- 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. -->
# mistral7binstruct_summarize
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mi... | {"license": "apache-2.0", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "mistralai/Mistral-7B-Instruct-v0.2", "model-index": [{"name": "mistral7binstruct_summarize", "results": []}]} | santhoshml/mistral7binstruct_summarize | null | [
"peft",
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"dataset:generator",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2024-04-22T01:33:01+00:00 | [] | [] | TAGS
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| mistral7binstruct\_summarize
============================
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.4155
Model description
-----------------
More information needed
Intended uses & limit... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.0002\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: constant\n* lr\\_scheduler\\_warmup\\_step... | [
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fill-mask | transformers |
# HPLT Bert for Portuguese
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we us... | {"language": ["pt"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_pt | null | [
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"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:33:18+00:00 | [
"2403.14009"
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"pt"
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#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #pt #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Portuguese
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model i... | [
"# HPLT Bert for Portuguese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-... | [
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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. -->
# bertin_base_EXIST_detection_spa
This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggi... | {"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bertin-project/bertin-roberta-base-spanish", "model-index": [{"name": "bertin_base_EXIST_detection_spa", "results": []}]} | Gerard-1705/bertin_base_EXIST_detection_spa | null | [
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] | null | 2024-04-22T01:33:29+00:00 | [] | [] | TAGS
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| bertin\_base\_EXIST\_detection\_spa
===================================
This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.5205
* Accuracy: 0.7903
Model description
-----------------
More info... | [
"### 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",
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fill-mask | transformers |
# HPLT Bert for Romanian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["ro"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ro | null | [
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"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:33:43+00:00 | [
"2403.14009"
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"ro"
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#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ro #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Romanian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
"# HPLT Bert for Romanian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BE... | [
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fill-mask | transformers |
# HPLT Bert for Russian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["ru"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ru | null | [
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"ru",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
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"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:34:02+00:00 | [
"2403.14009"
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"ru"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ru #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Russian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Russian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ru #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Russian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #ru #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Russian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
fill-mask | transformers |
# HPLT Bert for Sinhala
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["si"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_si | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"si",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:34:26+00:00 | [
"2403.14009"
] | [
"si"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #si #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Sinhala
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Sinhala\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #si #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Sinhala\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #si #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Sinhala\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **BipedalWalker-v3**
This is a trained model of a **PPO** agent playing **BipedalWalker-v3**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_... | {"library_name": "stable-baselines3", "tags": ["BipedalWalker-v3", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "BipedalWalker-v3", "type": "Bi... | CoderMan-O/ppo-BipedalWalker-v3 | null | [
"stable-baselines3",
"BipedalWalker-v3",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | null | 2024-04-22T01:34:47+00:00 | [] | [] | TAGS
#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing BipedalWalker-v3
This is a trained model of a PPO agent playing BipedalWalker-v3
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
"# PPO Agent playing BipedalWalker-v3\nThis is a trained model of a PPO agent playing BipedalWalker-v3\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: Add your code"
] | [
"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n",
"# PPO Agent playing BipedalWalker-v3\nThis is a trained model of a PPO agent playing BipedalWalker-v3\nusing the stable-baselines3 library.",
"## Usage (with Stable-baselines3)\nTODO: A... | [
33,
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"TAGS\n#stable-baselines3 #BipedalWalker-v3 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us \n# PPO Agent playing BipedalWalker-v3\nThis is a trained model of a PPO agent playing BipedalWalker-v3\nusing the stable-baselines3 library.## Usage (with Stable-baselines3)\nTODO: Add your code... |
fill-mask | transformers |
# HPLT Bert for Slovak
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["sk"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_sk | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"sk",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:34:53+00:00 | [
"2403.14009"
] | [
"sk"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sk #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Slovak
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Slovak\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sk #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Slovak\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models train... | [
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112,
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sk #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Slovak\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as ... |
fill-mask | transformers |
# HPLT Bert for Slovenian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we use... | {"language": ["sl"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_sl | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"sl",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:35:16+00:00 | [
"2403.14009"
] | [
"sl"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Slovenian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is... | [
"# HPLT Bert for Slovenian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-B... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Slovenian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tr... | [
72,
200,
112,
4
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sl #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Slovenian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained ... |
fill-mask | transformers |
# HPLT Bert for Somali
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["so"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_so | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"so",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:35:44+00:00 | [
"2403.14009"
] | [
"so"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #so #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Somali
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Somali\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #so #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Somali\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models train... | [
72,
200,
112,
4
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"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #so #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Somali\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as ... |
fill-mask | transformers |
# HPLT Bert for Albanian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used... | {"language": ["sq"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_sq | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"sq",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:36:07+00:00 | [
"2403.14009"
] | [
"sq"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sq #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Albanian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is ... | [
"# HPLT Bert for Albanian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BE... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sq #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Albanian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models tra... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sq #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Albanian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained a... |
fill-mask | transformers |
# HPLT Bert for Swedish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["sv"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_sv | null | [
"transformers",
"pytorch",
"fill-mask",
"BERT",
"HPLT",
"encoder",
"custom_code",
"sv",
"dataset:HPLT/hplt_monolingual_v1_2",
"arxiv:2403.14009",
"license:apache-2.0",
"autotrain_compatible",
"region:us"
] | null | 2024-04-22T01:36:38+00:00 | [
"2403.14009"
] | [
"sv"
] | TAGS
#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sv #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Swedish
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Swedish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sv #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Swedish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
72,
200,
112,
4
] | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #sv #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n# HPLT Bert for Swedish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as... |
null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned-adapters_ChatGPT_tiny_Seed103 | null | [
"peft",
"arxiv:1910.09700",
"base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"region:us"
] | null | 2024-04-22T01:36:53+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #arxiv-1910.09700 #base_model-TinyLlama/TinyLlama-1.1B-Chat-v1.0 #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
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"## Model Details",
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"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_ChatGPT_tiny_Seed103 | null | [
"peft",
"arxiv:1910.09700",
"base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"region:us"
] | null | 2024-04-22T01:36:59+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #arxiv-1910.09700 #base_model-TinyLlama/TinyLlama-1.1B-Chat-v1.0 #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
- Demo [optional]:
## Uses
### Direct Use
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"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\n\n\n- Developed by: \n- Shared by [optional]: \n- Model type: \n- Language(s) (NLP): \n- License: \n- Finetuned from model [optional]:",
"### Model Sources [optional]\n\n\n\n- Repository: \n- Paper [optional]: \n- Demo [optional]:"... | [
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fill-mask | transformers |
# HPLT Bert for Swahili
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["sw"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_sw | null | [
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# HPLT Bert for Swahili
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
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fill-mask | transformers |
# HPLT Bert for Tamil
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["ta"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ta | null | [
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|
# HPLT Bert for Tamil
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
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fill-mask | transformers |
# HPLT Bert for Telugu
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used t... | {"language": ["te"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_te | null | [
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|
# HPLT Bert for Telugu
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tr... | [
"# HPLT Bert for Telugu\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT... | [
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fill-mask | transformers |
# HPLT Bert for Thai
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used the... | {"language": ["th"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_th | null | [
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|
# HPLT Bert for Thai
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is trai... | [
"# HPLT Bert for Thai\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT m... | [
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fill-mask | transformers |
# HPLT Bert for Tagalog
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["tl"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_tl | null | [
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|
# HPLT Bert for Tagalog
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Tagalog\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
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fill-mask | transformers |
# HPLT Bert for Turkish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["tr"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_tr | null | [
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#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #tr #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us
|
# HPLT Bert for Turkish
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Turkish\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
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text-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | mrinoyb2/bankbert | null | [
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"bert",
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"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
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"1910.09700"
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#transformers #safetensors #bert #text-classification #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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fill-mask | transformers |
# HPLT Bert for Tatar
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["tt"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_tt | null | [
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"license:apache-2.0",
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"region:us"
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"2403.14009"
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|
# HPLT Bert for Tatar
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
"# HPLT Bert for Tatar\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT ... | [
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null | peft |
<!-- 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. -->
# finetune_starcoder2
This model is a fine-tuned version of [bigcode/starcoder2-7b](https://huggingface.co/bigcode/starcoder2-7b) ... | {"license": "bigcode-openrail-m", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "base_model": "bigcode/starcoder2-7b", "model-index": [{"name": "finetune_starcoder2", "results": []}]} | Coolian/finetune_starcoder2 | null | [
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"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:bigcode/starcoder2-7b",
"license:bigcode-openrail-m",
"region:us"
] | null | 2024-04-22T01:39:45+00:00 | [] | [] | TAGS
#peft #safetensors #trl #sft #generated_from_trainer #base_model-bigcode/starcoder2-7b #license-bigcode-openrail-m #region-us
|
# finetune_starcoder2
This model is a fine-tuned version of bigcode/starcoder2-7b on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparamet... | [
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fill-mask | transformers |
# HPLT Bert for Ukrainian
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we use... | {"language": ["uk"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_uk | null | [
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|
# HPLT Bert for Ukrainian
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is... | [
"# HPLT Bert for Ukrainian\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-B... | [
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fill-mask | transformers |
# HPLT Bert for Urdu
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used the... | {"language": ["ur"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_ur | null | [
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|
# HPLT Bert for Urdu
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is trai... | [
"# HPLT Bert for Urdu\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BERT m... | [
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fill-mask | transformers |
# HPLT Bert for Uzbek
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used th... | {"language": ["uz"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_uz | null | [
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|
# HPLT Bert for Uzbek
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is tra... | [
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fill-mask | transformers |
# HPLT Bert for Vietnamese
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we us... | {"language": ["vi"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_vi | null | [
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|
# HPLT Bert for Vietnamese
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model i... | [
"# HPLT Bert for Vietnamese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-... | [
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fill-mask | transformers |
# HPLT Bert for Chinese
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the [HPLT project](https://hplt-project.org/).
It is a so called masked language models. In particular, we used ... | {"language": ["zh"], "license": "apache-2.0", "tags": ["BERT", "HPLT", "encoder"], "datasets": ["HPLT/hplt_monolingual_v1_2"], "inference": false} | HPLT/hplt_bert_base_zh | null | [
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|
# HPLT Bert for Chinese
<img src="URL width=12.5%>
This is one of the encoder-only monolingual language models trained as a first release by the HPLT project.
It is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.
A monolingual LTG-BERT model is t... | [
"# HPLT Bert for Chinese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trained as a first release by the HPLT project.\nIt is a so called masked language models. In particular, we used the modification of the classic BERT model named LTG-BERT.\n\nA monolingual LTG-BER... | [
"TAGS\n#transformers #pytorch #fill-mask #BERT #HPLT #encoder #custom_code #zh #dataset-HPLT/hplt_monolingual_v1_2 #arxiv-2403.14009 #license-apache-2.0 #autotrain_compatible #region-us \n",
"# HPLT Bert for Chinese\n\n<img src=\"URL width=12.5%>\n\nThis is one of the encoder-only monolingual language models trai... | [
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null | null |
<p align="center">
<img style="width: 20%;" src="llasmol.png">
</p>
**Paper**: [LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset]()
**Page**: [https://osu-nlp-group.github.io/LlaSMol](https://osu-nlp-group.github.io/LlaSMol)
**Code**: ... | {"language": ["en"], "license": "cc-by-4.0", "tags": ["instruction tuning", "chemistry", "molecule", "small molecule"]} | osunlp/LlaSMol-Llama2-7B | null | [
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"en"
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#instruction tuning #chemistry #molecule #small molecule #en #license-cc-by-4.0 #region-us
|
<p align="center">
<img style="width: 20%;" src="URL">
</p>
Paper: [LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset]()
Page: URL
Code: URL
Models:
- LlaSMol-Galactica-6.7B: URL
- LlaSMol-Llama2-7B: URL
- LlaSMol-CodeLlama-7B: URL
- ... | [
"## ️ Usage\n\nFor instructions to run the model, please refer to our repository.",
"## Limitations\n\nWhile the model is carefully trained, we do not guarantee its effectiveness. The model may output incorrect or inaccurate information. Please use it at your own risk.\n\nAdditionally, the model is built as a ma... | [
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null | null | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
<img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
... | {"tags": ["pruna-ai"], "metrics": ["memory_disk", "memory_inference", "inference_latency", "inference_throughput", "inference_CO2_emissions", "inference_energy_consumption"], "thumbnail": "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"} | PrunaAI/Llama-3-13B-Instruct-v0.1-GGUF-smashed | null | [
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#gguf #pruna-ai #region-us
|
[](URL target=)
![Twitter](URL
![GitHub](URL
![LinkedIn](URL
![Discord](URL
Simply make AI models cheaper, smaller, faster, and greener!
============================================================
* Give a thumbs up if you like this model!
* Contact us and tell us which model to compress n... | [
"### How to load this model in Python code, using llama-cpp-python\n\nFor full documentation, please see: llama-cpp-python docs.",
"#### First install the package\n\nRun one of the following commands, according to your system:",
"#### Simple llama-cpp-python example code\n\n```\n\n* Option D - Running with Lang... | [
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null | null | ---
license: openrail
---This model is converted to CoreML for us in odysseyapp.io or other Mac-based Stable Diffusion apps. To add this model to Odyssey simply follow these instructions: https://odysseyapp.io/guides/custom-models
More information about the model can be found here: https://civitai.com/models/133005/j... | {} | odyssey-ai/juggernautX | null | [
"region:us"
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#region-us
| ---
license: openrail
---This model is converted to CoreML for us in URL or other Mac-based Stable Diffusion apps. To add this model to Odyssey simply follow these instructions: URL
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# Model Card for Model ID
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<!-- Provide a longer summary of what this model is. -->
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | jsunster/OrpoLlama-3-8B | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- Funded by [optional]:
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- Model type:
- Language(s) (NLP):
- License... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | relu-ntnu/bart-large-xsum_v4_trained_on_50_lr_1e-4 | null | [
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## Model Details
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