modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k | embedding list |
|---|---|---|---|---|---|---|---|
Declan/CNN_model_v2 | [
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"no_repeat_ngram_size... | 5 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/CNN_model_v3 | [
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tags:
- generated_from_keras_callback
model-index:
- name: dung1308/RM_system_not_mixed__NLP_model_90_10_CPU_2_epochs
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
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Declan/CNN_model_v4 | [
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language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/CNN_model_v5 | [
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language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/ChicagoTribune_model_v7 | [
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"no_repeat_ngram_size... | 7 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/ChicagoTribune_model_v8 | [
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"no_repeat_ngram_size... | 7 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/FoxNews_model_v2 | [
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"no_repeat_ngram_size... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
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Declan/FoxNews_model_v3 | [
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"no_repeat_ngram_size... | 7 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/HuffPost_model_v5 | [
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language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/HuffPost_model_v6 | [
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"no_repeat_ngram_size... | 9 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/NPR_model_v6 | [
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"no_repeat_ngram_size... | 3 | 2022-12-06T10:03:14Z | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/NewYorkTimes_model_v1 | [] | null | {
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"num_beams... | 0 | 2022-12-06T10:04:19Z | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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Declan/NewYorkTimes_model_v2 | [
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"no_repeat_ngram_size... | 7 | 2022-12-06T10:04:46Z | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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DeepBasak/Slack | [] | null | {
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"num_beams... | 0 | 2022-12-06T10:13:31Z | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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DeepChem/ChemBERTa-10M-MLM | [
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"no_repeat_ngra... | 90 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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DeepChem/ChemBERTa-5M-MLM | [
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"no_repeat_ngra... | 29 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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DeepPavlov/distilrubert-tiny-cased-conversational-v1 | [
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"ru",
"arxiv:2205.02340",
"transformers"
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"n... | 9,141 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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DeepPavlov/rubert-base-cased-sentence | [
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"ru",
"arxiv:1508.05326",
"arxiv:1809.05053",
"arxiv:1908.10084",
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language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
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0.... |
DeepPavlov/rubert-base-cased | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"arxiv:1905.07213",
"transformers",
"has_space"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 148,127 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.... |
DeepPavlov/xlm-roberta-large-en-ru-mnli | [
"pytorch",
"xlm-roberta",
"text-classification",
"en",
"ru",
"dataset:glue",
"dataset:mnli",
"transformers",
"xlm-roberta-large",
"xlm-roberta-large-en-ru",
"xlm-roberta-large-en-ru-mnli",
"has_space"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 227 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeepPavlov/xlm-roberta-large-en-ru | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"en",
"ru",
"transformers"
] | feature-extraction | {
"architectures": [
"XLMRobertaModel"
],
"model_type": "xlm-roberta",
"task_specific_params": {
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},
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"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngr... | 190 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeividasM/wav2vec2-large-xlsr-53-lithuanian | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"lt",
"dataset:common_voice",
"transformers",
"audio",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 7 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeltaHub/adapter_t5-3b_cola | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
-0.03275159001350403,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeltaHub/adapter_t5-3b_mrpc | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeltaHub/adapter_t5-3b_qnli | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
-0.03275159001350403,
-0.014759332872927189,
0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeltaHub/lora_t5-base_mrpc | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DemangeJeremy/4-sentiments-with-flaubert | [
"pytorch",
"flaubert",
"text-classification",
"fr",
"transformers",
"sentiments",
"french",
"flaubert-large"
] | text-classification | {
"architectures": [
"FlaubertForSequenceClassification"
],
"model_type": "flaubert",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 226 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
Denilson/gbert-base-germaner | [] | null | {
"architectures": null,
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"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
-0.03275159001350403,
-0.014759332872927189,
0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
Deniskin/essays_small_2000i | [] | null | {
"architectures": null,
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
-0.03275159001350403,
-0.014759332872927189,
0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
Deniskin/gpt3_medium | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 52 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
Denny29/DialoGPT-medium-asunayuuki | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeskDown/MarianMixFT_en-fil | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
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},
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"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeskDown/MarianMixFT_en-hi | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
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},
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"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeskDown/MarianMixFT_en-id | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
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},
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"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
DeskDown/MarianMixFT_en-ja | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
0.03146016225218773,
0.030212562531232834,
-0.04650815576314926,
-0.03275159001350403,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
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0.... |
DeskDown/MarianMixFT_en-my | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
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"no_repeat_ngram_size... | 7 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
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0.0... |
DeskDown/MarianMixFT_en-th | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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"no_repeat_ngram_size... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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DeskDown/MarianMixFT_en-vi | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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"no_repeat_ngram_size... | 5 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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DeskDown/MarianMix_en-ja-10 | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
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],
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"min_length": null,
"no_repeat_ngram_size... | 1 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
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0.... |
DeskDown/MarianMix_en-zh-10 | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
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],
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
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0.... |
DeskDown/MarianMix_en-zh_to_vi-ms-hi-ja | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
-0.009343069046735764,
0.... |
Despin89/test | [] | null | {
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"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
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0.... |
Dev-DGT/food-dbert-multiling | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
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},
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"min_length": null,
... | 17 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
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0.... |
Devid/DialoGPT-small-Miku | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
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0.05853936821222305,
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0.... |
Devmapall/paraphrase-quora | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
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},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 3 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
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0.... |
Devrim/prism-default | [
"license:mit"
] | null | {
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"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
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0.... |
DevsIA/Devs_IA | [] | null | {
"architectures": null,
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},
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
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0.... |
DevsIA/imagenes | [] | null | {
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"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
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0.... |
DewiBrynJones/wav2vec2-large-xlsr-welsh | [
"cy",
"dataset:common_voice",
"audio",
"automatic-speech-recognition",
"speech",
"xlsr-fine-tuning-week",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": null,
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
-0.019876524806022644,
0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
0.03350357338786125,
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0.... |
DheerajPranav/Dialo-GPT-Rick-bot | [] | null | {
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
tags:
- exbert
license: mit
---
# ColD Fusion model
Finetuned model that aims to be a great base model. It improves over RoBERTa base, trained on 35 datasets.
Full details at [this paper](https://arxiv.org/abs/2212.01378).
## Paper Abstract:
Pretraining has been shown to scale well with compute, d... | [
-0.00042704897350631654,
-0.034673117101192474,
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0.04189128801226616,
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0.05908849835395813,
0.05853936821222305,
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0.... |
Dhito/am | [] | null | {
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"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... | [
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... |
DicoTiar/wisdomfiy | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
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"min_length": null,
"no_repeat_ngram_size... | 3 | null | ---
language:
- zh
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small zh - howl
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
... | [
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0.04110771045088768,
-0.02959078922867775,
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0.... |
DiegoAlysson/opus-mt-en-ro-finetuned-en-to-ro | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"dataset:wmt16",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | [
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0.05938900262117386,
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-0.04342693090438843,
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0.... |
DimaOrekhov/cubert-method-name | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
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"no_re... | 10 | null | ---
language: en
license: mit
tags:
- vision
model_name: microsoft/git-base-vqav2
inference: false
pipeline_tag: visual-question-answering
---
# GIT (GenerativeImage2Text), base-sized, fine-tuned on VQAv2
GIT (short for GenerativeImage2Text) model, base-sized version, fine-tuned on VQAv2. It was introduced in the pap... | [
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0.01734573021531105,
... |
DimaOrekhov/transformer-method-name | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
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"no_re... | 8 | 2022-12-06T11:08:00Z | ---
language:
- hi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hindi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: m... | [
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DivyanshuSheth/T5-Seq2Seq-Final | [] | null | {
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"num_beams... | 0 | null | ---
language: en
license: mit
tags:
- vision
model_name: microsoft/git-base-textvqa
inference: false
pipeline_tag: visual-question-answering
---
# GIT (GenerativeImage2Text), base-sized, fine-tuned on TextVQA
GIT (short for GenerativeImage2Text) model, base-sized version, fine-tuned on TextVQA. It was introduced in t... | [
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0.0... |
Dmitriiserg/Pxd | [] | null | {
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"num_beams... | 0 | null | ---
language: et
license: cc-by-4.0
datasets:
- ERRnews
---
# mBART ERRnews
Pretrained mbart-large-cc25 model finetuned on ERRnews Estonian news story dataset.
## How to use
Here is how to use this model to get a summary of a given text in PyTorch:
```python
from transformers import AutoTokenizer, AutoModelForSeq2S... | [
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Doiman/DialoGPT-medium-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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],
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"no_repeat_ngram_size... | 13 | null | ---
language:
- sv
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: my_tuned_whisper_cn
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should... | [
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DongHyoungLee/distilbert-base-uncased-finetuned-cola | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
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},
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... | 27 | null | ---
language:
- it
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny It 3 - Gianluca Ruberto
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
... | [
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0.0... |
Doogie/Waynehills-KE-T5-doogie | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```pyth... | [
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... |
Waynehillsdev/Waynehills_summary_tensorflow | [
"tf",
"t5",
"text2text-generation",
"transformers",
"generated_from_keras_callback",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
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"no_repeat_n... | 5 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: recipe-nlg-gpt2-ingredient-to-recipe-model
results: []
---
<!-- 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. -->
#... | [
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0.... |
Doquey/DialoGPT-small-Luisbot1 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
tags:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-course
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metr... | [
-0.008285017684102058,
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-0.0003213057352695614,
... |
Doxophobia/DialoGPT-medium-celeste | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: roberta-large-finetuned-mnli-batch_size_4_100000_samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: mnli
... | [
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0.03518... |
DoyyingFace/bert-asian-hate-tweets-asian-unclean-freeze-8 | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
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},
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"min_length": null,
"no_rep... | 30 | null | ---
license: creativeml-openrail-m
---
Science Fiction/Horror monster textual embedding for Stable Diffusion 2.0.
This embedding is trained initially on 49 images from Tod Ryan's Artstation (https://www.artstation.com/todryan), then further tuned with an expanded dataset that includes 119 additional images generated w... | [
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DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-25 | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
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],
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},
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"no_rep... | 30 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
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0... |
DoyyingFace/bert-asian-hate-tweets-concat-clean-with-unclean-valid | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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"max_length": null
},
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"max_length": null,
"min_length": null,
"no_rep... | 25 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: camembert-base-squad-fr
results: []
---
<!-- 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. -->
# camembert-base-squ... | [
-0.06398238241672516,
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0.... |
DoyyingFace/bert-asian-hate-tweets-concat-clean | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
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},
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"max_length": null,
"min_length": null,
"no_rep... | 25 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: bert-base-historic-multilingual-cased-squad-fr
results: []
---
<!-- 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. --... | [
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0.0... |
albert-base-v1 | [
"pytorch",
"tf",
"safetensors",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 38,156 | 2022-12-06T13:03:24Z | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: bert-base-french-europeana-cased-squad-fr
results: []
---
<!-- 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. -->
# ... | [
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... |
albert-xlarge-v1 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 341 | 2022-12-06T13:09:03Z | ---
license: wtfpl
---
Cat picture embedding for 2.0. Trained on high quality Unsplash images, so it tends to prefer photorealism.
Warning: the weights are quite strong. But, when tamed, it works great with stylistic embeddings like the last couple of images!
Trained for 1500 steps, but added the 1000 steps one as we... | [
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... |
bert-base-cased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8,621,271 | 2022-12-06T13:28:42Z | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: Proximal Policy Optimisation (PPO)
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2... | [
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bert-base-chinese | [
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"safetensors",
"bert",
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"zh",
"arxiv:1810.04805",
"transformers",
"autotrain_compatible",
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] | fill-mask | {
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"no_repeat_ngram_size... | 3,377,486 | 2022-12-06T13:30:14Z | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Gorenzelg/bert-finetuned-squad11
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# G... | [
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"exbert",
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"no_repeat_ngram_size... | 175,983 | 2022-12-06T13:32:44Z | ---
language: ru
datasets:
- bond005/sberdevices_golos_10h_crowd
- bond005/sberdevices_golos_100h_farfield
- common_voice
- bond005/sova_rudevices
- bond005/rulibrispeech
metrics:
- wer
- cer
tags:
- audio
- automatic-speech-recognition
- speech
- common_voice
- SberDevices/Golos
- sova_rudevices
- rulibrispeech
licens... | [
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bert-base-german-dbmdz-cased | [
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"de",
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"no_repeat_ngram_size... | 1,814 | 2022-12-06T13:36:21Z | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
widget:
- text: "a photo of dpkbjwn and mnlrvr at a christmas market"
---
### Deepika and Manuel Simulator
classifiers:
"dpkbjwn" for Deepika
"mnlrvr" for Manuel
Example prompt: a photo of dpkbjwn and mnlrvr at a christmas market
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"no_repeat_ngram_size... | 4,749,504 | 2022-12-06T13:37:38Z | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuned-im-rahmen-der-rechtlichen-und-ethischen-bestimmungen-arbeiten
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proof... | [
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bert-base-multilingual-uncased | [
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"bert",
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"af",
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... | fill-mask | {
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"no_repeat_ngram_size... | 328,585 | 2022-12-06T13:42:40Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-Test
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: ... | [
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"no_repeat_ngram_size... | 59,663,489 | 2022-12-06T13:42:46Z | ---
language:
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license: apache-2.0
tags:
- generated_from_trainer
datasets:
- top_v2
model-index:
- name: t5-base-pointer-top_v2
results: []
---
<!-- 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... | [
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bert-large-uncased-whole-word-masking | [
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"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
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"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
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"autotrain_compatible",
"has_space"
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"no_repeat_ngram_size... | 76,685 | 2022-12-06T13:49:42Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: Bert-test-model
results: []
---
<!-- 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. -->
# B... | [
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bert-large-uncased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
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"has_space"
] | fill-mask | {
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"no_repeat_ngram_size... | 1,058,496 | 2022-12-06T13:51:46Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: idrak_wav2vec_timit_subsample
results: []
---
<!-- 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. -->
# idrak... | [
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0.... |
camembert-base | [
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"safetensors",
"camembert",
"fill-mask",
"fr",
"dataset:oscar",
"arxiv:1911.03894",
"transformers",
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"autotrain_compatible",
"has_space"
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"no_repeat_... | 1,440,898 | 2022-12-06T13:59:52Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: distilbert-base-uncased-finetuned-squad
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remov... | [
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distilbert-base-cased-distilled-squad | [
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"rust",
"safetensors",
"openvino",
"distilbert",
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"en",
"dataset:squad",
"arxiv:1910.01108",
"arxiv:1910.09700",
"transformers",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"has_space"
] | question-answering | {
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... | 257,745 | null | Access to model syndikatet/kaia is restricted and you are not in the authorized list. Visit https://huggingface.co/syndikatet/kaia to ask for access. | [
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distilbert-base-multilingual-cased | [
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"af",
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"no_repea... | 8,339,633 | 2022-12-06T14:05:41Z | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cstop_artificial
model-index:
- name: t5-base-pointer-cstop_artificial
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... | [
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Akshay-Vs/AI | [] | null | {
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"num_beams... | 0 | null | Access to model rybread01/email-ds-bert is restricted and you are not in the authorized list. Visit https://huggingface.co/rybread01/email-ds-bert to ask for access. | [
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ASCCCCCCCC/distilbert-base-chinese-amazon_zh_20000 | [
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"no_rep... | 93 | 2022-12-06T19:14:49Z | ---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- paws-x
metrics:
- accuracy
model-index:
- name: paws_x_m_bert_only_ko
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: paws-x
type: paws-x
config: ko
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ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000 | [
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"tensorboard",
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"text-classification",
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"generated_from_trainer",
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... | 39 | null | ---
language:
- mn
license: apache-2.0
tags:
- whisper-event
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
- bayartsogt/ulaanbal-v0
metrics:
- wer
model-index:
- name: whisper-medium-mn-5
results:
- task:
name: Automatic Speech Recognition
... | [
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Aeroxas/Botroxas-small | [] | null | {
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"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
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AetherIT/DialoGPT-small-Hal | [
"conversational"
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license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-teacher-base-student-en-asr-timit
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then... | [
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AethiQs-Max/aethiqs-base_bertje-data_rotterdam-epochs_10 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
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"BertForMaskedLM"
],
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"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: krirk-finetuned-Helsinki-NLP_opus-mt-ar-en
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete... | [
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... |
AethiQs-Max/aethiqs-base_bertje-data_rotterdam-epochs_30-epoch_30 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
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"BertForMaskedLM"
],
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"no_repeat_ngram_size... | 8 | null | ---
language: en
license: apache-2.0
library_name: diffusers
tags: []
datasets: huggan/smithsonian_butterflies_subset
metrics: []
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this com... | [
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0.0... |
Ahmedahmed/Wewe | [] | null | {
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"num_beams... | 0 | null | ---
language:
- vi
---
## Introduction
This model was initialized from [vinai/bartpho-word-base](https://huggingface.co/vinai/bartpho-word-base) and converted to [Allenai's Longformer Encoder-Decoder (LED)](https://github.com/allenai/longformer#longformer) based on [Longformer: The Long-Document Transformer](https://... | [
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0... |
Akash7897/test-clm | [] | null | {
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"num_beams... | 0 | null | Access to model DocPIXL/DOCPICL is restricted and you are not in the authorized list. Visit https://huggingface.co/DocPIXL/DOCPICL to ask for access. | [
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... |
Akashpb13/Hausa_xlsr | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"ha",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index",
"... | automatic-speech-recognition | {
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"Wav2Vec2ForCTC"
],
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 31 | null | ---
tags:
- mteb
model-index:
- name: e5-small
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type:... | [
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0.041... |
Akashpb13/Swahili_xlsr | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sw",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
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"Wav2Vec2ForCTC"
],
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},
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"length_penalty": null,
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"min_length": null,
"no_repeat_ngram_s... | 10 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: my_awesome_model
results: []
---
<!-- 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. -->
# my_awesome_model
... | [
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0.026266... |
Akashpb13/xlsr_hungarian_new | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"hu",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
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"Wav2Vec2ForCTC"
],
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"no_repeat_ngram_s... | 7 | null | ---
license: creativeml-openrail-m
---
### June from [Obituary - A Grave Beginning](https://invidious.weblibre.org/watch?v=0l940bPkV1o) on [WD](https://huggingface.co/hakurei/waifu-diffusion) via Dreambooth
#### model by no3
This your waifu-diffusion v1.3 model fine-tuned june taught to waifu-diffusion v1.3 with Dreamb... | [
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0.... |
AkshatSurolia/ConvNeXt-FaceMask-Finetuned | [
"pytorch",
"safetensors",
"convnext",
"image-classification",
"dataset:Face-Mask18K",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | image-classification | {
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],
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},
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"max_length": null,
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"n... | 56 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
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0.... |
AkshatSurolia/DeiT-FaceMask-Finetuned | [
"pytorch",
"deit",
"image-classification",
"dataset:Face-Mask18K",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | image-classification | {
"architectures": [
"DeiTForImageClassification"
],
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},
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"no_repeat... | 46 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: my_awesome_wnut_model
results: []
---
<!-- 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. -->
# my_awesome_wn... | [
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0.03... |
AkshayDev/BERT_Fine_Tuning | [] | null | {
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"num_beams... | 0 | null | ---
language: en
license: apache-2.0
library_name: diffusers
tags: []
datasets: EmileEsmaili/sheet_music_ede2110
metrics: []
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment.... | [
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0.0... |
AkshaySg/GrammarCorrection | [] | null | {
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},
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"num_beams... | 0 | null | ---
language:
- it
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Italian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name:... | [
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Ale/Alen | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: t5-small-finetuned-wikisql-with-cols
results: []
---
<!-- 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... | [
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0.... |
Aleenbo/Arcane | [] | null | {
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"num_beams... | 0 | 2022-12-07T08:37:14Z | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
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Aleksandar/bert-srb-ner-setimes | [
"pytorch",
"bert",
"token-classification",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 8 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
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