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 |
|---|---|---|---|---|---|---|---|
CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-msa | [
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"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
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"no_repeat... | 71 | null | language: kor
thumbnail: "Keywords to Sentences"
tags:
- keytotext
- k2t
- Keywords to Sentences
license: "MIT"
datasets:
- dataset.py
--- | [
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CAMeL-Lab/bert-base-arabic-camelbert-ca | [
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"no_repeat_ngram_size... | 580 | null | ---
license: mit
---
### UZUMAKI on Stable Diffusion
This is the `<NARUTO>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) noteb... | [
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0.... |
CAMeL-Lab/bert-base-arabic-camelbert-da-ner | [
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"ar",
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"transformers",
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] | token-classification | {
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"no_repeat... | 42 | null | ---
language:
- en
thumbnail: null
tags:
- automatic-speech-recognition
- CTC
- Attention
- pytorch
- speechbrain
license: apache-2.0
datasets:
- switchboard
metrics:
- wer
- cer
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" ... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-poetry | [
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"arxiv:2103.06678",
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"no_rep... | 37 | null | ---
language:
- en
thumbnail: null
tags:
- automatic-speech-recognition
- CTC
- Attention
- Transformer
- pytorch
- speechbrain
license: apache-2.0
datasets:
- switchboard
metrics:
- wer
- cer
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" fr... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-pos-egy | [
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"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
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"no_repeat... | 32 | null | ---
datasets:
- relbert/semeval2012_relational_similarity
model-index:
- name: relbert/roberta-large-semeval2012-average-no-mask-prompt-e-nce-conceptnet-validated
results:
- task:
name: Relation Mapping
type: sorting-task
dataset:
name: Relation Mapping
args: relbert/relation_mapping
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CAMeL-Lab/bert-base-arabic-camelbert-da-pos-glf | [
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"no_repeat... | 54 | null | ---
language:
- en
thumbnail: null
tags:
- automatic-speech-recognition
- CTC
- Attention
- pytorch
- speechbrain
license: "apache-2.0"
datasets:
- switchboard
metrics:
- wer
- cer
---
<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment | [
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"bert",
"text-classification",
"ar",
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"transformers",
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"no_rep... | 19,850 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: mit-b2-finetuned-memes
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
s... | [
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CAMeL-Lab/bert-base-arabic-camelbert-da | [
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"fill-mask",
"ar",
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"transformers",
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"no_repeat_ngram_size... | 449 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-20epochs-finetuned-memes
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolde... | [
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CAMeL-Lab/bert-base-arabic-camelbert-mix-ner | [
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"transformers",
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"no_repeat... | 1,860 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
... | [
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CAMeL-Lab/bert-base-arabic-camelbert-mix-poetry | [
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"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
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"no_rep... | 31 | null | ---
tags:
- autotrain
- translation
language:
- tr
- en
datasets:
- Tritkoman/autotrain-data-qjnwjkwnw
co2_eq_emissions:
emissions: 148.66763338560511
---
# Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 1490354394
- CO2 Emissions (in grams): 148.6676
## Validation Metrics
- Loss: 2.112
- S... | [
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CAMeL-Lab/bert-base-arabic-camelbert-mix-pos-glf | [
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"no_repeat... | 132 | null | ---
license: mit
---
### Sorami style on Stable Diffusion
This is the `<sorami-style>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.i... | [
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0.... |
CAMeL-Lab/bert-base-arabic-camelbert-mix | [
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"tf",
"jax",
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"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"Arabic",
"Dialect",
"Egyptian",
"Gulf",
"Levantine",
"Classical Arabic",
"MSA",
"Modern Standard Arabic",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
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"no_repeat_ngram_size... | 20,880 | null | ---
license: bigscience-bloom-rail-1.0
widget :
- text: "ആധുനിക ഭാരതം കണ്ട "
example_title: "ആധുനിക ഭാരതം"
- text : "മലയാളഭാഷ എഴുതുന്നതിനായി"
example_title: "മലയാളഭാഷ എഴുതുന്നതിനായി"
- text : "ഇന്ത്യയിൽ കേരള സംസ്ഥാനത്തിലും"
example_title : "ഇന്ത്യയിൽ കേരള"
---
# GPT2-Malayalam
## Model description
GPT2-Malayala... | [
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CAMeL-Lab/bert-base-arabic-camelbert-msa-did-madar-twitter5 | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
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] | text-classification | {
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"no_rep... | 75 | null | ---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-model-3-x25
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. -->
# pegasus-model-3-x2... | [
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CAMeL-Lab/bert-base-arabic-camelbert-msa-ner | [
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"bert",
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"ar",
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"transformers",
"license:apache-2.0",
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"no_repeat... | 229 | null | ---
tags:
- Pong-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Pong-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pong-PLE-v0
type: Pong-PLE-v0
metrics:
- type: mean_rewa... | [
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0.01... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-poetry | [
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"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
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"no_rep... | 25 | null | ---
tags:
- audio
- spectrograms
datasets:
- teticio/audio-diffusion-instrumental-hiphop-256
---
Denoising Diffusion Probabilistic Model trained on [teticio/audio-diffusion-instrumental-hiphop-256](https://huggingface.co/datasets/teticio/audio-diffusion-instrumental-hiphop-256) to generate mel spectrograms of 256x256 c... | [
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CAMeL-Lab/bert-base-arabic-camelbert-msa-quarter | [
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"transformers",
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
tags:
- autotrain
- translation
language:
- en
- es
datasets:
- Tritkoman/autotrain-data-akakka
co2_eq_emissions:
emissions: 4.471184695619804
---
# Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 1492154441
- CO2 Emissions (in grams): 4.4712
## Validation Metrics
- Loss: 0.899
- SacreBL... | [
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... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"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_rep... | 574 | null | ---
tags:
- autotrain
- translation
language:
- en
- es
datasets:
- Tritkoman/autotrain-data-akakka
co2_eq_emissions:
emissions: 0.26170356193686023
---
# Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 1492154444
- CO2 Emissions (in grams): 0.2617
## Validation Metrics
- Loss: 0.770
- Sacre... | [
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... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-sixteenth | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 26 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.54 +/- 2.70... | [
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CAMeL-Lab/bert-base-arabic-camelbert-msa | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 2,967 | null | ---
license: mit
---
### lxj-o4 on Stable Diffusion
This is the `<csp>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) notebook.... | [
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0.03421194478869438,
-0.011554445140063763,
-0.020647235214710236,
0.030481453984975815,
0... |
CBreit00/DialoGPT_small_Rick | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- paws
metrics:
- f1
- precision
- recall
model-index:
- name: deberta-v3-large-finetuned-paws-paraphrase-detector
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: paws
type... | [
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0.0268... |
CL/safe-math-bot | [] | null | {
"architectures": null,
"model_type": null,
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},
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"num_beams... | 0 | null | ---
license: mit
---
### She-Hulk Law Art on Stable Diffusion
This is the `<shehulk-style>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_infere... | [
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0.036415062844753265,
0... |
CLAck/indo-pure | [
"pytorch",
"marian",
"text2text-generation",
"en",
"id",
"dataset:ALT",
"transformers",
"translation",
"license:apache-2.0",
"autotrain_compatible"
] | translation | {
"architectures": [
"MarianMTModel"
],
"model_type": "marian",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 4 | null | ---
license: mit
---
### led-toy on Stable Diffusion
This is the `<led-toy>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) note... | [
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-0.01149987243115902,
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0.02384011074900627,
0.01250898465514183,
0.030730482190847397,
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0.03631528094410896,
0.012023291550576687,
-0.017500687390565872,
0.023447666317224503,
0.0... |
CLTL/MedRoBERTa.nl | [
"pytorch",
"roberta",
"fill-mask",
"nl",
"transformers",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 2,988 | null | ---
license: mit
---
### durer style on Stable Diffusion
This is the `<drr-style>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb... | [
-0.021827856078743935,
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0.020312320441007614,
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0.04329860582947731,
-0.017300302162766457,
-0.02075864188373089,
0.024904567748308182,
... |
CLTL/icf-levels-stm | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"... | 32 | null | ---
language: el
tags:
- summarization
license: apache-2.0
---
# Abstractive Greek Text Summarization
Application is deployed in [Hugging Face Spaces](https://huggingface.co/spaces/kriton/greek-text-summarization).<br>
We trained mT5-small for the downstream task of text summarization in Greek using this [News Article ... | [
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0... |
Cameron/BERT-Jigsaw | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
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"no_rep... | 35 | null | ---
license: mit
---
### Wish artist stile on Stable Diffusion
This is the `<wish-style>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inferenc... | [
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0... |
dccuchile/albert-xlarge-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 24 | null | ---
license: mit
---
# MagicPrompt - Dall-E 2
This is a model from the MagicPrompt series of models, which are [GPT-2](https://huggingface.co/gpt2) models intended to generate prompt texts for imaging AIs, in this case: [Dall-E 2](https://openai.com/dall-e-2/).
## 🖼️ Here's an example:
<img src="https://files.catb... | [
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dccuchile/distilbert-base-spanish-uncased-finetuned-mldoc | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
... | 27 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: xtreme
type: xtreme
args: PAN-X.de
metrics:
- name:... | [
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dccuchile/distilbert-base-spanish-uncased-finetuned-ner | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
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},
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"min_length": null,
... | 28 | 2022-09-18T07:18:08Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum-ss
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
spl... | [
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0... |
Chaima/TunBerto | [] | null | {
"architectures": null,
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},
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
- summarization
model-index:
- name: bart-base-xsum
results:
- task:
type: summarization
name: Summarization
dataset:
name: xsum
type: xsum
config: default
split: test
metrics:
- type: rouge
value: 38.643
... | [
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Chakita/KNUBert | [
"pytorch",
"tensorboard",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngra... | 20 | null | ---
license: mit
---
### green-blue shanshui on Stable Diffusion
This is the `<green-blue shanshui>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualiz... | [
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0.009981533512473106,
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0.04140244796872139,
... |
Cheatham/xlm-roberta-base-finetuned | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 20 | null | git lfs install
git clone https://huggingface.co/cardiffnlp/twitter-roberta-base-emotion | [
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0.02... |
Chinat/test-classifier | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
config:... | [
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0... |
ChoboAvenger/DialoGPT-small-DocBot | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
model-index:
- name: bert_emo_classifier
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... |
ChoboAvenger/DialoGPT-small-joshua | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
language:
- uk
tags:
- text2text-generation
library_name: generic
license: mit
---
# Attribution
OPT-175B is licensed under the [OPT-175B license](https://github.com/facebookresearch/metaseq/blob/main/projects/OPT/MODEL_LICENSE.md), Copyright (c) Meta Platforms, Inc. All Rights Reserved. | [
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ChrisP/xlm-roberta-base-finetuned-marc-en | [] | null | {
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language: fr
license: mit
datasets:
- oscar
---
## Start with
* Model description
-> The model description provides basic details about the model. This includes the architecture, version, if it was introduced in a paper, if an original implementation is available, the author, and general information about the m... | [
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ChristopherA08/IndoELECTRA | [
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"no_repeat_n... | 4 | null | ---
license: mit
---
### Rail Scene on Stable Diffusion
This is the `<rail-pov>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) ... | [
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0.0... |
Chuah/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: prot_bert_bfd-disoRNA
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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ChukSamuels/DialoGPT-small-Dr.FauciBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... | [
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0.0... |
Chun/DialoGPT-large-dailydialog | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: defau... | [
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Chun/DialoGPT-small-dailydialog | [
"pytorch",
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"text-generation",
"transformers"
] | text-generation | {
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"no_repeat_ngram_size... | 10 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: 2-finetuned-xlm-r-masakhaner-swa-whole-word-phonetic
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 comme... | [
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Chun/w-en2zh-hsk | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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"no_repeat_ngram_size... | 1 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-3000-samples
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, the... | [
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Chun/w-en2zh-mtm | [
"pytorch",
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"transformers",
"autotrain_compatible"
] | text2text-generation | {
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],
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"no_re... | 7 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- wikiann
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: deberta-finetuned-ner-connll-late-stop
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wikiann
type: wikiann
... | [
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Chun/w-en2zh-otm | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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"no_re... | 7 | null | ## Persian XLM-RoBERTA Large For Question Answering Task
XLM-RoBERTA is a multilingual language model pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. It was introduced in the paper [Unsupervised Cross-lingual Representation Learning at Scale](https://arxiv.org/abs/1911.02116v2) by Conneau e... | [
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Chun/w-zh2en-hsk | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MarianMTModel"
],
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"no_repeat_ngram_size... | 3 | null | ---
library_name: stable-baselines3
tags:
- AntBulletEnv-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- metrics:
- type: mean_reward
value: 1291.10 +/- 55.61
name: mean_reward
task:
type: reinforcement-learning
name: ... | [
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Chun/w-zh2en-mto | [
"pytorch",
"mbart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
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"no_re... | 7 | null | ---
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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Chungu424/qazwsx | [] | null | {
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"num_beams... | 0 | 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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Ci/Pai | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
---
### Lula 13 on Stable Diffusion
This is the `<lula-13>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) note... | [
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... |
Cilan/dalle-knockoff | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
license: mit
---
### laala-character on Stable Diffusion
This is the `<laala>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb... | [
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0.03... |
ClaudeCOULOMBE/RickBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
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"no_repeat_ngram_size... | 9 | null | ## ParsBert Fine-Tuned for Question Answering Task
ParsBERT is a monolingual language model based on Google’s BERT architecture. This model is pre-trained on large Persian corpora with various writing styles from numerous subjects (e.g., scientific, novels, news) with more than 3.9M documents, 73M sentences, and 1.3B ... | [
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ClaudeYang/awesome_fb_model | [
"pytorch",
"bart",
"text-classification",
"dataset:multi_nli",
"transformers",
"zero-shot-classification"
] | zero-shot-classification | {
"architectures": [
"BartForSequenceClassification"
],
"model_type": "bart",
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},
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"no_rep... | 26 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model-imdb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: ... | [
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CleveGreen/FieldClassifier_v2_gpt | [
"pytorch",
"gpt2",
"text-classification",
"transformers"
] | text-classification | {
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"GPT2ForSequenceClassification"
],
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"no_rep... | 26 | null | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- cord-layoutlmv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLMv3-Finetuned-CORD_100
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: cord-layoutlmv3
t... | [
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Cloudy/DialoGPT-CJ-large | [
"pytorch",
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 1 | null | ---
tags:
- generated_from_trainer
model-index:
- name: finetuned-bertweetlarge-pheme
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. -->
# finetuned-bertweetlarge-p... | [
-0.0243130661547184,
0.004457530565559864,
-0.0008129542111419141,
0.03196056932210922,
0.034198351204395294,
0.013333022594451904,
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0.05175408720970154,
0.027267171069979668,
-0.004382128827273846,
0.020882992073893547,
0.0... |
ClydeWasTaken/DialoGPT-small-joshua | [
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 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... | [
-0.030383022502064705,
-0.010249387472867966,
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0.009638137184083462,
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0.05541514232754707,
0.008806426078081131,
-0.021552111953496933,
0.007146158721297979,
0... |
CoachCarter/distilbert-base-uncased-finetuned-squad | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: sklearn
tags:
- sklearn
- skops
- tabular-regression
widget:
structuredData:
Hour:
- 0
- 1
- 2
Lag_1:
- 4.215
- 3.741
- 3.38
Lag_2:
- 3.939
- 4.215
- 3.741
Lag_3:
- 4.222
- 3.939
- 4.215
Lag_4:
- 4.568
- 4.222
- 3.939
... | [
-0.017098145559430122,
-0.021482128649950027,
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0.023758577182888985,
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0.024272145703434944,
-0.016964878886938095,
0.00852251797914505,
0.0... |
CodeDanCode/CartmenBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: model-2-bart-reverse-raw
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. ... | [
-0.011713137850165367,
-0.003962202463299036,
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0... |
CodeDanCode/SP-KyleBot | [
"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... | 15 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: stbl_clinical_bert_ft_rs1
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. -->
# st... | [
-0.010863021947443485,
-0.016307180747389793,
-0.0055665550753474236,
0.030880877748131752,
0.01616033911705017,
0.012411076575517654,
-0.03362598642706871,
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0.040162473917007446,
0.0033251650165766478,
-0.03211911767721176,
0.032188985496759415,
... |
CodeMonkey98/distilroberta-base-finetuned-wikitext2 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
---
### margo on Stable Diffusion
This is the `<dog-margo>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) note... | [
-0.03060058131814003,
-0.023567134514451027,
-0.0363546684384346,
0.04325765371322632,
0.01939612627029419,
0.024209043011069298,
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-0.007275770418345928,
-0.038919977843761444,
0.051912203431129456,
0.005084209609776735,
-0.0253674928098917,
0.03073924034833908,
0.0376... |
CodeNinja1126/bert-q-encoder | [
"pytorch"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: stbl_clinical_bert_ft_rs2
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. -->
# st... | [
-0.010249552316963673,
-0.01862245984375477,
-0.004833565559238195,
0.03017209656536579,
0.016895834356546402,
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-0.03321938216686249,
-0.030063655227422714,
-0.028826024383306503,
0.040756337344646454,
0.0031442733015865088,
-0.029664207249879837,
0.03043760173022747,
... |
CodeNinja1126/koelectra-model | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-09-18T21:07:39Z | ---
tags:
- generated_from_trainer
datasets:
- squad_bn
model-index:
- name: banglabert-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 remove this comment. -->
# banglab... | [
-0.019684717059135437,
-0.012543282471597195,
0.0022367280907928944,
0.04385973513126373,
0.03547132760286331,
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0.01928320899605751,
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0.03956695273518562,
0.03985244408249855,
-0.016929535195231438,
0.019866405054926872,
0.04... |
CodeNinja1126/test-model | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 24 | null | ---
license: creativeml-openrail-m
---
Ported from weights hosted on original model repo: https://huggingface.co/CompVis/stable-diffusion-v1-4 | [
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0.04942416027188301,
0.025081394240260124,
0.005278521683067083,
0.029528005048632622,
0.04291... |
CoderBoy432/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluste... | [
-0.03682786226272583,
-0.017038146033883095,
-0.016540275886654854,
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0.08364398777484894,
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0.013144438154995441,
0.00234610796906054,
0.04092745... |
CoderEFE/DialoGPT-marxbot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational",
"has_space"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | 2022-09-18T21:28:18Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- gem
model-index:
- name: OUT
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. -->
# OUT
This model... | [
-0.02271423302590847,
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0.0300704725086689,
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0.02524852566421032,
0.03890... |
CoderEFE/DialoGPT-medium-marx | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"early_stopping": null,
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: LeKazuha/distilbert-base-uncased-finetuned-squad
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 c... | [
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0.021872680634260178,
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0.02830609679222107,
0... |
CoffeeAddict93/gpt1-modest-proposal | [
"pytorch",
"openai-gpt",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"OpenAIGPTLMHeadModel"
],
"model_type": "openai-gpt",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 11 | 2022-09-18T21:58:03Z | ---
license: cc-by-4.0
tags:
- generated_from_trainer
model-index:
- name: electra-base-squad2-ta-qna-electra
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. -->
# e... | [
-0.059480417519807816,
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-0.002702346071600914,
0.03382159769535065,
0.03657202050089836,
0.030396848917007446,
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0.013169534504413605,
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0.02179468795657158,
0.024549225345253944,
-0.022441012784838676,
-0.00020638838759623468,
... |
CoffeeAddict93/gpt2-call-of-the-wild | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: model2-bart-reverse
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. -->
... | [
-0.012962260283529758,
-0.0009905939223244786,
-0.009375786408782005,
0.04083207994699478,
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0.051490407437086105,
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-0.04642653837800026,
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0.... |
CoffeeAddict93/gpt2-medium-modest-proposal | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: mit
---
### CarrasCharacter on Stable Diffusion
This is the `<Carras>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipyn... | [
-0.02409263700246811,
-0.013095447793602943,
-0.02944427914917469,
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0.048049408942461014,
-0.003027787199243903,
-0.016244856640696526,
0.033468179404735565,
... |
CoffeeAddict93/gpt2-modest-proposal | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
license: mit
---
### vietstoneking on Stable Diffusion
This is the `<vietstoneking>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference... | [
-0.020672064274549484,
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0.00878384243696928,
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0.0030653371941298246,
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0.040070388466119766,
0.0018130176467821002,
-0.023934828117489815,
0.04080190137028694,
0... |
CohleM/bert-nepali-tokenizer | [] | null | {
"architectures": null,
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"task_specific_params": {
"conversational": {
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},
"summarization": {
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | Access to model sd-concepts-library/rhizomuse-machine-bionic-sculpture is restricted and you are not in the authorized list. Visit https://huggingface.co/sd-concepts-library/rhizomuse-machine-bionic-sculpture to ask for access. | [
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0.02558233216404915,
0.007963469251990318,
0.0... |
CohleM/mbert-nepali-tokenizer | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-09-19T00:12:56Z | ---
license: mit
---
### rcrumb portraits style on Stable Diffusion
This is the `<rcrumb-portraits>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualiz... | [
-0.022023553028702736,
-0.030204687267541885,
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0.05145980790257454,
0.019078737124800682,
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0.007493430748581886,
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0.04811163246631622,
-0.010499972850084305,
-0.022435955703258514,
0.03263433277606964,
0... |
Connorvr/BrightBot-small | [
"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... | 7 | 2022-09-19T02:05:33Z | ---
tags:
- Pong-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: pong-policy
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pong-PLE-v0
type: Pong-PLE-v0
metrics:
- type: mean_rewa... | [
0.003948866855353117,
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... |
Connorvr/TeachingGen | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 4 | 2022-09-19T02:08:45Z | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- metrics:
- type: mean_reward
value: 14.50 +/- 12.34
name: mean_reward
task:
type: reinforcement-learning
... | [
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0.018881158903241158,
... |
Contrastive-Tension/BERT-Base-CT | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"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_ngram_size... | 16 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
language:
- ko
license:
- mit
widget:
source_sentence: "대한민국의 수도는 서울입니다."
sentences:
- "미국의 수도는 뉴욕이 아닙니다."
- "대한민국의 수도 요금은 저렴한 편입니다."
- "서울은 대한민국의 수도입니다."
---
# smartmind/robert... | [
-0.024129891768097878,
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0.02... |
Contrastive-Tension/BERT-Base-Swe-CT-STSb | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": nul... | 126 | 2022-09-22T05:38:57Z | ```
from transformers import AutoModel, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('truongpdd/vi-en-roberta-base')
model = AutoModel.from_pretrained('truongpdd/vi-en-roberta-base', from_flax=True)
``` | [
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0.04... |
Contrastive-Tension/BERT-Distil-NLI-CT | [
"pytorch",
"tf",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
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"max_length": null
},
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"min_length": null,
"no_repea... | 6 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- metrics:
- type: mean_reward
value: 609.50 +/- 193.33
name: mean_reward
task:
type: reinforcement-learning
... | [
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... |
Contrastive-Tension/BERT-Large-CT-STSb | [
"pytorch",
"tf",
"jax",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 7 | 2022-09-19T03:39:24Z | ---
tags:
- automatic-speech-recognition
- gary109/AI_Light_Dance
- generated_from_trainer
model-index:
- name: ai-light-dance_singing4_ft_wav2vec2-large-xlsr-53-5gram-v4-2-1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should proba... | [
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0.000670553301461041,
... |
Cooker/cicero-similis | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- ko
- en
widget:
source_sentence: "대한민국의 수도는?"
sentences:
- "서울특별시는 한국이 정치,경제,문화 중심 도시이다."
- "부산은 대한민국의 제2의 도시이자 최대의 해양 물류 도시이다."
- "제주도는 대한민국에서 유명한 관광지이다"
- "Seoul is the c... | [
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0.02441... |
Cool/Demo | [] | null | {
"architectures": null,
"model_type": null,
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},
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"num_beams... | 0 | 2022-09-19T04:43:03Z | ---
license: mit
---
### mu-sadr on Stable Diffusion
This is the `<783463b>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) note... | [
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0.012669472023844719,
0.02453400008380413,
0.004070613067597151,
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0.041721541434526443,
0.0008885047864168882,
-0.017356140539050102,
0.034404102712869644,
0... |
CopymySkill/DialoGPT-medium-atakan | [
"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... | 7 | null | ---
language:
- zh
license: apache-2.0
tags:
- chinese poem
- 中文
- 写诗
- 唐诗
- 宋词
widget:
- text: "作诗：百花 模仿：李清照"
---
# 2023 update: Check new version at https://huggingface.co/hululuzhu/chinese-poem-t5-v2
# 一个好玩的中文AI写诗模型
- 两种模式仿写唐宋古诗
- 无特定风格输入格式 `作诗：您的标题`，比如 `作诗：秋思`
- 无特定风格输入格式 `作诗：您的标题 模仿：唐宋诗人名字`，比如... | [
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0.... |
Corvus/DialoGPT-medium-CaptainPrice | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: mit
---
### bozo 22 on Stable Diffusion
This is the `<bozo-22>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) note... | [
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0.0025108526460826397,
0.01268837321549654,
0.004869662690907717,
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0.03365924954414368,
0.010603519156575203,
-0.006642451509833336,
0.03080013394355774,
0... |
CouchCat/ma_mlc_v7_distil | [
"pytorch",
"distilbert",
"text-classification",
"en",
"transformers",
"multi-label",
"license:mit"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
... | 29 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: prot_bert_bfd-disoanno
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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0.01957976631820202,
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CouchCat/ma_ner_v6_distil | [
"pytorch",
"distilbert",
"token-classification",
"en",
"transformers",
"ner",
"license:mit",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
... | 6 | null | ---
tags:
- roberta
- adapter-transformers
datasets:
- glue
language:
- en
---
# Adapter `WillHeld/pfadapter-roberta-base-mnli` for roberta-base
An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [glue](https://huggingface.co/datasets/glue/) dataset and includes a prediction head... | [
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0.02... |
CouchCat/ma_ner_v7_distil | [
"pytorch",
"distilbert",
"token-classification",
"en",
"transformers",
"ner",
"license:mit",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
... | 13 | null | ---
license: mit
---
### SkyFalls on Stable Diffusion
This is the `<SkyFalls>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) no... | [
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0.05797262117266655,
0.009055438451468945,
-0.009145164862275124,
0.03750314936041832,
0... |
CouchCat/ma_sa_v7_distil | [
"pytorch",
"distilbert",
"text-classification",
"en",
"transformers",
"sentiment-analysis",
"license:mit"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
... | 38 | null | ---
language:
- multilingual
license: apache-2.0
inference: false
tags:
- youtube
- video
- pytorch
---
# YouTube video semantic similarity model (WT = with transcripts)
This YouTube video semantic similarity model was developed as part of the RegretsReporter research project at Mozilla Foundation. You can read more... | [
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0.... |
CoveJH/ConBot | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
language:
- multilingual
license: apache-2.0
inference: false
tags:
- youtube
- video
- pytorch
---
# YouTube video semantic similarity model (NT = no transcripts)
This YouTube video semantic similarity model was developed as part of the RegretsReporter research project at Mozilla Foundation. You can read more a... | [
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-0.016583163291215897,
0... |
Coverage/sakurajimamai | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
---
### zk on Stable Diffusion
This is the `zk` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) notebook. You ca... | [
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0.04602549597620964,
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-0.017698993906378746,
0.031939342617988586,
... |
Coyotl/DialoGPT-test-last-arthurmorgan | [
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
license: other
commercial: no
inference: false
---
# OPT 2.7B - Erebus
## Model description
This is the second generation of the original Shinen made by Mr. Seeker. The full dataset consists of 6 different sources, all surrounding the "Adult" theme. The name "Erebus" comes from the greek mythology, als... | [
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0... |
Coyotl/DialoGPT-test2-arthurmorgan | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: mit
---
### tudisco on Stable Diffusion
This is the `<cat-toy>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) note... | [
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Coyotl/DialoGPT-test3-arthurmorgan | [
"conversational"
] | conversational | {
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"num_beams... | 0 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
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... |
Craak/GJ0001 | [] | null | {
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},
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"num_beams... | 0 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.50 +/- 2.78... | [
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0.... |
CracklesCreeper/Piglin-Talks-Harry-Potter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language: en
license: other
commercial: no
---
# OPT 2.7B - Nerys
## Model Description
OPT 2.7B-Nerys is a finetune created using Facebook's OPT model.
## Training data
The training data contains around 2500 ebooks in various genres (the "Pike" dataset), a CYOA dataset called "CYS" and 50 Asian "Light Novels" (the ... | [
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Craftified/Bob | [] | null | {
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},
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- zeroth_korean_asr
model-index:
- name: wav2vec2-large-xls-r-300m-korean-third
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it,... | [
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0... |
Craig/mGqFiPhu | [
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | {
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},
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"num_beams... | 0 | 2022-09-19T07:05:01Z | ---
language:
- ko
tags:
- albert
---
# smartmind/albert-kor-base-tweak
[kykim/albert-kor-base](https://huggingface.co/kykim/albert-kor-base)와 동일한 모델입니다.
`AutoTokenizer`로 토크나이저를 불러올 수 있도록 조정했습니다. | [
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Craig/paraphrase-MiniLM-L6-v2 | [
"pytorch",
"bert",
"arxiv:1908.10084",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | {
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"BertModel"
],
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1,026 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-cased-hate-speech
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. -->
# d... | [
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0.0... |
CrisLeaf/generador-de-historias-de-tolkien | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
tags:
- generated_from_trainer
model-index:
- name: DNADebertaK6_Arabidopsis
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. -->
# DNADebertaK6_Arabidopsis
This... | [
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0.002763427793979... |
Crisblair/Wkwk | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
language: en
license: other
commercial: no
---
# OPT 13B - Nerys
## Model Description
OPT 13B-Nerys is a finetune created using Facebook's OPT model.
## Training data
The training data contains around 2500 ebooks in various genres (the "Pike" dataset), a CYOA dataset called "CYS" and 50 Asian "Light Novels" (the "M... | [
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0.008733331225812435,
... |
Crispy/dialopt-small-kratos | [] | null | {
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},
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"min_length": null,
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"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
model-index:
- name: DNADebertaK6_Worm
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. -->
# DNADebertaK6_Worm
This model is a fi... | [
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0.... |
CrypticT1tan/DialoGPT-medium-harrypotter | [] | null | {
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},
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"num_beams... | 0 | null | ---
language: en
tags:
- emotion-classification
datasets:
- go-emotions
- bdotloh/empathetic-dialogues-contexts
---
# Model Description
Yet another Transformer model fine-tuned for approximating another non-linear mapping between X and Y? That's right!
This is your good ol' emotion classifier - given an input text, t... | [
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0.04127815... |
Cryptikdw/DialoGPT-small-rick | [
"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 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluste... | [
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Culmenus/IceBERT-finetuned-ner | [
"pytorch",
"tensorboard",
"roberta",
"token-classification",
"dataset:mim_gold_ner",
"transformers",
"generated_from_trainer",
"license:gpl-3.0",
"model-index",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 5 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: xlm-roberta-large-finetuned-ours-DS
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comple... | [
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0.012329221703112125,
0.046... |
Culmenus/XLMR-ENIS-finetuned-ner | [
"pytorch",
"tensorboard",
"xlm-roberta",
"token-classification",
"dataset:mim_gold_ner",
"transformers",
"generated_from_trainer",
"license:agpl-3.0",
"model-index",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"XLMRobertaForTokenClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 6 | null | ---
license: mit
---
### Ori Toor on Stable Diffusion
This is the `<ori-toor>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_conceptualizer_inference.ipynb) no... | [
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0.045816581696271896,
0.0019562833476811647,
-0.010566097684204578,
0.03589719533920288,
0... |
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