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 |
|---|---|---|---|---|---|---|---|
Ayham/xlnet_bert_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
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"no_re... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
config: default
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Ayham/xlnet_distilgpt2_summarization_cnn_dailymail | [
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language: ms
---
# roberta-base-bahasa-cased
Pretrained RoBERTa base language model for Malay.
## Pretraining Corpus
`roberta-base-bahasa-cased` model was pretrained on ~400 miliion words. Below is list of data we trained on,
1. IIUM confession, https://github.com/huseinzol05/malay-dataset/tree/master/dumping/... | [
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Ayham/xlnetgpt2_xsum7 | [
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"no_re... | 8 | 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: 1704.47 +/- 175.74
name: mean_reward
task:
type: reinforcement-learning
name:... | [
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Ayoola/pytorch_model | [] | null | {
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tags:
- generated_from_trainer
model-index:
- name: GPT-Neo_DnD_Control
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. -->
# GPT-Neo_DnD_Control
This model is ... | [
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Ayoola/wav2vec2-large-xlsr-turkish-demo-colab | [] | null | {
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"num_beams... | 0 | null | Access to model clam004/emerg-intent-consistent-good-gpt2-xl-v2 is restricted and you are not in the authorized list. Visit https://huggingface.co/clam004/emerg-intent-consistent-good-gpt2-xl-v2 to ask for access. | [
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Ayran/DialoGPT-medium-harry-1 | [] | null | {
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license: mit
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-base-sroie
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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Ayran/DialoGPT-small-gandalf | [
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"no_repeat_ngram_size... | 11 | null | ---
license: mit
---
### madhubani art on Stable Diffusion
This is the `<madhubani-art>` 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... | [
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Ayran/DialoGPT-small-harry-potter-1-through-3 | [
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"no_repeat_ngram_size... | 12 | null | ---
tags:
- CartPole-v1
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: PPO
results:
- metrics:
- type: mean_reward
value: 208.80 +/- 135.81
name: mean_reward
task:
type: reinforcement-learning
name: reinforcem... | [
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Azaghast/GPT2-SCP-Descriptions | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
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"no_repeat_ngram_size... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
... | [
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Azuris/DialoGPT-medium-senorita | [
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"text-generation",
"transformers",
"conversational"
] | conversational | {
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"no_repeat_ngram_size... | 14 | null | ---
datasets:
- relbert/semeval2012_relational_similarity
model-index:
- name: relbert/roberta-large-semeval2012-mask-prompt-c-nce-classification-conceptnet-validated
results:
- task:
name: Relation Mapping
type: sorting-task
dataset:
name: Relation Mapping
args: relbert/relation_mapping... | [
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BSC-LT/roberta-large-bne-capitel-ner | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
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],
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"no_... | 5 | null | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- huggingface/autotrain-data-imdb-full
co2_eq_emissions:
emissions: 74.06131825522797
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1373552879
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Badr/model1 | [] | null | {
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"num_beams... | 0 | null | ---
license: bsd
---
a lightweight solution for the Kaggle ELL competition using distilbert
Info about the Kaggle ELL competition: <a href="https://www.kaggle.com/competitions/feedback-prize-english-language-learning/code">https://www.kaggle.com/competitions/feedback-prize-english-language-learning/code</a>
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Bagus/ser-japanese | [] | null | {
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- ./gcc-arm-8.3-2019.03-x86_64-arm-linux-gnueabihf.tar.xz
|Filename | URL for downloading| comment|
|-------|-----| ---|
|./gcc-arm-8.3-2019.03-x86_64-arm-linux-gnueabihf.tar.xz | <https://developer.arm.com/tools-and-software/open-source-software/developer-tools/gnu-toolchain/gnu-a/downloads/8-3-2019-03> | <https://d... | [
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BaptisteDoyen/camembert-base-xnli | [
"pytorch",
"tf",
"camembert",
"text-classification",
"fr",
"dataset:xnli",
"transformers",
"zero-shot-classification",
"xnli",
"nli",
"license:mit",
"has_space"
] | zero-shot-classification | {
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"CamembertForSequenceClassification"
],
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... | 405,474 | 2022-09-07T13:15:31Z | ---
license: cc-by-4.0
---
Install Instructions
1. Download Model into Google Drive > AI > DiscoDiffusion > Models
2. Add path '/content/drive/MyDrive/AI/DiscoDiffusion/Models/AIDM_130k_v01.pt' to Disco Diffusion Step 2 > Custom Model > Custom Path
3. In Custom Model Settings add the following code below
4. Run All
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BatuhanYilmaz/bert-finetuned-nerxD | [] | null | {
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tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- huggingface/autotrain-data-emotions
co2_eq_emissions:
emissions: 0.05402221758817422
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1374752887
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BatuhanYilmaz/code-search-net-tokenizer1 | [] | null | {
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tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- huggingface/autotrain-data-emotions
co2_eq_emissions:
emissions: 0.030012388645982102
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1374752888
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BatuhanYilmaz/distilbert-base-uncased-finetuned-squad-d5716d28 | [
"pytorch",
"distilbert",
"fill-mask",
"en",
"dataset:squad",
"arxiv:1910.01108",
"transformers",
"question-answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | {
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"no_repea... | 18 | null | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- huggingface/autotrain-data-emotions
co2_eq_emissions:
emissions: 5.378843181503548
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1374752889
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BatuhanYilmaz/dummy-model | [
"tf",
"camembert",
"fill-mask",
"transformers",
"generated_from_keras_callback",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"CamembertForMaskedLM"
],
"model_type": "camembert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_... | 6 | null | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- huggingface/autotrain-data-emotions
co2_eq_emissions:
emissions: 18.738323825083565
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 1374752890
- CO2 Emissions (in g... | [
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0.... |
BatuhanYilmaz/mlm-finetuned-imdb | [] | null | {
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"min_length": null,
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- yelp_review_full
metrics:
- accuracy
model-index:
- name: Bert_Classifier
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: yelp_review_full
type: yelp_review_full
config: yelp_revi... | [
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0.015959521755576134,
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0.010687208734452724,
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Baybars/debateGPT | [] | 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... | 0 | null | ---
license: apache-2.0
tags:
- MRC
- Natural Questions List
- xlm-roberta-large
language:
- multilingual
---
# Model description
An XLM-RoBERTa reading comprehension model for List Question Answering using a fine-tuned [xlm-roberta-large](https://huggingface.co/xlm-roberta-large/) model that is further fine-tuned on... | [
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0.0385027714073658,
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0.023304453119635582,
... |
Bia18/Beatriz | [] | null | {
"architectures": null,
"model_type": null,
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},
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"min_length": null,
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Imene/vit-base-patch16-224-in21k-Wr
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. -->
... | [
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0.0... |
Biasface/DDDC | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | ---
language: en
license: mit
tags:
- vision
- video-classification
model-index:
- name: nielsr/xclip-base-patch16-hmdb-2-shot
results:
- task:
type: video-classification
dataset:
name: HMDB-51
type: hmdb-51
metrics:
- type: top-1 accuracy
value: 53.0
---
# X-CLIP (base-sized mo... | [
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BigDaddyNe1L/Hhaa | [] | null | {
"architectures": null,
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},
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"min_length": null,
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"num_beams... | 0 | null | ---
language: en
license: mit
tags:
- vision
- video-classification
model-index:
- name: nielsr/xclip-base-patch16-hmdb-8-shot
results:
- task:
type: video-classification
dataset:
name: HMDB-51
type: hmdb-51
metrics:
- type: top-1 accuracy
value: 62.8
---
# X-CLIP (base-sized mo... | [
-0.03974417224526405,
-0.006050767842680216,
-0.0006857175612822175,
0.04161790385842323,
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0.0690430998802185,
0.011473598890006542,
-0.02233627811074257,
-0.0022379420697689056,
... |
BigSalmon/FormalBerta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 10 | null | ---
language: en
license: mit
tags:
- vision
- video-classification
model-index:
- name: nielsr/xclip-base-patch16-ucf-8-shot
results:
- task:
type: video-classification
dataset:
name: UCF101
type: ucf101
metrics:
- type: top-1 accuracy
value: 88.3
---
# X-CLIP (base-sized model... | [
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-0.000645936990622431,
-0.004793618805706501,
0.04173383116722107,
0.03268139436841011,
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0.07346518337726593,
0.009902926161885262,
-0.013870677910745144,
-0.007134723477065563,
... |
BigSalmon/FormalBerta2 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"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_ngra... | 16 | null | ---
language: en # <-- my language
widget:
- text: "Moody’s decision to upgrade the credit rating of Air Liquide is all the more remarkable as it is taking place in a more difficult macroeconomic and geopolitical environment. It underlines the Group’s capacity to maintain a high level of cash flow despite the ... | [
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0... |
BigSalmon/GPTHeHe | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"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... | 8 | null | ---
license: mit
---
### Cheburashka on Stable Diffusion
This is the `<cheburashka>` 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.ipy... | [
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0.011751726269721985,
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0.001539063174277544,
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0.051754288375377655,
0.013754130341112614,
-0.004292618483304977,
0.041775815188884735,
... |
BigSalmon/GPTIntro | [] | 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... | 0 | null | ---
language: en
license: mit
tags:
- vision
- video-classification
model-index:
- name: nielsr/xclip-base-patch16-zero-shot
results:
- task:
type: video-classification
dataset:
name: HMDB-51
type: hmdb-51
metrics:
- type: top-1 accuracy
value: 44.6
- task:
type: video-cl... | [
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0.027037363499403,
0.03806190565228462,
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0.07534508407115936,
0.007622964680194855,
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-0.004499578382819891,
0.0... |
BigSalmon/GoodMaskResults | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: m-ctc-t-german
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. -->
# m-ctc-t-german
This... | [
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0.... |
BigSalmon/InformalToFormalLincoln14 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
license: mit
---
### karl's lzx 1 on Stable Diffusion
This is the `<lzx>` 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) not... | [
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0.04417543485760689,
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0.028551602736115456,
0.0305... |
BigSalmon/InformalToFormalLincoln23 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"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... | 5 | null | ---
tags:
- generated_from_keras_callback
model-index:
- name: VanessaSchenkel/padrao-unicamp-vanessa-finetuned-handscrafted
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.... | [
-0.03112921491265297,
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0.011769384145736694,
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0.019940000027418137,
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0.0649050921201706,
0.022106612101197243,
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0.04546445235610008,
0.041... |
BigSalmon/InformalToFormalLincoln24 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"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... | 5 | 2022-09-07T19:20:53Z | ---
license: mit
---
### canary cap on Stable Diffusion
This is the `<canary-cap>` 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... | [
-0.03364146500825882,
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0.023403692990541458,
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0.034059274941682816,
0.009020701050758362,
-0.013501900248229504,
0.037448517978191376,
... |
BigSalmon/InformalToFormalLincolnDistilledGPT2 | [
"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: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... | [
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0.01913844421505928,
0... |
BigSalmon/MrLincoln3 | [
"pytorch",
"tensorboard",
"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... | 17 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: albert-base-v2-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 co... | [
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... |
BigSalmon/Points2 | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | 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 | ---
datasets:
- relbert/semeval2012_relational_similarity
model-index:
- name: relbert/roberta-large-semeval2012-mask-prompt-e-nce-classification-conceptnet-validated
results:
- task:
name: Relation Mapping
type: sorting-task
dataset:
name: Relation Mapping
args: relbert/relation_mapping... | [
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0.... |
Blabla/Pipipopo | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"num_beams... | 0 | null | ---
license: mit
---
### Walter Wick photography on Stable Diffusion
This is the `<walter-wick>` 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_i... | [
-0.01936149224638939,
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0.01617414876818657,
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0.008505459874868393,
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0.052198510617017746,
-0.0028412104584276676,
-0.013232206925749779,
0.018744543194770813,
0.0... |
Blerrrry/Kkk | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- wildreceipt
model-index:
- name: layoutlmv3-finetuned-wildreceipt
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 r... | [
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0.0296... |
BobBraico/bert-finetuned-ner | [] | null | {
"architectures": null,
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"num_beams... | 0 | 2022-09-08T02:00:45Z | ---
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... | [
-0.030837440863251686,
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0... |
BobBraico/distilbert-base-uncased-finetuned-imdb-accelerate | [] | null | {
"architectures": null,
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"num_beams... | 0 | 2022-09-08T02:05:04Z | ---
license: mit
---
### Smiling Friend style on Stable Diffusion
This is the `<smilingfriends-cartoon>` 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_conceptu... | [
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0.04651709645986557,
0.0... |
Boondong/Wandee | [] | null | {
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},
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"num_beams... | 0 | 2022-09-08T03:05:17Z | ---
license: apache-2.0
---
## Table of Contents
1. [Model Details](#model-details)
2. [Uses](#uses)
3. [Training Data](#training-data)
4. [Risks and Limitations](#risks-and-limitations)
5. [Evaluation](#evaluation)
6. [Recommendations](#recommendations)
7. [Glossary and Calculations](#glossary-and-calculations)
8. [Mo... | [
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0... |
BrunoNogueira/DialoGPT-kungfupanda | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
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"GPT2LMHeadModel"
],
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"no_repeat_ngram_size... | 10 | null | ---
license: mit
---
### Monster Girl on Stable Diffusion
This is the `<monster-girl>` 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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0.04355191811919212,
0.0... |
Brunomezenga/NN | [] | null | {
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},
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"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/sanmemero/1662612412375/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width... | [
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... |
Bryanwong/wangchanberta-ner | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/mariojpenton-mjorgec1994/1662625679744/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-ri... | [
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0... |
CAMeL-Lab/bert-base-arabic-camelbert-mix-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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},
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"min_length": null,
"no_rep... | 855 | 2022-09-08T09:21:14Z | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: greek_legal_bert_v2-finetuned-ner
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 rem... | [
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0... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-did-nadi | [
"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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},
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"max_length": null,
"min_length": null,
"no_rep... | 71 | null | ---
license: mit
---
### Party girl on Stable Diffusion
This is the `<party-girl>` 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... | [
-0.037368230521678925,
-0.03433201089501381,
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0.007036751136183739,
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0.041006382554769516,
0.007375289220362902,
-0.002071572234854102,
0.03564778342843056,
0... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_rep... | 25 | null | ---
license: mit
---
### Dicoo on Stable Diffusion
This is the `<Dicoo>` 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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0.031054651364684105,
0... |
CLEE/CLEE | [] | null | {
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},
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"num_beams... | 0 | null | ---
language: en
license: mit
tags:
- vision
- video-classification
model-index:
- name: nielsr/xclip-large-patch14-kinetics-600
results:
- task:
type: video-classification
dataset:
name: Kinetics 400
type: kinetics-400
metrics:
- type: top-1 accuracy
value: 88.3
- type: top-... | [
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CM-CA/Cartman | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta_large-filtered_simple-chunk-conll2003_0907_v1
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
t... | [
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0.0... |
Capreolus/birch-bert-large-msmarco_mb | [
"pytorch",
"tf",
"jax",
"bert",
"next-sentence-prediction",
"transformers"
] | null | {
"architectures": [
"BertForNextSentencePrediction"
],
"model_type": "bert",
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},
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"no_rep... | 1 | 2022-09-08T16:05:57Z | Attempt at making a NWScript model trained on scripts from Neverwinter Nights.
## Intended Use and Limitations
The intention is for the model to generate a script based on users written comment strings. | [
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Captain-1337/CrudeBERT | [
"pytorch",
"bert",
"text-classification",
"arxiv:1908.10063",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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},
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"no_rep... | 28 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-finetuned-basil
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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0.03960... |
Captain272/lstm | [] | null | {
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},
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"num_beams... | 0 | 2022-09-08T16:14:06Z | ---
license: mit
---
### apulian-rooster-v0.1 on Stable Diffusion
--
# Inspired by the design of the Galletto (rooster) typical of ceramics and pottery made in Grottaglie, Puglia (Italy).
This is the `<apulian-rooster-v0.1>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the ... | [
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... |
Carlork314/Carlos | [] | null | {
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"num_beams... | 0 | 2022-09-08T16:15:52Z | ---
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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... |
Carlork314/Xd | [] | null | {
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},
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"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/piemadd/1662653961299/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: ... | [
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0.011945542879402637,
-0.0034868281800299883,
-0.01949014700949192,
0.... |
Cathy/reranking_model | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"min_length": null,
"... | 27 | 2022-09-08T16:57:36Z | ---
language: nl
license: mit
---
# MedRoBERTa.nl finetuned for negation
## Description
This model is a finetuned RoBERTa-based model pre-trained from scratch on Dutch hospital notes sourced from Electronic Health Records. All code used for the creation of MedRoBERTa.nl can be found at https://github.com/cltl-student... | [
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Cedille/fr-boris | [
"pytorch",
"gptj",
"text-generation",
"fr",
"dataset:c4",
"arxiv:2202.03371",
"transformers",
"causal-lm",
"license:mit",
"has_space"
] | text-generation | {
"architectures": [
"GPTJForCausalLM"
],
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"no_repeat_ngram_size... | 401 | 2022-09-08T16:58:04Z | ---
license: mit
---
### fractal on Stable Diffusion
This is the `<fractal>` concept taught to Stable Diffusion via Textual Inversion. You can load this concept into the [Stable Conceptualizer](#) notebook. You can also train your own concepts and load them into the concept libraries using [this notebook](#).
The imag... | [
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dccuchile/albert-base-spanish-finetuned-pos | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
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"no_re... | 5 | null | ---
license: mit
---
### Nebula on Stable Diffusion
This is the `<nebula>` 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) notebo... | [
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... |
dccuchile/albert-large-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
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},
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"no... | 25 | 2022-09-08T18:13:31Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... | [
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-0.011748546734452248,
0.021032027900218964,
0.033... |
dccuchile/albert-xlarge-spanish-finetuned-ner | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 5 | null | ---
datasets:
- relbert/semeval2012_relational_similarity
model-index:
- name: relbert/roberta-large-semeval2012-average-prompt-a-nce-classification-conceptnet-validated
results:
- task:
name: Relation Mapping
type: sorting-task
dataset:
name: Relation Mapping
args: relbert/relation_mapp... | [
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... |
dccuchile/albert-xlarge-spanish-finetuned-qa-mlqa | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"AlbertForQuestionAnswering"
],
"model_type": "albert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repe... | 7 | 2022-09-08T19:53:10Z | ---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# sentence-transformers/paraphrase-mpnet-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional den... | [
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CennetOguz/distilbert-base-uncased-finetuned-recipe-1 | [
"pytorch",
"tensorboard",
"distilbert",
"fill-mask",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
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"no_repea... | 7 | 2022-09-09T02:43:59Z | ---
language: ja
license: cc-by-sa-4.0
---
# electra-base-cyberbullying
This is an [ELECTRA](https://github.com/google-research/electra) Small model for the Japanese language finetuned for automatic cyberbullying detection.
The model was based on [Izumi Lab ELECTRA small Japanese discriminator](https://huggingfa... | [
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CennetOguz/distilbert-base-uncased-finetuned-recipe-accelerate | [
"pytorch",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
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"DistilBertForMaskedLM"
],
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"no_repea... | 7 | 2022-09-09T02:52:52Z | ---
language: en
thumbnail: http://www.huggingtweets.com/amouranth/1668957567411/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width... | [
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Cheatham/xlm-roberta-large-finetuned-d1 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
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... | 20 | null | ---
license: apache-2.0
tags:
- object-detection
- vision
datasets:
- coco
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/savanna.jpg
example_title: Savanna
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/football-match.jpg
example_title: Football Match
- s... | [
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... |
Cheatham/xlm-roberta-large-finetuned-d12 | [
"pytorch",
"xlm-roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
... | 20 | null | ---
tags:
- generated_from_trainer
datasets:
- i2b22014
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electramed-small-deid2014-ner-v3
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: i2b22014
type: i2b22014
config: i2b22014... | [
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0.045... |
Chester/traffic-rec | [] | null | {
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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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0.03... |
Chinat/test-classifier | [] | null | {
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"num_beams... | 0 | 2022-09-09T09:06:46Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: NLP2122_FranciosoDonato
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. -->
# NLP2122_Fra... | [
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0.0... |
Ching/negation_detector | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 9 | null | ---
language:
- de
license: mit
datasets:
- germaner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: gbert-large-germaner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: germaner
type: germaner
args: default
metrics:
... | [
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0.0... |
ChoboAvenger/DialoGPT-small-DocBot | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"num_beams... | 0 | 2022-09-09T09:19:36Z | ---
tags:
- generated_from_trainer
model-index:
- name: DNADebertaK6_Zebrafish
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_Zebrafish
This mod... | [
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0.... |
ChoboAvenger/DialoGPT-small-joshua | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- conversational
- chatbot
---
# Rogers DailoGPT Model
| [
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0.0... |
ChrisVCB/DialoGPT-medium-cmjs | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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"max_length": 1000
},
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"early_stopping": null,
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-all
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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0.0472249761223793,
0.025916853919625282,
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0.020179254934191704,
0.03... |
Ci/Pai | [] | null | {
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language: en
tags:
- detr
license: unknown
datasets:
- PubTables-1M
---
# The models are taken from https://github.com/microsoft/table-transformer/
# Original model now on MSFT org: https://huggingface.co/microsoft/table-transformer-detection
I have built a HuggingFace Space: https://huggingface.co/spaces/SalML/Tab... | [
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0.0451... |
Cilan/dalle-knockoff | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
license: mit
---
### lucky-luck on Stable Diffusion
This is the `<lucky-luke>` 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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0.04353485256433487,
0.013368774205446243,
-0.014970485121011734,
0.03288769721984863,
0.... |
Clarianliz30/Caitlyn | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null |
---
language: en
---
<p align="center">
<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: recognition
https://github.com/mindee/doctr
### Example usag... | [
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0.04519060254096985,
0.007566129323095083,
-0.011655234731733799,
-0.017943447455763817,
... |
CleveGreen/FieldClassifier | [
"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... | 34 | 2022-09-09T12:28:47Z |
---
language: en
---
<p align="center">
<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: recognition
https://github.com/mindee/doctr
### Example usag... | [
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0.04057750105857849,
0.032507482916116714,
0.005321667995303869,
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0.04519060254096985,
0.007566129323095083,
-0.011655234731733799,
-0.017943447455763817,
... |
CleveGreen/FieldClassifier_v2 | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 46 | null | ---
tags:
- autotrain
- vision
- image-classification
datasets:
- dhruv0808/autotrain-data-ad_detection_ver_1
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_ti... | [
-0.011283257976174355,
-0.016060594469308853,
0.014862186275422573,
0.043689269572496414,
0.04981832951307297,
-0.006154055707156658,
-0.02111826092004776,
-0.00062839116435498,
-0.03458784148097038,
0.06518729776144028,
-0.0036076223477721214,
0.0035063340328633785,
0.0014063954586163163,
... |
CohleM/mbert-nepali-tokenizer | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
"summarization": {
"early_stopping": null,
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-09-09T14:15:36Z | ---
language:
- ko
tags:
- pytorch
- causal-lm
license: apache-2.0
---
# Polyglot-Ko-3.8B
## Model Description
Polyglot-Ko is a series of large-scale Korean autoregressive language models made by the EleutherAI polyglot team.
| Hyperparameter | Value ... | [
-0.04603532329201698,
-0.02535468153655529,
0.007223923224955797,
0.0338064506649971,
0.04157556593418121,
0.02117057517170906,
0.011526504531502724,
0.0026577780954539776,
-0.03473576530814171,
0.052454352378845215,
0.01462169922888279,
-0.015613106079399586,
0.010541168972849846,
0.01854... |
Coldestadam/Breakout_Mentors_SpongeBob_Model | [
"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... | 10 | 2022-09-09T14:15:55Z | ---
tags:
- autotrain
- vision
- image-classification
datasets:
- DominikB/autotrain-data-person-classifier
widget:
- src: https://100-pics.net/images/answers/de/schauspieler/schauspieler_22135_191026.jpeg
example_title: Jack Black 1
- src: https://assets.rebelmouse.io/eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpbWFnZSI... | [
-0.00805392675101757,
-0.018292829394340515,
-0.0029353112913668156,
0.03334972262382507,
0.054340098053216934,
0.01406807079911232,
-0.03689683601260185,
-0.0011359959607943892,
-0.027897940948605537,
0.05287057161331177,
0.012710588984191418,
-0.005717875435948372,
0.0016027558594942093,
... |
ComCom/gpt2 | [
"pytorch",
"gpt2",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"GPT2Model"
],
"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": nul... | 1 | null | ---
license: mit
---
### Russian on Stable Diffusion
This is the `<Russian>` 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... | [
-0.01924331672489643,
-0.03306536749005318,
-0.027579808607697487,
0.047572385519742966,
0.020063193514943123,
0.0167193915694952,
0.002257484942674637,
0.0006265011033974588,
-0.05493098124861717,
0.051955461502075195,
-0.0016267496393993497,
-0.014848303981125355,
0.03179283067584038,
0.... |
ComCom-Dev/gpt2-bible-test | [] | 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... | 0 | null | ---
tags:
- decisionTransformer
- deep reinforcement
datasets:
- edbeeching/decision_transformer_gym_replay
license:
- mit
---
### Running training
- Num examples = 1000
- Num Epochs = 120
- Instantaneous batch size per device = 64
- Total train batch size = 64
- Gradient Accumulation steps = 1
- Total optimization s... | [
-0.048427630215883255,
0.023291293531656265,
0.0018307171994820237,
-0.004902438726276159,
0.04614831879734993,
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0.008244669996201992,
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0.06832433491945267,
0.010809695348143578,
-0.031011085957288742,
-0.0017669094959273934,
... |
Connor-tech/bert_cn_finetuning | [
"pytorch",
"jax",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 27 | 2022-09-09T14:53:35Z | ---
thumbnail: "https://repository-images.githubusercontent.com/523487884/fdb03a69-8353-4387-b5fc-0d85f888a63f"
datasets:
- ChristophSchuhmann/improved_aesthetics_6plus
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- image-to-image
---
# Stable Diffusion Image Variations Model Ca... | [
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0.04003234952688217,
0.03738529235124588,
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0.05196036398410797,
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0.01179054006934166,
0.0... |
Connorvr/TeachingGen | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"generated_from_trainer",
"license:mit"
] | 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... | 4 | 2022-09-09T15:30:08Z | ---
license: mit
---
### Tony DiTerlizzi's Planescape Art on Stable Diffusion
This is the `<tony-diterlizzi-planescape>` 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... | [
-0.019419029355049133,
-0.02475210651755333,
-0.034356944262981415,
0.05203477293252945,
0.015631143003702164,
0.017652330920100212,
0.010099798440933228,
-0.004722294397652149,
-0.022425061091780663,
0.04698946699500084,
0.00698514562100172,
-0.017418770119547844,
0.02256719209253788,
0.0... |
ConstellationBoi/Oop | [] | null | {
"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 | ---
license: mit
---
### Moeb Style on Stable Diffusion
This is the `<moe-bius>` 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) ... | [
-0.025373170152306557,
-0.02472924254834652,
-0.03342609480023384,
0.032559290528297424,
0.008421815931797028,
0.021448148414492607,
0.004335240460932255,
0.008183258585631847,
-0.03348234295845032,
0.04591149091720581,
-0.009571600705385208,
-0.004847012460231781,
0.031186899170279503,
0.... |
Corvus/DialoGPT-medium-CaptainPrice-Extended | [
"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 | 2022-09-09T17:32:38Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-amazon-shoe-reviews
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and comp... | [
-0.012118138372898102,
0.021004458889365196,
-0.01780230738222599,
0.028445107862353325,
0.04359191283583641,
0.011054967530071735,
-0.008725796826183796,
-0.010323514230549335,
-0.052728474140167236,
0.0652824342250824,
0.033644769340753555,
-0.032680265605449677,
0.012040064670145512,
0.... |
Coyotl/DialoGPT-test3-arthurmorgan | [
"conversational"
] | conversational | {
"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... | 0 | 2022-09-09T18:49:07Z | ---
license: mit
---
### scrap-style on Stable Diffusion
This is the `<style-scrap>` 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.ipy... | [
-0.022051207721233368,
-0.02273627743124962,
-0.036198489367961884,
0.03950574994087219,
0.012878700159490108,
0.023122373968362808,
-0.000608337577432394,
0.009623431600630283,
-0.04190344363451004,
0.053148604929447174,
-0.006531220395117998,
-0.010648067109286785,
0.024334201589226723,
... |
Craftified/Bob | [] | 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... | 0 | 2022-09-09T19:00:20Z | ---
license: mit
---
### tela lenca on Stable Diffusion
This is the `<tela-lenca>` 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... | [
-0.016704842448234558,
-0.02334517054259777,
-0.018801718950271606,
0.034223996102809906,
0.013068296015262604,
0.012771242298185825,
-0.009086760692298412,
-0.0009581626509316266,
-0.04091901704668999,
0.03902645781636238,
0.0012190992711111903,
-0.01909523829817772,
0.033971741795539856,
... |
Craig/mGqFiPhu | [
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | {
"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... | 0 | 2022-09-09T19:18:43Z | ---
language:
- en
tags:
- stable-diffusion
- text-to-image
license: bigscience-bloom-rail-1.0
inference: false
---
https://huggingface.co/hakurei/waifu-diffusion
This is just the EMA version of the model. Anything other than the model required for inference has been removed. This decreases the file size by ~3 gigaby... | [
-0.02742806449532509,
-0.03180243819952011,
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0.022371821105480194,
0.01980362832546234,
0.004309815354645252,
0.016045916825532913,
0.004508380778133869,
-0.034239836037158966,
0.04909501224756241,
0.043918587267398834,
0.017486514523625374,
0.04663977026939392,
0.0182... |
Craig/paraphrase-MiniLM-L6-v2 | [
"pytorch",
"bert",
"arxiv:1908.10084",
"sentence-transformers",
"feature-extraction",
"sentence-similarity",
"transformers",
"license:apache-2.0"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"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": nul... | 1,026 | 2022-09-09T19:28:37Z | ---
tags:
- autotrain
- vision
- image-classification
datasets:
- monkseal555/autotrain-data-hurricane3
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: T... | [
-0.004923665430396795,
-0.018064724281430244,
-0.0009704881813377142,
0.048500776290893555,
0.0567949078977108,
-0.007434807252138853,
-0.007354565430432558,
-0.0006146876839920878,
-0.0247835423797369,
0.061231423169374466,
-0.004578910768032074,
0.007492890581488609,
0.00243060989305377,
... |
CrayonShinchan/bart_fine_tune_test | [] | 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... | 0 | 2022-09-09T19:43:14Z | ---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: orhanxakarsu/turkishPoe-generation-1
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. -->
# orha... | [
-0.02679990418255329,
-0.022443605586886406,
0.009137461893260479,
0.03553256019949913,
0.031491849571466446,
-0.0008885949500836432,
0.007184184622019529,
-0.006950185634195805,
-0.028334010392427444,
0.07072766125202179,
0.008895273320376873,
-0.02792927622795105,
0.013359811156988144,
0... |
Crispy/dialopt-small-kratos | [] | 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... | 0 | null | ---
license: mit
---
### shu doll on Stable Diffusion
This is the `<shu-doll>` 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... | [
-0.02500753663480282,
-0.023924997076392174,
-0.0203938540071249,
0.03370378538966179,
0.016243942081928253,
0.020449204370379448,
-0.002647585468366742,
-0.005683536641299725,
-0.03751514106988907,
0.04508299008011818,
0.002226640237495303,
-0.010229140520095825,
0.045758720487356186,
0.0... |
Crystal/distilbert-base-uncased-finetuned-squad | [] | 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... | 0 | null | ```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/Infill3")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/Infill3")
```
```
Demo:
https://huggingface.co/spaces/BigSalmon/FormalInformalConciseWordy
```
```
prompt = """few sights are as [blan... | [
-0.0168470349162817,
-0.025068311020731926,
-0.011436709202826023,
0.06354399770498276,
0.040163785219192505,
0.02900754101574421,
0.00032619235571473837,
-0.01601441018283367,
-0.05361092463135719,
0.062103066593408585,
0.037557657808065414,
0.004621665924787521,
-0.014711233787238598,
0.... |
Culmenus/opus-mt-de-is-finetuned-de-to-is_ekkicc | [] | 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... | 0 | null | ---
license: mit
---
### smw map on Stable Diffusion
This is the `<smw-map>` 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... | [
-0.029608797281980515,
-0.024304861202836037,
-0.035880908370018005,
0.049109186977148056,
0.009763822890818119,
0.023938048630952835,
-0.002036801539361477,
0.0015786334406584501,
-0.03315219283103943,
0.044327057898044586,
0.0020591833163052797,
-0.011159534566104412,
0.03968426212668419,
... |
CuongLD/wav2vec2-large-xlsr-vietnamese | [
"pytorch",
"jax",
"wav2vec2",
"automatic-speech-recognition",
"vi",
"dataset:common_voice, infore_25h",
"arxiv:2006.11477",
"arxiv:2006.13979",
"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... | 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
... | [
-0.037140581756830215,
-0.0028561772778630257,
-0.005735096521675587,
0.02591019682586193,
0.04573920741677284,
-0.021089859306812286,
-0.005246045999228954,
-0.02751609869301319,
-0.03312060981988907,
0.06651654094457626,
0.032517630606889725,
-0.02348458580672741,
0.022995945066213608,
0... |
CurtisASmith/GPT-JRT | [] | 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... | 0 | null | ---
datasets:
- relbert/semeval2012_relational_similarity
model-index:
- name: relbert/roberta-large-semeval2012-average-prompt-e-nce-classification-conceptnet-validated
results:
- task:
name: Relation Mapping
type: sorting-task
dataset:
name: Relation Mapping
args: relbert/relation_mapp... | [
-0.00122561224270612,
-0.006489964667707682,
-0.027216505259275436,
0.05382666736841202,
0.045315682888031006,
0.021970905363559723,
-0.03298588842153549,
-0.01044062152504921,
-0.06679494678974152,
0.028941817581653595,
0.018647029995918274,
0.002885887399315834,
0.015953900292515755,
0.0... |
CurtisBowser/DialoGPT-medium-sora-three | [] | null | {
"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 | ---
license: mit
---
### Erwin Olaf Style on Stable Diffusion
This is the `<erwin-olaf>` 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... | [
-0.015734408050775528,
-0.015190565027296543,
-0.030171392485499382,
0.047763194888830185,
0.01097839418798685,
0.01963213086128235,
0.0001612786581972614,
0.00706159882247448,
-0.04177381843328476,
0.04402521252632141,
-0.009775406681001186,
-0.012493204325437546,
0.034191157668828964,
0.... |
CurtisBowser/DialoGPT-medium-sora-two | [
"pytorch",
"conversational"
] | conversational | {
"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... | 0 | null | ---
license: mit
---
### Maurice-Quentin- de-la-Tour-style on Stable Diffusion
This is the `<maurice>` 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_conceptual... | [
-0.021887971088290215,
-0.01838034950196743,
-0.024945024400949478,
0.04943513497710228,
0.011499646119773388,
0.016061924397945404,
0.0014061006950214505,
0.005692597944289446,
-0.028575094416737556,
0.04044691473245621,
-0.024266807362437248,
-0.019375309348106384,
0.02268662303686142,
0... |
CurtisBowser/DialoGPT-medium-sora | [
"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:
- en
- ja
- multilingual
license: cc-by-4.0
tags:
- translation
- opus-mt-tc
model-index:
- name: opus-mt-tc-base-en-ja
results:
- task:
type: translation
name: Translation eng-jpg
dataset:
name: tatoeba-test-v2021-08-07
type: tatoeba_mt
args: eng-jpg
metrics:
... | [
-0.006373079959303141,
-0.02468787506222725,
0.008444007486104965,
0.051642853766679764,
0.04078034684062004,
0.027493849396705627,
0.0016922913491725922,
-0.00903701689094305,
-0.04488154873251915,
0.06014381721615791,
0.018672198057174683,
-0.014516527764499187,
-0.009266582317650318,
0.... |
CurtisBowser/DialoGPT-small-sora | [
"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 | 2022-09-09T21:54:47Z | ---
language:
- en
- nl
- multilingual
license: cc-by-4.0
tags:
- translation
- opus-mt-tc
model-index:
- name: opus-mt-tc-base-en-nl
results:
- task:
type: translation
name: Translation eng-mld
dataset:
name: tatoeba-test-v2021-08-07
type: tatoeba_mt
args: eng-mld
metrics:
... | [
-0.01278657652437687,
-0.01687742955982685,
0.003120147157460451,
0.04500431939959526,
0.04457125440239906,
0.03182044252753258,
-0.006863031070679426,
-0.012452327646315098,
-0.0457715205848217,
0.05835431441664696,
0.01638546772301197,
-0.01762910932302475,
-0.012365428730845451,
0.05387... |
CyberMuffin/DialoGPT-small-ChandlerBot | [
"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
- de
- multilingual
license: cc-by-4.0
tags:
- translation
- opus-mt-tc
model-index:
- name: opus-mt-tc-base-en-de
results:
- task:
type: translation
name: Translation eng-deu
dataset:
name: tatoeba-test-v2021-08-07
type: tatoeba_mt
args: eng-deu
metrics:
... | [
-0.01391500886529684,
-0.018592391163110733,
0.003920223563909531,
0.04869367554783821,
0.04165950417518616,
0.03583557903766632,
-0.006239485461264849,
-0.00814872421324253,
-0.051932696253061295,
0.06297237426042557,
0.017142130061984062,
-0.01727859489619732,
-0.018710661679506302,
0.05... |
Czapla/Rick | [] | 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... | 0 | null | # roberta-psych
---
language: en
---
This is a [RoBERTa](https://arxiv.org/pdf/1907.11692.pdf) model pretrained on Alexander Street Database of Counselling and Psychotherapy Transcripts (see more about database and its content [here](https://alexanderstreet.com/products/counseling-and-psychotherapy-transcripts-series)... | [
-0.021999210119247437,
0.0015085411723703146,
-0.011425871402025223,
0.056830208748579025,
0.05851230397820473,
0.018360907211899757,
-0.00971595011651516,
0.0004991992609575391,
-0.010129368863999844,
0.04934646934270859,
0.03233185410499573,
-0.031821224838495255,
0.029350653290748596,
0... |
D3vil/DialoGPT-smaall-harrypotter | [] | 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... | 0 | null | ---
license: mit
---
### Drive scorpion jacket on Stable Diffusion
This is the `<drive-scorpion-jacket>` 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_conceptu... | [
-0.033740464597940445,
-0.005109724123030901,
-0.03768128529191017,
0.03786594420671463,
0.018788721412420273,
0.016818851232528687,
0.0062996684573590755,
-0.004429941531270742,
-0.03579733893275261,
0.043728359043598175,
-0.001362928538583219,
-0.00996766984462738,
0.031760040670633316,
... |
D3vil/DialoGPT-smaall-harrypottery | [] | 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... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/frankdegods/1667103905913/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; wid... | [
0.005751125048846006,
-0.036625735461711884,
-0.002950716996565461,
0.04731069505214691,
0.05011340603232384,
0.010576598346233368,
-0.015014034695923328,
-0.011777854524552822,
-0.04210915416479111,
0.0343719981610775,
0.014487198553979397,
-0.00015682974481023848,
-0.01873909868299961,
0... |
D4RL1NG/yes | [] | 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... | 0 | null | ---
license: mit
---
### dark penguin pinguinanimations on Stable Diffusion
This is the `<darkpenguin-robot>` 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_con... | [
-0.03123920038342476,
-0.028012529015541077,
-0.03467940911650658,
0.043466560542583466,
0.026568090543150902,
0.010417329147458076,
0.003249956062063575,
-0.015602873638272285,
-0.021094631403684616,
0.05183422565460205,
0.00047180874389596283,
-0.019457437098026276,
0.0260548684746027,
0... |
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