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 |
|---|---|---|---|---|---|---|---|
Augustvember/WokkaBot3 | [
"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 | ---
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: 7.52 +/- 2.74... | [
-0.020478008314967155,
-0.01697101630270481,
-0.009525326080620289,
0.027065496891736984,
0.049544889479875565,
-0.0008635351550765336,
-0.01947658881545067,
0.00779628474265337,
-0.0368896909058094,
0.05209137499332428,
0.01623373106122017,
-0.00696997344493866,
0.01074474398046732,
0.026... |
Augustvember/WokkaBot7 | [] | 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 | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- metrics:
- type: mean_reward
value: 1295.00 +/- 492.10
name: mean_reward
task:
type: reinforcement-learning... | [
-0.039895832538604736,
-0.015427365899085999,
-0.017065171152353287,
0.034965597093105316,
0.05093655362725258,
-0.004216205794364214,
-0.012639468535780907,
-0.025108909234404564,
-0.03363223001360893,
0.05239167436957359,
0.02238994650542736,
-0.03053671307861805,
0.018618544563651085,
0... |
Augustvember/WokkaBot8 | [] | 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:
- fr
pipeline_tag: token-classification
widget:
- text: "La # pyrale du # buis à l'air très friande du # tournesol # semences."
example_title: "1 ravageur"
- text: "Quelles tactiques le producteur de la # SaskAg utilise-t-il pour protéger ses 13 800 acres de la cécidomyie du blé , de la fausse-teigne de... | [
0.02184944413602352,
-0.029352951794862747,
0.002947938395664096,
0.022504009306430817,
0.06560958176851273,
-0.00063257449073717,
-0.031986501067876816,
-0.027492159977555275,
-0.03630863502621651,
0.05529393255710602,
-0.008047088980674744,
-0.008502161130309105,
-0.009940623305737972,
0... |
Augustvember/WokkaBot9 | [] | 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:
- vi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: HuyenNguyen
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probabl... | [
-0.04437410086393356,
-0.013884063810110092,
-0.03196749463677406,
0.036777563393116,
0.04147937893867493,
0.029464116320014,
-0.01053362712264061,
-0.016549568623304367,
-0.03266992047429085,
0.036035191267728806,
0.03620963171124458,
-0.012939476408064365,
0.011958385817706585,
0.0328020... |
Augustvember/WokkaBot99 | [] | 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:
- 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: 7.56 +/- 2.71... | [
-0.020282918587327003,
-0.01625370979309082,
-0.007506420835852623,
0.025433437898755074,
0.04712114855647087,
-0.0016640062676742673,
-0.018613647669553757,
0.006858841981738806,
-0.037598203867673874,
0.052800457924604416,
0.016455968841910362,
-0.007090084720402956,
0.012844209559261799,
... |
Augustvember/test | [
"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... | 12 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Example Fine-Tuned Model for Unit 2 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
Describe your model here
## Usage
```python
from diffusers import DDPMPipeline
p... | [
-0.004829404875636101,
-0.018773334100842476,
0.013171205297112465,
0.024002952501177788,
0.03144903481006622,
0.012692118063569069,
0.000818876433186233,
-0.0036453325301408768,
-0.011812031269073486,
0.050794970244169235,
0.01355994027107954,
0.006749491672962904,
0.026506314054131508,
0... |
Augustvember/wokka | [
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"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... | 4 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- safetensors
- stable-diffusion
---
### Wriggly's-Extra-Gum-artstyle-ponydiffusion Dreambooth model trained by Kagerage with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb)... | [
-0.02729184180498123,
-0.011508723720908165,
-0.014724456705152988,
0.05031600967049599,
0.023749055340886116,
0.02194279432296753,
0.0017983228899538517,
-0.020447714254260063,
0.0009102537296712399,
0.04699021950364113,
0.022864878177642822,
-0.011324465274810791,
-0.017647171393036842,
... |
Augustvember/wokka2 | [
"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... | 12 | null | ---
language:
- en
license: unknown
tags:
- stable-diffusion
- text-to-image
---
A reupload of 2 model from a 🧲 link that i found interesting.
That 🧲 contain several safetensors model, 200GB in total. | [
-0.023791959509253502,
-0.032455991953611374,
0.006544906180351973,
0.026456736028194427,
0.03011036477982998,
0.0067469272762537,
0.024712160229682922,
0.0009771011536940932,
-0.03209656849503517,
0.04666188731789589,
0.033292628824710846,
-0.00255182315595448,
0.03512853756546974,
0.0374... |
Aurora/community.afpglobal | [] | 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:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.04067319631576538,
-0.0010963407112285495,
-0.005900859367102385,
0.04896730184555054,
0.02956347167491913,
0.021194331347942352,
-0.024730369448661804,
-0.037212271243333817,
-0.005357447545975447,
0.04906168952584267,
0.018759243190288544,
-0.009519155137240887,
0.020109932869672775,
... |
Ayham/albert_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 7 | null | Fusion-in-Decoder (FiD) is a model described in the following paper:
> Izacard, Gautier, and Édouard Grave. [Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering](https://aclanthology.org/2021.eacl-main.74/). _Proceedings of the 16th Conference of the European Chapter of the Associati... | [
0.012073477730154991,
-0.023950407281517982,
-0.026021504774689674,
0.04261068254709244,
0.00701543502509594,
0.027975566685199738,
-0.005195186007767916,
-0.002232305007055402,
-0.028886882588267326,
0.022778881713747978,
0.049287348985672,
0.02795977145433426,
0.013477442786097527,
0.044... |
Ayham/albert_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | null | ---
license: cc0-1.0
---
I created this embedding for SD 2.x 768x768 models, it turns everything into your favorite Christmas classic AniMagic stop motion style as popularized by Rudolf the Red Nosed Reindeer and Santa Claus is Coming to Town among several others produced by the same studio!
The Unreleased Christmas S... | [
-0.03517995402216911,
-0.02915051579475403,
-0.012030601501464844,
0.03138943016529083,
0.06096987798810005,
0.02554592303931713,
-0.011010236106812954,
-0.007350810803472996,
-0.025390030816197395,
0.06968667358160019,
0.01639387756586075,
-0.02783229760825634,
0.020570190623402596,
0.032... |
Ayham/bert_bert_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | Fusion-in-Decoder (FiD) is a model described in the following paper:
> Izacard, Gautier, and Édouard Grave. [Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering](https://aclanthology.org/2021.eacl-main.74/). _Proceedings of the 16th Conference of the European Chapter of the Associati... | [
0.01372696552425623,
-0.0283537358045578,
-0.027344517409801483,
0.04404196888208389,
0.007406134158372879,
0.026262708008289337,
-0.006392025854438543,
-0.00381906284019351,
-0.03284994140267372,
0.025895357131958008,
0.05429164692759514,
0.030880676582455635,
0.00647836085408926,
0.03831... |
Ayham/bert_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | 2022-12-24T05:01:19Z | ---
license: creativeml-openrail-m
tags:
- conversational
---
This is just a mirror of [ConvoGPT-1.3B](https://huggingface.co/hakurei/convogpt-staging/tree/main/1.3b-uft) just for archiving purposes. | [
-0.03307391330599785,
0.015269456431269646,
-0.02930690534412861,
0.012927998788654804,
0.041234489530324936,
0.02000265009701252,
0.0027585849165916443,
0.012485994026064873,
-0.026030220091342926,
0.024591291323304176,
0.03466346487402916,
0.011209537275135517,
0.01663791574537754,
0.047... |
Ayham/bertgpt2_cnn | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
language:
- vi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: Hieu Dam Model Shuffle
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
sho... | [
-0.04754148796200752,
-0.00987479742616415,
-0.017518963664770126,
0.03470427915453911,
0.042191650718450546,
0.005563750397413969,
0.014180181547999382,
-0.00014146244211588055,
-0.04832934960722923,
0.05215485394001007,
0.02913111075758934,
-0.0076677738688886166,
-0.0011427451390773058,
... |
Ayham/distilbert_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 5 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.041592370718717575,
-0.017019445076584816,
-0.017625216394662857,
0.0337713286280632,
0.05070365220308304,
-0.004389533307403326,
-0.013772709295153618,
-0.025751395151019096,
-0.03184756264090538,
0.052874695509672165,
0.022029204294085503,
-0.0316927433013916,
0.018302997574210167,
0.... |
Ayham/distilbert_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
language:
- zh
tags:
- unilm
license: apache-2.0
---
# unilm-base-chinese-news-sum
```sh
pip install git+https://github.com/Liadrinz/transformers-unilm # 安装兼容HuggingFace的UniLM模型代码
```
```py
from unilm import UniLMTokenizer, UniLMForConditionalGeneration
news_article = (
"12月23日，河北石家庄。8岁哥哥轻车熟路哄睡弟弟，姿势标准... | [
-0.03237688168883324,
-0.03687897324562073,
-0.005136257037520409,
0.05488476902246475,
0.033037398010492325,
0.026734761893749237,
-0.017633778974413872,
-0.03542092442512512,
-0.036759376525878906,
0.0638740211725235,
0.011738908477127552,
0.0015790980542078614,
0.025516526773571968,
0.0... |
Ayham/distilbert_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 14 | null | ---
language:
- ja
license: other
tags:
- whisper-event
- generated_from_trainer
datasets:
- Elite35P-Server/EliteVoiceProject
metrics:
- wer
model-index:
- name: Whisper Base Japanese Elite
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: E... | [
-0.02837844006717205,
-0.017971571534872055,
0.005910661071538925,
0.04079214856028557,
0.05134473368525505,
0.019897280260920525,
-0.0077628097496926785,
-0.02226414903998375,
-0.03290123492479324,
0.0589582622051239,
0.045908212661743164,
-0.02954893931746483,
0.004684822633862495,
0.027... |
Ayham/ernie_gpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 13 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Example Fine-Tuned Model for Unit 2 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
Describe your model here
## Usage
```python
from diffusers import DDPMPipeline
p... | [
-0.006507342681288719,
-0.018839167430996895,
0.014721081592142582,
0.025845536962151527,
0.030689449980854988,
0.012405727989971638,
0.0015786420553922653,
-0.0019377537537366152,
-0.009684903547167778,
0.050179120153188705,
0.015319691970944405,
0.004584082867950201,
0.024508727714419365,
... |
Ayham/roberta_gpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 31 | null | ---
license: cc-by-nc-sa-4.0
language:
- en
thumbnail: "https://huggingface.co/GeneralAwareness/Ppgra/resolve/main/photograph of johnny depp - ppgra.png"
tags:
- stable-diffusion
- v2
- text-to-image
- image-to-image
- Embedding
---
Textual Inversion Embedding by General Awareness For SD 2.x trained on 768x768 imag... | [
-0.003194606862962246,
-0.0021540725138038397,
-0.026124484837055206,
0.034444693475961685,
0.051854562014341354,
0.037250351160764694,
-0.01991465501487255,
-0.007436234038323164,
-0.026595212519168854,
0.05180160701274872,
-0.007478637155145407,
-0.045935746282339096,
-0.01666671223938465,... |
Ayham/roberta_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.039744313806295395,
-0.0015044126193970442,
-0.006848711986094713,
0.04941493645310402,
0.029176639392971992,
0.022257840260863304,
-0.02548186667263508,
-0.03710716962814331,
-0.005718480329960585,
0.05020078644156456,
0.018680209293961525,
-0.010798102244734764,
0.021426521241664886,
... |
Ayham/robertagpt2_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
license: cc-by-4.0
---
# Description: 한국어 수학교육 텍스트로 학습한 토크나이저
- 학습 데이터 저작권: 두산동아, 미래엔, 비상에듀, 지학사, 한국교육과정평가원
- 모델 체크포인트: skt/kogpt2-base-v2
- 개인 연구 목적으로 사용, 개발중인 토크나이저입니다. 학습 데이터 저작권이 저에게 있지 않으므로, 무단 사용을 자제해주세요.
# What to do
- 수학교육 분야의 여러 tasks에서 사용가능한 언어 모델을 개발중입니다.
# How to use
```python
>>> from transformers im... | [
0.018296923488378525,
-0.03897447884082794,
-0.008470103144645691,
0.03355381265282631,
0.0292976051568985,
0.031282443553209305,
-0.0013534579193219543,
0.008651290088891983,
-0.04873386397957802,
0.04482409730553627,
0.006708554457873106,
0.00036516421823762357,
0.008212226442992687,
0.0... |
Ayham/xlmroberta_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 9 | 2022-12-24T07:02:02Z | ---
license: openrail
library_name: diffusers
tags:
- TPU
- JAX
- Flax
- stable-diffusion
- text-to-image
language:
- en
thumbnail: https://huggingface.co/camenduru/plushies/resolve/main/samples.jpg
datasets:
- camenduru/plushies
inference: false
---
Maybe this is the first ever model trained with TPUs and converted t... | [
-0.016619021072983742,
-0.027047457173466682,
0.007881112396717072,
0.04097292944788933,
0.04781464859843254,
0.0160982608795166,
0.0014435993507504463,
-0.01419144868850708,
-0.008215747773647308,
0.026666173711419106,
0.005285430233925581,
0.00013665870937984437,
0.012739386409521103,
0.... |
Ayham/xlmroberta_large_gpt2_summarization_cnndm | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 12 | null | ---
license: mit
---
## GPT-2 Tokenizer with unmerged digits
A fork of the GPT-2 tokenizer, which **removes multi-digit tokens**:
```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('cyrilzhang/gpt2-numfix')
tokenizer('123.45') # [16, 17, 18, 13, 19, 20]
gpt2_tokenizer('123.... | [
-0.03251614421606064,
-0.025090837851166725,
-0.015493764542043209,
0.021227488294243813,
0.04471807926893234,
0.02887790836393833,
-0.012723984196782112,
0.02540852688252926,
-0.009820574894547462,
0.024986794218420982,
0.02818925492465496,
0.011317272670567036,
0.007937045767903328,
0.03... |
Ayham/xlnet_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 13 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.04465325549244881,
-0.01895853318274021,
-0.016181977465748787,
0.03280165418982506,
0.05020739510655403,
-0.005627999547868967,
-0.012865153141319752,
-0.025539075955748558,
-0.03178417310118675,
0.05177393555641174,
0.01991366595029831,
-0.03181016072630882,
0.018495358526706696,
0.01... |
Ayham/xlnet_roberta_new_summarization_cnn_dailymail | [] | 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 | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.04328209534287453,
-0.01727459207177162,
-0.01898469775915146,
0.03558952733874321,
0.05083553493022919,
-0.0036487411707639694,
-0.013635260984301567,
-0.025218529626727104,
-0.03287313133478165,
0.052465930581092834,
0.023324420675635338,
-0.03174064680933952,
0.019393114373087883,
0.... |
Ayjayo/DialoGPT-medium-AyjayoAI | [
"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... | 12 | 2022-12-24T07:52:19Z | ---
language:
- vi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: HuyenNguyen
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probabl... | [
-0.04437410086393356,
-0.013884063810110092,
-0.03196749463677406,
0.036777563393116,
0.04147937893867493,
0.029464116320014,
-0.01053362712264061,
-0.016549568623304367,
-0.03266992047429085,
0.036035191267728806,
0.03620963171124458,
-0.012939476408064365,
0.011958385817706585,
0.0328020... |
Aymene/opus-mt-en-ro-finetuned-en-to-ro | [] | 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:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery-h
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Froz... | [
-0.018993500620126724,
-0.017675988376140594,
-0.011013492941856384,
0.029791483655571938,
0.051072217524051666,
-0.016695722937583923,
-0.013372679241001606,
-0.010526468977332115,
-0.053928010165691376,
0.051453255116939545,
-0.0012080537853762507,
-0.00808970257639885,
0.02477245219051838... |
Ayran/DialoGPT-medium-harry-1 | [] | 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: other
widget:
- text: "Christmas"
example_title: "Christmas"
- text: "Lego"
example_title: "Lego"
inference:
parameters:
temperature: 1.25
repetition_penalty: 1.25
min_length: 96
max_length: 128
---
This is the model trained for this short video:
https://www.youtube.com/shorts/hpIUK... | [
-0.029692305251955986,
0.014844682067632675,
0.007019244600087404,
0.06556358933448792,
0.04400648549199104,
0.031262677162885666,
0.004851543344557285,
0.010473594069480896,
-0.01743161492049694,
0.05115202069282532,
0.04253694415092468,
0.010352445766329765,
-0.01443480420857668,
0.01224... |
Azaghast/GPT2-SCP-Miscellaneous | [
"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... | 5 | 2022-12-24T09:44:16Z | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.03976627066731453,
-0.016538135707378387,
-0.013599102385342121,
0.03730570897459984,
0.04862893745303154,
-0.004475489724427462,
-0.013957975432276726,
-0.023405393585562706,
-0.029441259801387787,
0.053949158638715744,
0.02022315189242363,
-0.03297789394855499,
0.016663724556565285,
0... |
BJTK2/model_name | [] | 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:
- 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... | [
-0.015014012344181538,
-0.01697639748454094,
-0.007004616316407919,
0.029003707692027092,
0.051801662892103195,
-0.015062307007610798,
-0.012394028715789318,
-0.009077910333871841,
-0.058275654911994934,
0.05650924891233444,
-0.00007478403131244704,
-0.009885088540613651,
0.02702670171856880... |
BSC-LT/roberta-base-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 | {
"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_... | 12 | 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... | [
-0.018018275499343872,
-0.018487678840756416,
-0.0075598908588290215,
0.031756654381752014,
0.05124504119157791,
-0.016695642843842506,
-0.011557691730558872,
-0.009634031914174557,
-0.059134431183338165,
0.05454602465033531,
-0.0011664554476737976,
-0.008566752076148987,
0.02418566308915615... |
BSC-LT/roberta-base-ca | [
"pytorch",
"roberta",
"fill-mask",
"ca",
"transformers",
"masked-lm",
"BERTa",
"catalan",
"license:apache-2.0",
"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... | 18 | null | ---
language:
- vi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: HuyenNguyen
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probabl... | [
-0.04437410086393356,
-0.013884063810110092,
-0.03196749463677406,
0.036777563393116,
0.04147937893867493,
0.029464116320014,
-0.01053362712264061,
-0.016549568623304367,
-0.03266992047429085,
0.036035191267728806,
0.03620963171124458,
-0.012939476408064365,
0.011958385817706585,
0.0328020... |
BSC-LT/roberta-large-bne-sqac | [
"pytorch",
"roberta",
"question-answering",
"es",
"dataset:BSC-TeMU/SQAC",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"qa",
"question answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 15 | null | ---
license: creativeml-openrail-m
language:
- en
tags:
- text-to-image
- stable-diffusion
- stable-diffusion-diffusers
#datasets:
#- Name/name
inference: true
widget:
- text: disc demon
- text: disc demon | [
-0.027069147676229477,
-0.006035903934389353,
-0.03415893763303757,
0.014874263666570187,
0.0624329037964344,
0.0019045118242502213,
0.016164273023605347,
-0.003828109707683325,
-0.009713956154882908,
0.04128580167889595,
0.04388291388750076,
0.014654404483735561,
0.014766460284590721,
0.0... |
Babelscape/wikineural-multilingual-ner | [
"pytorch",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"de",
"en",
"es",
"fr",
"it",
"nl",
"pl",
"pt",
"ru",
"multilingual",
"dataset:Babelscape/wikineural",
"transformers",
"named-entity-recognition",
"sequence-tagger-model",
"license:cc-by-nc-sa-4.0",
"aut... | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 41,608 | null | ---
language:
- uz
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_10_0
- AIRI_UZ
- generated_from_trainer
datasets:
- common_voice_10_0
model-index:
- name: uzbek_stt
results: []
---
## Oyqiz jamoasi a'zolari tomonidan qilingan STT ning eng yaxshi versiyasi!
### Foziljon ... | [
-0.025305921211838722,
-0.020312920212745667,
-0.02362162619829178,
0.04843195900321007,
0.06454578042030334,
0.03773506358265877,
-0.0025693534407764673,
-0.011967504397034645,
-0.04772679880261421,
0.05097309872508049,
0.041967105120420456,
-0.027036087587475777,
0.0067818923853337765,
0... |
Bagus/wav2vec2-xlsr-japanese-speech-emotion-recognition | [
"pytorch",
"wav2vec2",
"audio-classification",
"ja",
"dataset:jtes",
"transformers",
"audio",
"speech",
"speech-emotion-recognition",
"has_space"
] | audio-classification | {
"architectures": [
"HubertForSequenceClassification"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 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: 7.56 +/- 2.71... | [
-0.021111134439706802,
-0.01662357524037361,
-0.007872520014643669,
0.027052568271756172,
0.0479762963950634,
-0.0007744247559458017,
-0.019030362367630005,
0.006191837601363659,
-0.03796479478478432,
0.0522412471473217,
0.017664724960923195,
-0.007292794529348612,
0.010454965755343437,
0.... |
Bakkes/BakkesModWiki | [] | 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: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- science
widget:
- text: 3d diagram of the solar system in the style of pprotein
---
# DreamBooth model for the pprotein concept trained by jonathang on the jonathang/dream... | [
-0.0217422042042017,
-0.024078810587525368,
-0.01719045825302601,
0.020955223590135574,
0.04518866911530495,
0.02060716412961483,
0.003603051882237196,
0.0020061442628502846,
-0.02032473124563694,
0.046871211379766464,
0.014839724637567997,
0.016667474061250687,
-0.02043154276907444,
0.045... |
Balgow/prod_desc | [] | 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 | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.042094796895980835,
-0.016472868621349335,
-0.017546074464917183,
0.03302072733640671,
0.049967847764492035,
-0.005128008313477039,
-0.013968049548566341,
-0.02547861635684967,
-0.032789792865514755,
0.05384999141097069,
0.022375019267201424,
-0.03084060549736023,
0.018455274403095245,
... |
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 | {
"architectures": [
"CamembertForSequenceClassification"
],
"model_type": "camembert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 405,474 | null | ---
license: creativeml-openrail-m
---
This is a fine-tuned version of the [Stable Diffusion model available from KerasCV](https://github.com/keras-team/keras-cv/tree/master/keras_cv/models/stable_diffusion). Fine-tuning code is available [here](https://github.com/sayakpaul/stabe-diffusion-keras-ft). The weights provi... | [
-0.034154362976551056,
-0.013552737422287464,
-0.018906759098172188,
0.011028577573597431,
0.024473601952195168,
0.0020540663972496986,
0.01665029488503933,
0.009080439805984497,
-0.02390144392848015,
0.046719737350940704,
0.00831674039363861,
0.007003234699368477,
0.03568103909492493,
0.0... |
Barbarameerr/Barbara | [] | 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
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```pyth... | [
-0.020757796242833138,
-0.013112966902554035,
0.011127213016152382,
0.03160317987203598,
0.023820364847779274,
0.025223352015018463,
0.0049784258008003235,
-0.007620096672326326,
-0.006219564005732536,
0.06260652095079422,
-0.0014202437596395612,
-0.01474264170974493,
0.024614907801151276,
... |
Begimay/Task | [] | 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:
- 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... | [
-0.017852528020739555,
-0.01804402843117714,
-0.008116506040096283,
0.02989240735769272,
0.051379233598709106,
-0.017841985449194908,
-0.010296603664755821,
-0.011200705543160439,
-0.05576245114207268,
0.05448701232671738,
-0.00162629468832165,
-0.009079123847186565,
0.02582375891506672,
0... |
BertChristiaens/EmojiPredictor | [
"pytorch",
"distilbert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"DistilBertForTokenClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 6 | 2022-12-24T16:55:42Z | Explain Humanity
Muhammad Naeem
Can you explain humanity
Humanity refers to the human race, which includes all people on Earth. It is a term that encompasses the shared characteristics and qualities that define what it means to be human, such as the capacity for reason, emotion, creativity, and culture.
As a specie... | [
-0.011217152699828148,
0.014132535085082054,
-0.019393352791666985,
0.0021512471139431,
0.06675510108470917,
0.032316386699676514,
-0.003164976369589567,
0.0012568134116008878,
-0.029262129217386246,
0.04361937567591667,
0.051850419491529465,
-0.000530387507751584,
0.02801389805972576,
0.0... |
BhanuSama/gpt2-finetuned-xsum | [] | 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 | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.04148189723491669,
-0.019097771495580673,
-0.017149347811937332,
0.034520428627729416,
0.05129748582839966,
-0.004452576860785484,
-0.014138978905975819,
-0.025021828711032867,
-0.030375385656952858,
0.053059425204992294,
0.021123098209500313,
-0.03149152919650078,
0.01736593060195446,
... |
Bharathdamu/wav2vec2-large-xls-r-300m-hindi3-colab | [] | 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: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
Model Trained by (https://linktr.ee/kukuhtw) using fast-dreambooth (https://github.com/TheLastBen/fast-stable-diffusion)
<b>use keyword prompt</b> : 👉👉👉 <b><i>ganjarpranowo</i></b> 👈👈👈
<b>sample prompt below this :</b>
<i>ganjar... | [
0.012045475654304028,
-0.029381845146417618,
-0.01854090206325054,
0.039429739117622375,
0.05080227553844452,
0.009011548012495041,
-0.00270403316244483,
-0.027105214074254036,
-0.01872188225388527,
0.054048798978328705,
0.03163626044988632,
-0.010049261152744293,
-0.02538737840950489,
0.0... |
Bia18/Beatriz | [] | 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 | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.04204115644097328,
-0.016480104997754097,
-0.017547525465488434,
0.032645128667354584,
0.05092283710837364,
-0.0055526248179376125,
-0.013315362855792046,
-0.025131840258836746,
-0.03280078247189522,
0.053329259157180786,
0.022470567375421524,
-0.031328748911619186,
0.017163315787911415,
... |
Biasface/DDDC | [
"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... | 14 | null | ---
tags:
- autotrain
- stable-diffusion
- text-to-image
datasets:
- clem/autotrain-data-friedeberg-0OIYU5UZXE
co2_eq_emissions:
emissions: 23.966933198902527
---
# Model Trained Using AutoTrain
- Problem type: Dreambooth
- Model ID: 2603979056
- CO2 Emissions (in grams): 23.9669 | [
-0.016727527603507042,
-0.014347268268465996,
0.000026284924388164654,
0.01026394683867693,
0.048832785338163376,
0.012535865418612957,
-0.008901361376047134,
0.0007101162918843329,
-0.040915437042713165,
0.05576688051223755,
0.03481491655111313,
0.020135754719376564,
-0.004015559796243906,
... |
BigSalmon/FormalRobertaa | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | 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... | 5 | null | ---
tags:
- autotrain
- stable-diffusion
- text-to-image
datasets:
- clem/autotrain-data-maxdekdt-AER2SE090K
co2_eq_emissions:
emissions: 86.12664300406121
license: openrail
language:
- en
---
# Model Trained Using AutoTrain
- Problem type: Dreambooth
- Model ID: 2604679068
- CO2 Emissions (in grams): 86.1266 | [
-0.020497098565101624,
-0.012599967420101166,
-0.003004899248480797,
0.013944875448942184,
0.05555027350783348,
0.011684396304190159,
-0.007897088304162025,
0.000509557081386447,
-0.0416562594473362,
0.05258220061659813,
0.028046002611517906,
0.022513609379529953,
-0.006229120306670666,
0.... |
BigSalmon/FormalRobertaaa | [
"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... | 12 | 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:... | [
-0.0005877850926481187,
0.010339731350541115,
-0.014612163417041302,
0.02967444434762001,
0.03804205730557442,
0.011578847654163837,
-0.03624425455927849,
-0.03792067617177963,
-0.032463159412145615,
0.056647736579179764,
0.028487717732787132,
-0.012899610213935375,
0.019953029230237007,
0... |
BigSalmon/GPT2HardArticleEasyArticle | [
"pytorch",
"jax",
"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... | 7 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```pyth... | [
-0.023766091093420982,
-0.012682569213211536,
0.009449251927435398,
0.03217343986034393,
0.022480858489871025,
0.026354491710662842,
0.005132968071848154,
-0.006026907823979855,
-0.007348368875682354,
0.06240827962756157,
-0.003171011805534363,
-0.015155762434005737,
0.02329373173415661,
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": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | 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
config: plus
... | [
-0.007540320977568626,
0.0029967029113322496,
-0.03131501004099846,
0.040079515427351,
0.05364162102341652,
0.011722936294972897,
-0.031281765550374985,
-0.026039138436317444,
-0.02862939052283764,
0.054938048124313354,
0.0032532927580177784,
-0.012917030602693558,
0.012383035384118557,
0.... |
BigSalmon/GPTNeo350MInformalToFormalLincoln | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 8 | 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:... | [
-0.00004435248774825595,
0.0108231445774436,
-0.014329514466226101,
0.02908729761838913,
0.038403160870075226,
0.011748983524739742,
-0.03640091046690941,
-0.037067215889692307,
-0.032254308462142944,
0.057301584631204605,
0.028211282566189766,
-0.013595609925687313,
0.01967650279402733,
0... |
BigSalmon/GPTNeo350MInformalToFormalLincoln3 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 10 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71
... | [
-0.02627127431333065,
-0.01818389818072319,
-0.00907297246158123,
0.027643946930766106,
0.043465159833431244,
-0.004314897116273642,
-0.02006806805729866,
0.00778611097484827,
-0.03536168858408928,
0.05489832162857056,
0.019053367897868156,
-0.0037569657433778048,
0.011291093192994595,
0.0... |
BigSalmon/GPTNeo350MInformalToFormalLincoln5 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 11 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: uzroberta-sentiment-analysis
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 th... | [
-0.010104316286742687,
-0.010250612162053585,
-0.024478169158101082,
0.03626426309347153,
0.04928724467754364,
0.03396691381931305,
-0.016699383035302162,
-0.022524237632751465,
-0.053734563291072845,
0.05929385870695114,
0.020067689940333366,
-0.04666615277528763,
0.004071859642863274,
0.... |
BigSalmon/InfillFormalLincoln | [
"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... | 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
... | [
-0.03753102943301201,
-0.003016060683876276,
-0.005243847146630287,
0.02535262145102024,
0.04528677091002464,
-0.02163599617779255,
-0.0051335422322154045,
-0.028247907757759094,
-0.03369799628853798,
0.06634269654750824,
0.0324883908033371,
-0.023207619786262512,
0.022786663845181465,
0.0... |
BigSalmon/InformalToFormalLincoln15 | [
"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... | 11 | null | ---
license: openrail
---
# ⚠️ Type of model/library unknown.
# Feel free to open a Pull request
# for integration of the huggingface model hub
# into the corresponding library =) | [
-0.05850060656666756,
-0.010053894482553005,
-0.0038186621386557817,
0.016766516491770744,
0.021285483613610268,
0.02011464163661003,
-0.031100960448384285,
-0.0018828808097168803,
-0.012402690015733242,
0.040415238589048386,
-0.007714549079537392,
0.02282549813389778,
0.034349411725997925,
... |
BigSalmon/InformalToFormalLincoln16 | [
"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... | 8 | 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: 7.56 +/- 2.71... | [
-0.020253943279385567,
-0.015229991637170315,
-0.007297482807189226,
0.024914152920246124,
0.047117993235588074,
-0.0018116430146619678,
-0.019650334492325783,
0.006546832621097565,
-0.03767186775803566,
0.052240677177906036,
0.01644088886678219,
-0.006499702110886574,
0.01270049437880516,
... |
BigSalmon/InformalToFormalLincoln21 | [
"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... | 8 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.04041924700140953,
-0.0009931279346346855,
-0.008859903551638126,
0.049410413950681686,
0.029726773500442505,
0.02189376763999462,
-0.02610727772116661,
-0.03588700667023659,
-0.007478517480194569,
0.04942067712545395,
0.018304644152522087,
-0.009304516017436981,
0.01958833448588848,
0.... |
BigSalmon/InformalToFormalLincoln23 | [
"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... | 5 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### ANYTHING-MIDJOURNEY-V-4.1 Dreambooth model trained by Joeythemonster with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the conc... | [
-0.032875243574380875,
-0.021003080531954765,
-0.03336980938911438,
0.03111298941075802,
0.021184608340263367,
0.024529367685317993,
0.0016112992307171226,
-0.011881591752171516,
-0.01041076797991991,
0.025201497599482536,
0.042878102511167526,
0.008073901757597923,
-0.017083290964365005,
... |
BigSalmon/InformalToFormalLincoln25 | [
"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... | 10 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: geocoder_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. --... | [
-0.02492050640285015,
-0.0012649913551285863,
-0.011311355046927929,
0.051549963653087616,
0.04833676666021347,
0.010343276895582676,
0.0027409519534558058,
-0.014153500087559223,
-0.05236097052693367,
0.06604844331741333,
0.003396255662664771,
-0.02710092067718506,
0.006825330667197704,
0... |
BigSalmon/MrLincoln12 | [
"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... | 9 | 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
... | [
-0.03889419138431549,
-0.00243758806027472,
-0.0027258999180048704,
0.026758361607789993,
0.04300343617796898,
-0.02012587897479534,
-0.006439896300435066,
-0.02880178764462471,
-0.033879127353429794,
0.0690823346376419,
0.03514830395579338,
-0.020781464874744415,
0.02122851088643074,
0.00... |
BigSalmon/MrLincoln13 | [
"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... | 9 | null | ---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_engagement_spl_RoBERTa_acad
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.0
- name: NER Recall
type: recall
value: 0.0
-... | [
0.026833457872271538,
-0.03316793963313103,
-0.01897536776959896,
0.03184615448117256,
0.06004472076892853,
0.0247717946767807,
-0.03865472599864006,
-0.005712890066206455,
-0.052780285477638245,
0.0776958018541336,
0.025134436786174774,
-0.010726554319262505,
0.009954805485904217,
0.05070... |
BigSalmon/MrLincoln2 | [
"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... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-large-uncased-finetuned-bert-large-uncase-p2
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 c... | [
-0.015456845983862877,
0.009310760535299778,
-0.014717578887939453,
0.04669683426618576,
0.03945397213101387,
-0.0026580605190247297,
-0.015566780231893063,
-0.03660404682159424,
-0.03158799558877945,
0.055144038051366806,
0.01444775890558958,
-0.01806989498436451,
0.027216313406825066,
0.... |
BigSalmon/MrLincoln7 | [] | 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 | ---
pipeline_tag: text-classification
language: en
license: apache-2.0
tags:
- sentiment-analysis
widget:
- text: I am very happy.
example_title: English
---
Enter comments and find out the sentiment of the comment | [
-0.017491629347205162,
-0.002596004167571664,
-0.004260732792317867,
0.0425286702811718,
0.05461207032203674,
0.026692822575569153,
-0.01823887974023819,
0.016614947468042374,
-0.025383897125720978,
0.0393073633313179,
0.022255679592490196,
-0.006576669402420521,
0.017252711579203606,
0.03... |
BigSalmon/MrLincoln8 | [
"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: other
tags:
- generated_from_trainer
model-index:
- name: opt-350m
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. -->
# opt-350m
This model is a fine-... | [
-0.03435167670249939,
-0.003842167789116502,
-0.011451386846601963,
0.0287493746727705,
0.025658363476395607,
0.02327437326312065,
-0.011895562522113323,
-0.00015774578787386417,
-0.034637462347745895,
0.05471762642264366,
0.05635567754507065,
-0.009586745873093605,
-0.002567754127085209,
... |
BigSalmon/ParaphraseParentheses | [
"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... | 10 | 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
... | [
-0.037221137434244156,
-0.0027464041486382484,
-0.005307888146489859,
0.02565934509038925,
0.04574828967452049,
-0.020902439951896667,
-0.005408497527241707,
-0.027875052765011787,
-0.032842058688402176,
0.06640337407588959,
0.0330006405711174,
-0.02346307784318924,
0.022740382701158524,
0... |
BigSalmon/PhraseBerta | [
"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 | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: roberta-retrained-350k
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. -->
# roberta-retrained-3... | [
-0.026924394071102142,
-0.009052492678165436,
-0.020878689363598824,
0.030283017084002495,
0.0249866284430027,
0.037505097687244415,
-0.01648508384823799,
-0.004753971006721258,
-0.04476983845233917,
0.06282132118940353,
0.019895797595381737,
-0.024062594398856163,
0.027287723496556282,
0.... |
BigSalmon/Points | [
"pytorch",
"tensorboard",
"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... | 13 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.037470098584890366,
-0.0017934015486389399,
-0.005505565088242292,
0.04859703406691551,
0.030095485970377922,
0.022443266585469246,
-0.024569585919380188,
-0.03815946727991104,
-0.007365052588284016,
0.0511336550116539,
0.020453250035643578,
-0.008083874359726906,
0.02194950357079506,
0... |
BigSalmon/T52 | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 8 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ohss117/bert-finetuned-ner_v3
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. -->
# ohss... | [
-0.024531744420528412,
-0.01124750915914774,
-0.006011087913066149,
0.015615380369126797,
0.030603580176830292,
0.013401670381426811,
-0.02607095241546631,
-0.027960211038589478,
-0.042801592499017715,
0.05224095284938812,
0.01566525362432003,
-0.016748975962400436,
0.029814034700393677,
0... |
BigSalmon/TS3 | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible",
"has_space"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 7 | null | ---
language:
- en
tags:
- webgpt
- regression
- reward-model
license: "apache-2.0"
datasets:
- openai/webgpt_comparisons
metrics:
- accuracy
---
# Reward Model pretrained on openai/webgpt_comparison
Reward model finetuned from existing pretrain model.
Things that aligned with the orignal papers
* Overfits easil... | [
-0.019759828224778175,
-0.009246938861906528,
-0.004313142038881779,
0.04266674816608429,
0.030460195615887642,
-0.015256720595061779,
-0.013549188151955605,
-0.015600395388901234,
-0.04260120913386345,
0.07138682156801224,
0.03873322904109955,
-0.014019785448908806,
-0.011236532591283321,
... |
Bilz/DialoGPT-small-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 | ---
language:
- en
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
# Smelon.com备份
# Anything备份版
# Anything V3
欢迎使用 Anything V3 - weebs 的潜在扩散模型。该模型旨在通过几个提示生成高质量、高度详细的动漫风格。与其他动漫风格的 Stable Diffusion 模型一样，它也支持 danbooru 标签生成图像。
例如 **_1gi... | [
-0.001449695904739201,
-0.03505927324295044,
-0.007541193626821041,
0.04853130504488945,
0.03462906926870346,
0.00400066003203392,
-0.0009707189165055752,
-0.01642945408821106,
-0.02516966126859188,
0.0630139410495758,
0.010322119109332561,
-0.004011030774563551,
0.013191308826208115,
0.03... |
BinksSachary/DialoGPT-small-shaxx | [
"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... | 12 | null | ---
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- food
widget:
- text: A photo of cmexsks drink with ice cream on top
---
# DreamBooth model for the cmexsks concept trained by shahp7575 on the shahp7575/chemex dataset.
T... | [
-0.014464347623288631,
-0.014618261717259884,
-0.011762862093746662,
0.033701617270708084,
0.03045952320098877,
0.0030772038735449314,
0.0008532037027180195,
0.0015687269624322653,
-0.015389435924589634,
0.05131248012185097,
0.04296863079071045,
0.012609614059329033,
-0.012841034680604935,
... |
BlindMan820/Sarcastic-News-Headlines | [
"pytorch",
"distilbert",
"text-classification",
"English",
"dataset:Kaggle Dataset",
"transformers",
"Text",
"Sequence-Classification",
"Sarcasm",
"DistilBert"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 28 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: 20NG_BERT_1E
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. -->
# 20NG_BERT_1E
This mod... | [
-0.02412075735628605,
-0.0018205803353339434,
-0.02567833475768566,
0.04558182880282402,
0.033627089112997055,
0.028834884986281395,
-0.005565941333770752,
-0.020778443664312363,
-0.041858602315187454,
0.04834947735071182,
0.032342616468667984,
-0.013646114617586136,
0.016820335760712624,
... |
Bloodwarrior/Chikfalay | [] | 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 | ---
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
... | [
-0.03785614296793938,
-0.0025950900744646788,
-0.005517695099115372,
0.02524886280298233,
0.0452035516500473,
-0.02147880755364895,
-0.005351691506803036,
-0.027679409831762314,
-0.03361769765615463,
0.06644775718450546,
0.03299495205283165,
-0.023884285241365433,
0.02236763946712017,
0.00... |
BobBraico/distilbert-base-uncased-finetuned-imdb-accelerate | [] | 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:
- vi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: HuyenNguyen
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probabl... | [
-0.04437410086393356,
-0.013884063810110092,
-0.03196749463677406,
0.036777563393116,
0.04147937893867493,
0.029464116320014,
-0.01053362712264061,
-0.016549568623304367,
-0.03266992047429085,
0.036035191267728806,
0.03620963171124458,
-0.012939476408064365,
0.011958385817706585,
0.0328020... |
Brendan/cse244b-hw2-roberta | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 28 | 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... | [
-0.01749899610877037,
-0.017323223873972893,
-0.0072670443914830685,
0.029451970010995865,
0.05184532329440117,
-0.01718938536942005,
-0.011527392081916332,
-0.008413153700530529,
-0.057732075452804565,
0.05321387201547623,
-0.0015308496076613665,
-0.00906586367636919,
0.024527134373784065,
... |
Broadus20/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"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 | ---
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... | [
-0.018422672525048256,
-0.019506823271512985,
-0.006204243749380112,
0.030625492334365845,
0.04972604289650917,
-0.01816069521009922,
-0.012369468808174133,
-0.00883533339947462,
-0.05975180119276047,
0.0539349764585495,
-0.0026726953219622374,
-0.008134781382977962,
0.027537336573004723,
... |
Brokette/projetCS | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | 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... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 20NG_ELECTRA_5E
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. -->
#... | [
-0.024492722004652023,
0.010201839730143547,
0.009860330261290073,
0.01767401583492756,
0.040445201098918915,
0.016068439930677414,
-0.01814921759068966,
-0.004684156272560358,
-0.043510742485523224,
0.043875664472579956,
0.021591220051050186,
-0.02401096560060978,
0.005793725606054068,
0.... |
Brona/poc_de | [] | 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: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 20NG_ALBERT_5E
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. -->
# ... | [
-0.0176285021007061,
0.004322283435612917,
-0.008562801405787468,
0.03807872161269188,
0.03713283687829971,
0.0035260275471955538,
-0.01351608894765377,
-0.020721053704619408,
-0.03566891327500343,
0.043138809502124786,
0.030584516003727913,
-0.034091364592313766,
0.00036305992398411036,
0... |
Bryanwong/wangchanberta-ner | [] | 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:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.041994765400886536,
-0.0008451061439700425,
-0.007635938003659248,
0.048953842371702194,
0.028564898297190666,
0.021846570074558258,
-0.02462754212319851,
-0.03821646794676781,
-0.007046541199088097,
0.04820995405316353,
0.01782049424946308,
-0.008982343599200249,
0.020991703495383263,
... |
Buntan/xlm-roberta-base-finetuned-marc-en | [] | 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: cc-by-nc-nd-4.0
language:
- en
tags:
- stable-diffusion
- text-to-image
- diffusers
---
This model is named "Cinematic Diffusion". It has been trained using Stable Diffusion 1.5 to generate cinematic images. To utilize it, you must include the keyword "syberart" at the beginning of your prompt.
Th... | [
0.0007227198802866042,
-0.020280871540308,
-0.012302161194384098,
0.04985615238547325,
0.0679539293050766,
0.015161635354161263,
-0.0038723309990018606,
-0.016180038452148438,
-0.007792657241225243,
0.05715041235089302,
0.05735763534903526,
-0.005178901832550764,
0.008723655715584755,
0.04... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-ner | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 85 | 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,
0.0510595329105854,
0.01117929257452488,
0.04447409510612488,
-0.01840854622423649,
-0.002739659510552883,
-0.070090651512146,
0.08364398777484894,
0.03946809098124504,
0.013144438154995441,
0.00234610796906054,
0.04092745... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-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": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 42 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for Unit 1 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute 🦋.
## Usage
```pyth... | [
-0.013603356666862965,
-0.012169991619884968,
0.013667548075318336,
0.03415903076529503,
0.023243244737386703,
0.028177903965115547,
0.002254186198115349,
-0.003583116689696908,
-0.007747534662485123,
0.06453656405210495,
0.00011125834862468764,
-0.015368461608886719,
0.026148270815610886,
... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-pos-egy | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 16,451 | null | ---
language:
- en
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
duplicated_from: Linaqruf/anything-v3.0
---
# Anything V3
Welcome to Anything V3 - a latent diffusion model for weebs. This model is intended to produce high-quality, hig... | [
0.009547813795506954,
-0.03443821892142296,
-0.011201353743672371,
0.037739481776952744,
0.03200749680399895,
0.0006575208390131593,
-0.003819826291874051,
-0.006764960940927267,
-0.01049058884382248,
0.06678777188062668,
0.011192896403372288,
0.0012114226119592786,
0.01694193109869957,
0.... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-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": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 73 | null | ---
tags:
- FrozenLake-v1-8x8-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-8x8-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-8x8-no_slippery
type: Frozen... | [
-0.01804862730205059,
-0.018687019124627113,
-0.006601220928132534,
0.030736522749066353,
0.052848152816295624,
-0.019286764785647392,
-0.009555328637361526,
-0.012089280411601067,
-0.05768534168601036,
0.0539640411734581,
-0.002721644937992096,
-0.009789185598492622,
0.02603897638618946,
... |
CAMeL-Lab/bert-base-arabic-camelbert-da-pos-egy | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 32 | 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... | [
-0.01612410694360733,
-0.016719089820981026,
-0.004925630521029234,
0.027859335765242577,
0.051276806741952896,
-0.01675909385085106,
-0.012075473554432392,
-0.006821317132562399,
-0.05864735692739487,
0.05490309000015259,
-0.0012691105948761106,
-0.009632820263504982,
0.02690933272242546,
... |
CAMeL-Lab/bert-base-arabic-camelbert-da | [
"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... | 449 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... | [
-0.05123021453619003,
0.0061965277418494225,
-0.00700937258079648,
0.05753478780388832,
0.028734548017382622,
0.030975669622421265,
-0.003979689907282591,
-0.034208107739686966,
-0.005581888370215893,
0.05190730094909668,
0.018198391422629356,
-0.012797307223081589,
0.008412334136664867,
0... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-half | [
"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... | 16 | null |
---
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: es
datasets:
- lmqg/qg_esquad
pipeline_tag: text2text-generation
tags:
- answer extraction
widget:
- text: "<hl> En la diáspora somalí, múltiples eventos islámicos de recaudación de fondos se llevan a cabo cada año en ciudade... | [
-0.010456391610205173,
-0.03487015515565872,
0.00005588762724073604,
0.05522185191512108,
0.05032475292682648,
-0.005592173896729946,
-0.024018732830882072,
-0.0057086581364274025,
-0.06627098470926285,
0.03226838633418083,
0.019229482859373093,
0.012109293602406979,
-0.018893349915742874,
... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-pos-glf | [
"pytorch",
"tf",
"bert",
"token-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"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... | 21 | 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
... | [
-0.037462905049324036,
-0.002482887590304017,
-0.004940251354128122,
0.02605454996228218,
0.04561932012438774,
-0.021506046876311302,
-0.005236606579273939,
-0.028028417378664017,
-0.03346487507224083,
0.06647864729166031,
0.03246232494711876,
-0.0236655306071043,
0.02286098711192608,
0.00... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-quarter | [
"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... | 12 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### The-Owl-House-Diffusion Dreambooth model trained by Theodora527 with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept v... | [
-0.018741188570857048,
-0.033286936581134796,
-0.01769629865884781,
0.04428126662969589,
0.024428434669971466,
0.018218712881207466,
-0.0012109932722523808,
-0.008129958063364029,
-0.005196641199290752,
0.04128948971629143,
0.03372451290488243,
0.008525525219738483,
-0.028924010694026947,
... |
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": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 574 | 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... | [
-0.015916772186756134,
-0.019222281873226166,
-0.005904431454837322,
0.030232315883040428,
0.05083903670310974,
-0.01777978241443634,
-0.011299609206616879,
-0.008793995715677738,
-0.06042563170194626,
0.0552353598177433,
-0.0020248310174793005,
-0.008236275054514408,
0.02516563981771469,
... |
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:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.04208284988999367,
-0.0010890898993238807,
-0.007792735937982798,
0.04936949536204338,
0.02850380912423134,
0.021797554567456245,
-0.025816064327955246,
-0.03700709342956543,
-0.006349544506520033,
0.049656257033348083,
0.018048454076051712,
-0.008659886196255684,
0.020997771993279457,
... |
CBreit00/DialoGPT_small_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 | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
widget:
- '全国高校科研质量排名，清华北大浙大无缘前五。'
model-index:
- name: classification_tnews_arg
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... | [
-0.041792262345552444,
-0.021708738058805466,
-0.006831268779933453,
0.06219470873475075,
0.045359056442976,
0.027865499258041382,
-0.012631586752831936,
-0.020680611953139305,
-0.018106576055288315,
0.04928572475910187,
0.01593608409166336,
-0.008638017810881138,
0.004992923699319363,
0.0... |
CLAck/en-km | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"translation",
"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... | 12 | 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
... | [
-0.03173268586397171,
-0.0006987142260186374,
-0.0036082963924854994,
0.02820293977856636,
0.038450367748737335,
-0.021115655079483986,
-0.0014302532654255629,
-0.0339699424803257,
-0.02585943229496479,
0.06245821714401245,
0.02721206471323967,
-0.034991711378097534,
0.028143396601080894,
... |
CLTL/icf-domains | [
"pytorch",
"roberta",
"nl",
"transformers",
"license:mit",
"text-classification"
] | text-classification | {
"architectures": [
"RobertaForMultiLabelSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": nul... | 35 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: taxi_v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.48 +/- 2.71
... | [
-0.018719878047704697,
-0.01527377124875784,
-0.005944394040852785,
0.025485845282673836,
0.04472421482205391,
-0.0005379071226343513,
-0.01983482949435711,
0.008261444047093391,
-0.03724127635359764,
0.053778208792209625,
0.01868896372616291,
-0.010729348286986351,
0.013745682314038277,
0... |
CLTL/icf-levels-fac | [
"pytorch",
"roberta",
"text-classification",
"nl",
"transformers",
"license:mit"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 32 | null | ---
language: eng
license: mit
dataset: Logical Fallacy Dataset
---
# distilbert-base-fallacy-classification
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [Logical Fallacy Dataset](https://github.com/causalNLP/logical-fallacy).
## Model descrip... | [
-0.014493171125650406,
0.004582255147397518,
-0.01879667118191719,
0.05016125738620758,
0.04761775583028793,
0.018096862360835075,
-0.027124686166644096,
0.0007691543432883918,
-0.020912211388349533,
0.04219839721918106,
0.029361918568611145,
-0.030723631381988525,
0.03503074496984482,
0.0... |
CTBC/ATS | [] | 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: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### Model Dreambooth concept Ira-Olympus-v3-3600 được train bởi hr16 bằng [Shinja Zero SoTA DreamBooth_Stable_Diffusion](https://colab.research.google.com/drive/1G7qx6M_S1PDDlsWIMdbZXwdZik6sUlEh) notebook <br>
Test concept bằng [Shinja Ze... | [
-0.040515050292015076,
-0.04542657360434532,
-0.015863439068198204,
0.022290967404842377,
0.026791490614414215,
0.00767118064686656,
-0.002736175898462534,
-0.0032798524480313063,
-0.03556910157203674,
0.0431559719145298,
0.03601403906941414,
-0.0021961748134344816,
-0.01879514940083027,
0... |
CallumRai/HansardGPT2 | [
"pytorch",
"jax",
"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... | 14 | 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... | [
-0.01780948042869568,
-0.017056476324796677,
-0.006280938163399696,
0.02963109128177166,
0.051188934594392776,
-0.018055252730846405,
-0.011309321038424969,
-0.009039458818733692,
-0.058901309967041016,
0.05421223118901253,
-0.0023576803505420685,
-0.00938902236521244,
0.025331195443868637,
... |
CalvinHuang/mt5-small-finetuned-amazon-en-es | [
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"transformers",
"summarization",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | summarization | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 16 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
-0.04025764763355255,
-0.002483102958649397,
-0.00804420467466116,
0.05190884321928024,
0.027958078309893608,
0.022210581228137016,
-0.025459177792072296,
-0.03834864869713783,
-0.006107001099735498,
0.04587632417678833,
0.018252259120345116,
-0.007672600913792849,
0.01791684702038765,
0.0... |
Cameron/BERT-mdgender-convai-ternary | [
"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... | 38 | 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: 7.56 +/- 2.71... | [
-0.019661054015159607,
-0.01363420207053423,
-0.007788666989654303,
0.025873923674225807,
0.04787271469831467,
-0.0019570051226764917,
-0.01960810087621212,
0.0062886313535273075,
-0.03704611584544182,
0.05206837132573128,
0.017112312838435173,
-0.007495902478694916,
0.012256941758096218,
... |
Cameron/BERT-mdgender-wizard | [
"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... | 30 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.037242185324430466,
-0.001955152489244938,
-0.0049775876104831696,
0.025610655546188354,
0.04541448876261711,
-0.021919315680861473,
-0.0053880708292126656,
-0.028203368186950684,
-0.03318974748253822,
0.06669695675373077,
0.03246600925922394,
-0.023623675107955933,
0.022418733686208725,
... |
Cameron/BERT-rtgender-opgender-annotations | [
"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... | 33 | 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
... | [
-0.03737928718328476,
-0.0023070978932082653,
-0.004336626268923283,
0.02516838163137436,
0.045190948992967606,
-0.022110210731625557,
-0.0052519370801746845,
-0.027847012504935265,
-0.03374013677239418,
0.06650849431753159,
0.03238588199019432,
-0.023361163213849068,
0.022920722141861916,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.