modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k | embedding list |
|---|---|---|---|---|---|---|---|
Declan/FoxNews_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 3 | null | ---
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon-notyet
- animal
widget:
- text: a renaissance painting of catloxi cat wearing a crown sitting on a throne,
elegant, close-up
---
# DreamBooth model for the catloxi conce... | [
-0.026135297492146492,
-0.031711649149656296,
-0.009077323600649834,
0.03806795924901962,
0.03437386825680733,
0.020840993151068687,
-0.010746894404292107,
-0.01531969103962183,
-0.007114693522453308,
0.04872758314013481,
0.031060470268130302,
0.00004183667988399975,
-0.004880478605628014,
... |
Declan/HuffPost_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 3 | 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... | [
-0.015991846099495888,
-0.01733298972249031,
-0.006285429000854492,
0.02861405722796917,
0.050373803824186325,
-0.015904201194643974,
-0.011491086333990097,
-0.007803004235029221,
-0.05792085453867912,
0.055256437510252,
-0.0010898930486291647,
-0.00950357411056757,
0.025095216929912567,
0... |
Declan/HuffPost_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 3 | 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: 7.52 +/- 2.71
... | [
-0.018615033477544785,
-0.014577913098037243,
-0.007313829381018877,
0.02403375320136547,
0.04469141364097595,
0.0009748582378961146,
-0.01900521293282509,
0.008875339291989803,
-0.035577256232500076,
0.055902149528265,
0.01862153597176075,
-0.006995227187871933,
0.01315055601298809,
0.023... |
Declan/Reuters_model_v3 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 7 | null | ---
language:
- es
license: apache-2.0
tags:
- "national library of spain"
- "spanish"
- "bne"
- "PlanTL-GOB-ES/MLDoc"
- "text-classification"
datasets:
- "PlanTL-GOB-ES/MLDoc"
metrics:
- "f1"
model-index:
- name: roberta-base-bne-mldoc
results:
- task:
type: text-classification
dataset:
ty... | [
-0.010023935697972775,
-0.017677264288067818,
0.01081551518291235,
0.040626417845487595,
0.039999280124902725,
0.037433236837387085,
-0.014191539026796818,
-0.008267735131084919,
-0.03212595731019974,
0.035858750343322754,
0.007696089334785938,
-0.02648441679775715,
-0.027294717729091644,
... |
Declan/Reuters_model_v4 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xlsum-with-multi-news-10-epoch
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | [
-0.017809662967920303,
-0.010116608813405037,
0.0073015508241951466,
0.022902412340044975,
0.03613647073507309,
0.006192517466843128,
-0.020863259211182594,
-0.022378182038664818,
-0.033739447593688965,
0.055385615676641464,
0.018429353833198547,
-0.028769496828317642,
0.007060898933559656,
... |
Declan/Reuters_model_v8 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 3 | 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
... | [
-0.04108384996652603,
-0.01602654717862606,
-0.017209481447935104,
0.03349556401371956,
0.04966941848397255,
-0.004683104809373617,
-0.013122806325554848,
-0.025995157659053802,
-0.0319991298019886,
0.053322918713092804,
0.022415440529584885,
-0.03236137330532074,
0.017341693863272667,
0.0... |
Declan/WallStreetJournal_model_v1 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 3 | 2022-12-27T02:10:20Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned-eurosat-albumentations
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
... | [
-0.032486386597156525,
-0.00962422601878643,
-0.01292699296027422,
0.041329625993967056,
0.03223080933094025,
-0.006719022057950497,
-0.008433875627815723,
0.007420648820698261,
-0.017778508365154266,
0.04465275630354881,
0.0337541289627552,
0.0007459775079041719,
0.0024749368894845247,
0.... |
Declan/WallStreetJournal_model_v2 | [
"pytorch",
"bert",
"fill-mask",
"transformers",
"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... | 7 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.03740570321679115,
-0.0022402440663427114,
-0.005299117416143417,
0.02563650719821453,
0.04545349255204201,
-0.021548394113779068,
-0.005404547788202763,
-0.027755320072174072,
-0.03304596245288849,
0.0665728971362114,
0.03279861435294151,
-0.02361823059618473,
0.02269946224987507,
0.00... |
DeepChem/SmilesTokenizer_PubChem_1M | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 227 | null |
---
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: ja
datasets:
- lmqg/qag_jaquad
pipeline_tag: text2text-generation
tags:
- questions and answers generation
widget:
- text: "ゾフィーは貴族出身ではあったが王族出身ではなく、ハプスブルク家の皇位継承者であるフランツ・フェルディナントとの結婚は貴賤結婚となった。皇帝フランツ・ヨーゼフは、2人の間に生まれた子孫が皇位を継がないこと... | [
0.01955629698932171,
-0.012047884985804558,
-0.02729293704032898,
0.031362272799015045,
0.05084680765867233,
-0.0033761283848434687,
-0.01989704929292202,
-0.01364489458501339,
-0.04244474694132805,
0.031410884112119675,
0.011692237108945847,
0.0016619120724499226,
0.005656495224684477,
0.... |
DeepESP/gpt2-spanish-medium | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"es",
"dataset:ebooks",
"transformers",
"GPT-2",
"Spanish",
"ebooks",
"nlg",
"license:mit"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 340 | 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... | [
-0.018601244315505028,
-0.01772819273173809,
-0.007452324964106083,
0.03060969151556492,
0.05136154219508171,
-0.0187015850096941,
-0.0106361610814929,
-0.008399993181228638,
-0.058825790882110596,
0.05357694625854492,
-0.0021183802746236324,
-0.009047940373420715,
0.02505602315068245,
0.0... |
DeepESP/gpt2-spanish | [
"pytorch",
"tf",
"jax",
"gpt2",
"text-generation",
"es",
"dataset:ebooks",
"transformers",
"GPT-2",
"Spanish",
"ebooks",
"nlg",
"license:mit",
"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... | 1,463 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: taxi-frozenlake
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.52 +/... | [
-0.018800420686602592,
-0.013071753084659576,
-0.007040185388177633,
0.028166942298412323,
0.05005156621336937,
-0.011848637834191322,
-0.015786858275532722,
0.006470559164881706,
-0.046356450766325,
0.04819851368665695,
0.020764850080013275,
-0.007472342345863581,
0.015377986244857311,
0.... |
DeepPavlov/bert-base-bg-cs-pl-ru-cased | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"bg",
"cs",
"pl",
"ru",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1,614 | 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
... | [
-0.040953148156404495,
-0.01653658039867878,
-0.01824263110756874,
0.033379506319761276,
0.050272513180971146,
-0.004056152887642384,
-0.013808343559503555,
-0.02617080882191658,
-0.03165052458643913,
0.053780633956193924,
0.022606659680604935,
-0.03157603740692139,
0.01724252663552761,
0.... |
DeepPavlov/bert-base-multilingual-cased-sentence | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"multilingual",
"arxiv:1704.05426",
"arxiv:1809.05053",
"arxiv:1908.10084",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 140 | null | ---
language:
- zh
library_name: transformers
pipeline_tag: text2text-generation
---
```python
from transformers import pipeline
text_generator = pipeline("text-generation", model="svjack/T5-daliy-dialogue")
text_generator(
"你饿吗？"
)
'''
[
{
"generated_text": "是的,我快饿死了"
}
]
'''
``` | [
-0.036281466484069824,
-0.01798178255558014,
-0.0016036501619964838,
0.040021300315856934,
0.058620356023311615,
0.0476558692753315,
-0.01539062149822712,
-0.005628938786685467,
-0.03234807029366493,
0.0544743612408638,
0.05605800077319145,
-0.00472828047350049,
0.00036095624091103673,
0.0... |
DeepPavlov/distilrubert-tiny-cased-conversational-v1 | [
"pytorch",
"distilbert",
"ru",
"arxiv:2205.02340",
"transformers"
] | null | {
"architectures": null,
"model_type": "distilbert",
"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,
"n... | 9,141 | null | ---
language:
- zh
library_name: transformers
pipeline_tag: text2text-generation
---
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("svjack/T5-dialogue-choose")
model = AutoModelForSeq2SeqLM.from_pretrained("svjack/T5-dialogue-choose")
text = '''
... | [
-0.03260377421975136,
-0.0324053131043911,
-0.005275642033666372,
0.046361252665519714,
0.04892945662140846,
0.029920706525444984,
-0.027894409373402596,
-0.005371858831495047,
-0.032410167157649994,
0.046439845114946365,
0.036033421754837036,
0.0022147460840642452,
0.004050904419273138,
0... |
DeepPavlov/marianmt-tatoeba-ruen | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"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... | 30 | null | ---
tags:
- autotrain
- text-classification
language:
- zh
widget:
- text: "I love AutoTrain 🤗"
datasets:
- paulkm/autotrain-data-lottery_prod
co2_eq_emissions:
emissions: 11.554897545219454
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 2626879382
- CO2 Emissions (in grams):... | [
-0.03022889606654644,
-0.026747005060315132,
-0.003234511474147439,
0.03864589333534241,
0.04069788381457329,
0.033115532249212265,
-0.028520498424768448,
-0.014282574877142906,
-0.04238433390855789,
0.07850474119186401,
0.023362567648291588,
0.02953355200588703,
-0.003933101426810026,
0.0... |
DeepPavlov/roberta-large-winogrande | [
"pytorch",
"roberta",
"text-classification",
"en",
"dataset:winogrande",
"arxiv:1907.11692",
"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,
"... | 348 | 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... | [
-0.03936174511909485,
-0.0005573565140366554,
-0.007212432567030191,
0.04944112151861191,
0.029280688613653183,
0.022458767518401146,
-0.026797974482178688,
-0.03783866763114929,
-0.004304884932935238,
0.04971320554614067,
0.017333539202809334,
-0.009855522774159908,
0.019900424405932426,
... |
DeepPavlov/rubert-base-cased-conversational | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"transformers",
"has_space"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 17,362 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-Regression-Edmunds_Car_Reviews-all_car_brands
results: []
language:
- en
---
# distilbert-base-uncased-Regression-Edmunds_Car_Reviews-all_car_brands
This model is a fine-tuned version of [distilbert-base-uncased](htt... | [
-0.03386625647544861,
0.022744491696357727,
-0.006643859203904867,
0.027992654591798782,
0.033409811556339264,
0.026558075100183487,
-0.01332768052816391,
-0.007707804441452026,
-0.04356243088841438,
0.045462049543857574,
0.04838469997048378,
-0.03911050409078598,
0.018421093001961708,
0.0... |
DeepPavlov/rubert-base-cased-sentence | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"arxiv:1508.05326",
"arxiv:1809.05053",
"arxiv:1908.10084",
"transformers",
"has_space"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 46,991 | null |
---
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: fr
datasets:
- lmqg/qg_frquad
pipeline_tag: text2text-generation
tags:
- answer extraction
widget:
- text: "Pourtant, la strophe spensérienne, utilisée cinq fois avant que ne commence le chœur, constitue en soi un vecteur don... | [
-0.027209952473640442,
-0.01576128788292408,
0.005285277497023344,
0.04155576974153519,
0.01684609428048134,
0.012034209445118904,
-0.016667388379573822,
-0.01395178958773613,
-0.022509712725877762,
0.03194471076130867,
0.03943109139800072,
0.008399787358939648,
-0.0024434004444628954,
0.0... |
DeepPavlov/rubert-base-cased | [
"pytorch",
"jax",
"bert",
"feature-extraction",
"ru",
"arxiv:1905.07213",
"transformers",
"has_space"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 148,127 | 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
... | [
-0.037025004625320435,
-0.0027558046858757734,
-0.0046390327624976635,
0.02554072067141533,
0.045490097254514694,
-0.021362893283367157,
-0.005090715363621712,
-0.02849077433347702,
-0.03367365151643753,
0.06669542193412781,
0.03284242004156113,
-0.023597748950123787,
0.02263927273452282,
... |
DeepPavlov/xlm-roberta-large-en-ru-mnli | [
"pytorch",
"xlm-roberta",
"text-classification",
"en",
"ru",
"dataset:glue",
"dataset:mnli",
"transformers",
"xlm-roberta-large",
"xlm-roberta-large-en-ru",
"xlm-roberta-large-en-ru-mnli",
"has_space"
] | text-classification | {
"architectures": [
"XLMRobertaForSequenceClassification"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 227 | null | ---
license: creativeml-openrail-m
---
A free iOS and MacOS app for you to generate AI arts on the go: https://apps.apple.com/us/app/%E7%94%BB%E5%83%8F%E7%94%9F%E6%88%90ai-%E3%83%AD%E3%83%BC%E3%82%AB%E3%83%AB-stable-diffusion/id1658459595
This is made possible by using the newest Apple Core ML tool and the pipeline a... | [
-0.03743543103337288,
-0.013999227434396744,
-0.009384148754179478,
0.040725477039813995,
0.030021125450730324,
0.008157516829669476,
-0.01948598399758339,
-0.016528606414794922,
-0.008808797225356102,
0.04507118836045265,
0.012677936814725399,
0.00997120887041092,
0.007469929754734039,
0.... |
DeepPavlov/xlm-roberta-large-en-ru | [
"pytorch",
"xlm-roberta",
"feature-extraction",
"en",
"ru",
"transformers"
] | feature-extraction | {
"architectures": [
"XLMRobertaModel"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngr... | 190 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | [
-0.02543695457279682,
0.026894472539424896,
-0.019763195887207985,
0.0365833044052124,
0.04308154806494713,
0.03524484857916832,
-0.017417024821043015,
-0.03256652504205704,
-0.029866257682442665,
0.05998843535780907,
0.022348051890730858,
-0.03730810433626175,
0.03414764627814293,
0.04560... |
DeltaHub/lora_t5-base_mrpc | [
"pytorch",
"transformers"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
license: mit
tags:
- 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... | [
-0.02069842256605625,
-0.012683401815593243,
0.011778460815548897,
0.030343543738126755,
0.02421742118895054,
0.02470877580344677,
0.004736130125820637,
-0.007820963859558105,
-0.006189741659909487,
0.06323995441198349,
-0.0004976191557943821,
-0.01638803817331791,
0.02587961032986641,
0.0... |
DemangeJeremy/4-sentiments-with-flaubert | [
"pytorch",
"flaubert",
"text-classification",
"fr",
"transformers",
"sentiments",
"french",
"flaubert-large"
] | text-classification | {
"architectures": [
"FlaubertForSequenceClassification"
],
"model_type": "flaubert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 226 | null | ---
license: openrail
---
# Oud (عود) Unconditional Diffusion
The Oud is one of the most foundational instruments to all of Arab music. It can be heard in nearly every song, whether the subgenre is rooted in pop or classical music.
Its distinguishing sound can be picked out of a crowd of string instruments with little... | [
-0.028838900849223137,
-0.0017317713936790824,
-0.03233505040407181,
0.01909123919904232,
0.015303188003599644,
0.019568391144275665,
0.012924378737807274,
0.0022191551979631186,
-0.008739443495869637,
0.06044423207640648,
0.003232455113902688,
-0.00539916567504406,
0.002854173304513097,
0... |
Deniskin/essays_small_2000 | [] | 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
---
## / 7th Layer /
<img src="https://i.imgur.com/MjnczlB.png" width="1700" height="">
# (Important Notice:1.6)
default CFG Scale : 7 ±5
default Sampler : DPM++ 2M Karras
default Steps : 25
Negative prompt : (worst quality:1.4), (low quality:1.4) , (monochrome:1.1),
# Don't write a lot of "N... | [
-0.0008306134841404855,
-0.0402282290160656,
-0.005255300551652908,
0.034301772713661194,
0.04311564937233925,
0.02015984058380127,
-0.006321720313280821,
-0.0071741933934390545,
-0.0503702238202095,
0.05035242810845375,
0.024287398904561996,
-0.019535662606358528,
-0.002109298249706626,
0... |
DeskDown/MarianMixFT_en-ms | [
"pytorch",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"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... | 5 | null | # Gender-and-Age-Detection <img alt="GitHub" src="https://img.shields.io/github/license/smahesh29/Gender-and-Age-Detection">
<h2>Objective :</h2>
<p>To build a gender and age detector that can approximately guess the gender and age of the person (face) in a picture or through webcam.</p>
<h2>About the Project :</h... | [
-0.04110877588391304,
-0.007342146709561348,
0.0031447953078895807,
0.018656939268112183,
0.059848904609680176,
-0.008317256346344948,
-0.0048438929952681065,
0.00522690499201417,
-0.017860693857073784,
0.06979623436927795,
0.029291464015841484,
0.00466027669608593,
0.024805989116430283,
0... |
DeskDown/MarianMix_en-ja-10 | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"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... | 1 | 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
... | [
-0.03727676346898079,
-0.0027829559985548258,
-0.0050790379755198956,
0.025466937571763992,
0.04562101513147354,
-0.02149798721075058,
-0.005241859704256058,
-0.02796006388962269,
-0.03303135558962822,
0.0665011778473854,
0.03254558518528938,
-0.023843681439757347,
0.0223515834659338,
0.00... |
DeskDown/MarianMix_en-zh-10 | [
"pytorch",
"tensorboard",
"marian",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"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... | 3 | null | ---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, th... | [
-0.022855566814541817,
-0.0025276578962802887,
0.010108867660164833,
0.027436384931206703,
0.03879762440919876,
-0.002415851689875126,
-0.026902470737695694,
-0.005715782754123211,
-0.04525378718972206,
0.05318262428045273,
0.024196570739150047,
-0.023867638781666756,
0.010184905491769314,
... |
Dhito/am | [] | 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 | Access to model Faisalrahi/pytorch_model.bin is restricted and you are not in the authorized list. Visit https://huggingface.co/Faisalrahi/pytorch_model.bin to ask for access. | [
-0.04039602726697922,
-0.012230115942656994,
0.008116278797388077,
0.03651158884167671,
0.03217321261763573,
0.011481917463243008,
0.022301070392131805,
0.008279620669782162,
-0.04814562574028969,
0.050791651010513306,
0.07139952480792999,
0.01458137296140194,
0.00007215777441160753,
0.054... |
Dhritam/Zova-bot | [] | 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
... | [
-0.03751325607299805,
-0.003034124383702874,
-0.004869374912232161,
0.025922134518623352,
0.045573703944683075,
-0.021288497373461723,
-0.00529321888461709,
-0.028447963297367096,
-0.033398084342479706,
0.06641579419374466,
0.032424889504909515,
-0.023471709340810776,
0.022777855396270752,
... |
Dhruva/Interstellar | [] | 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
... | [
-0.04167098551988602,
-0.017599917948246002,
-0.01764329895377159,
0.03349776566028595,
0.049495793879032135,
-0.005099902395159006,
-0.013712914660573006,
-0.02474464848637581,
-0.03103642165660858,
0.05358891189098358,
0.021703464910387993,
-0.031092233955860138,
0.017752552404999733,
0.... |
Dongmin/testmodel | [
"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... | 11 | null | ---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-ner-invoiceSenderRecipient-all-inv-26-12
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proo... | [
-0.013814100064337254,
0.0025910637341439724,
-0.022349247708916664,
0.026459410786628723,
0.04422084614634514,
0.023503320291638374,
-0.028634140267968178,
-0.028701920062303543,
-0.04171595722436905,
0.06010229513049126,
0.04365954548120499,
-0.038744859397411346,
0.0032046029809862375,
... |
Doogie/Waynehills-KE-T5-doogie | [] | 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
... | [
-0.037421420216560364,
-0.002098340541124344,
-0.0051644896157085896,
0.02572437934577465,
0.04543490335345268,
-0.021703241392970085,
-0.0055541228502988815,
-0.028162678703665733,
-0.03306446596980095,
0.06648775190114975,
0.03251371160149574,
-0.02429754100739956,
0.022640982642769814,
... |
Waynehillsdev/Waynehills-STT-doogie-server | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | 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... | 61 | 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... | [
-0.017364613711833954,
-0.01953122578561306,
-0.005812957417219877,
0.029729371890425682,
0.05249745398759842,
-0.0188820231705904,
-0.011377224698662758,
-0.008104250766336918,
-0.05848182737827301,
0.05408143997192383,
-0.0018041683360934258,
-0.008244326338171959,
0.025930700823664665,
... |
Doohae/q_encoder | [
"pytorch"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 3 | null | ---
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
... | [
-0.037538591772317886,
-0.0027629025280475616,
-0.0046407985500991344,
0.02563130110502243,
0.045115936547517776,
-0.02140306681394577,
-0.005601195152848959,
-0.027461277320981026,
-0.03332867845892906,
0.066551573574543,
0.03198423981666565,
-0.023633817210793495,
0.023301104083657265,
0... |
Doxophobia/DialoGPT-medium-celeste | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
license: apache-2.0
---
## 简介 Brief Introduction
1.1亿参数的ernie-1.0模型
## 模型信息 Released Model Information
当前发布的pytorch版本ERNIE-base，是从huggingface下载并修复vocab和config对不上的问题。
This released pytorch model is downloading from huggingface, then fixed the vocab and config not matching issue.
## 使用 Usage
```python
from transfo... | [
-0.04916904866695404,
0.010308762080967426,
-0.0025853354018181562,
0.03687402606010437,
0.03093942441046238,
0.01999935321509838,
-0.004442867822945118,
-0.026318520307540894,
-0.02645503543317318,
0.05120297521352768,
0.015455753542482853,
-0.01313873939216137,
0.038586314767599106,
0.03... |
DoyyingFace/bert-asian-hate-tweets-asian-clean-with-unclean-valid | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 29 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- timit_asr
model-index:
- name: wav2vec2-base-timit-demo-colab
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 thi... | [
-0.019761033356189728,
-0.004931440111249685,
-0.015939798206090927,
0.02356914058327675,
0.03911997005343437,
0.01491507701575756,
0.007493389304727316,
-0.004115424118936062,
-0.026774832978844643,
0.0400531142950058,
0.025647614151239395,
-0.02309095486998558,
-0.004724451340734959,
0.0... |
DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-25 | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 30 | 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... |
albert-xlarge-v2 | [
"pytorch",
"tf",
"albert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1909.11942",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"AlbertForMaskedLM"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_... | 2,973 | 2022-12-27T10:14:22Z | ---
library_name: stable-baselines3
tags:
- CartPole-v1
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:... | [
-0.0409025177359581,
-0.010296810418367386,
-0.012502243742346764,
0.025319568812847137,
0.03938334807753563,
-0.004052293486893177,
-0.008364852517843246,
-0.012608307413756847,
-0.040434580296278,
0.07213384658098221,
0.009451132267713547,
-0.017083492130041122,
0.01972317509353161,
0.00... |
bert-base-cased-finetuned-mrpc | [
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | 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... | 11,644 | 2022-12-27T10:20:45Z | ---
license: mit
---
## Sentiment Analysis API
This is the deployment part of the project.
### Training:
Run the Google Colab notebook (Runtime = "GPU") (https://colab.research.google.com/drive/1EuF5FDl1X8VnuOO5RxzmM0c9TbtQrVm9?usp=sharing)
### Fine Tuning
1) Increasing #epochs
2) Increasing BATCH_SIZE to 32
3) Cha... | [
-0.030939588323235512,
-0.019894612953066826,
-0.02140847034752369,
0.039866749197244644,
0.057949841022491455,
0.029650038108229637,
0.012714127078652382,
-0.014754519797861576,
-0.042627446353435516,
0.04968033730983734,
0.042360883206129074,
0.012082534842193127,
0.027728814631700516,
0... |
bert-base-cased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"exbert",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"BertForMaskedLM"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8,621,271 | 2022-12-27T10:22:47Z |
---
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... | [
-0.04145364835858345,
-0.0013512499863281846,
-0.007690192200243473,
0.04905758053064346,
0.028797026723623276,
0.023366956040263176,
-0.02554941177368164,
-0.03592652827501297,
-0.006417629308998585,
0.049800436943769455,
0.01898927427828312,
-0.010241620242595673,
0.02005133405327797,
0.... |
bert-base-chinese | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"zh",
"arxiv:1810.04805",
"transformers",
"autotrain_compatible",
"has_space"
] | 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... | 3,377,486 | 2022-12-27T10:29:09Z | ---
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... | [
-0.018549766391515732,
-0.017596585676074028,
-0.005671793129295111,
0.029611915349960327,
0.051125045865774155,
-0.017573630437254906,
-0.010692483745515347,
-0.008362062275409698,
-0.05925106257200241,
0.0543241985142231,
-0.0024884396698325872,
-0.009475269354879856,
0.0253102108836174,
... |
bert-base-german-dbmdz-cased | [
"pytorch",
"jax",
"bert",
"fill-mask",
"de",
"transformers",
"license:mit",
"autotrain_compatible",
"has_space"
] | 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... | 1,814 | null | Access to model S-Sajad-Hosseini/q-Taxi-v3 is restricted and you are not in the authorized list. Visit https://huggingface.co/S-Sajad-Hosseini/q-Taxi-v3 to ask for access. | [
-0.02478606440126896,
-0.017838453873991966,
-0.008643330074846745,
0.02452671527862549,
0.03703474625945091,
0.004483620170503855,
-0.01274255570024252,
0.025008060038089752,
-0.051914479583501816,
0.0245815496891737,
0.037163421511650085,
-0.003218195866793394,
0.02385479025542736,
0.043... |
bert-base-multilingual-uncased | [
"pytorch",
"tf",
"jax",
"safetensors",
"bert",
"fill-mask",
"multilingual",
"af",
"sq",
"ar",
"an",
"hy",
"ast",
"az",
"ba",
"eu",
"bar",
"be",
"bn",
"inc",
"bs",
"br",
"bg",
"my",
"ca",
"ceb",
"ce",
"zh",
"cv",
"hr",
"cs",
"da",
"nl",
"en",
"et",
... | 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... | 328,585 | 2022-12-27T10:43:25Z | ---
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
... | [
-0.02006547711789608,
-0.0156838558614254,
-0.006675960961729288,
0.02568393014371395,
0.0468505434691906,
0.00020118345855735242,
-0.01870962232351303,
0.007854919880628586,
-0.03750074282288551,
0.05474585294723511,
0.018754784017801285,
-0.007461645640432835,
0.012806537561118603,
0.024... |
bert-large-cased-whole-word-masking-finetuned-squad | [
"pytorch",
"tf",
"jax",
"rust",
"safetensors",
"bert",
"question-answering",
"en",
"dataset:bookcorpus",
"dataset:wikipedia",
"arxiv:1810.04805",
"transformers",
"license:apache-2.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"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_n... | 8,214 | 2022-12-27T10:46:48Z | ---
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... | [
-0.014350632205605507,
-0.019168119877576828,
-0.006313770078122616,
0.03662419691681862,
0.04949704185128212,
-0.016398541629314423,
-0.01465722918510437,
-0.010987512767314911,
-0.0617029182612896,
0.05899501591920853,
-0.005154496058821678,
-0.012166780419647694,
0.021255891770124435,
0... |
1n3skh/idk | [] | 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
... | [
-0.040885716676712036,
-0.01684420183300972,
-0.017097704112529755,
0.03403623029589653,
0.05110878497362137,
-0.005153030157089233,
-0.013574058189988136,
-0.02598056197166443,
-0.032900337129831314,
0.053649481385946274,
0.022808218374848366,
-0.03186604008078575,
0.016318265348672867,
0... |
Ab2021/bookst5 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-12-27T20:56:20Z | ---
tags:
- conversational
---
# Black Doom DialoGPT Model | [
-0.04862667992711067,
0.0290484931319952,
0.006447256542742252,
0.018328411504626274,
0.032456330955028534,
0.015099097974598408,
0.0055491081438958645,
0.0349966436624527,
-0.00970492698252201,
0.019084367901086807,
0.05710623040795326,
-0.01520512718707323,
0.002735836897045374,
0.035217... |
AdapterHub/bert-base-uncased-pf-comqa | [
"bert",
"en",
"dataset:com_qa",
"arxiv:2104.08247",
"adapter-transformers",
"question-answering"
] | question-answering | {
"architectures": null,
"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": null,
"num_bea... | 0 | null | ---
language:
- unk
tags:
- autotrain
- summarization
datasets:
- ell-hol/autotrain-data-test-orangesum
widget:
- text: I love AutoTrain 🤗
co2_eq_emissions:
emissions: 675.7789931017469
model-index:
- name: ell-hol/mT5-OrangeSum
results:
- task:
type: summarization
name: Summarization
dataset:
... | [
-0.00820069294422865,
-0.03769746422767639,
-0.0055643366649746895,
0.04096798226237297,
0.04606005176901817,
0.015480639412999153,
-0.01575341261923313,
-0.02157539874315262,
-0.05577274039387703,
0.07245703786611557,
0.011804668232798576,
0.02696993388235569,
0.021216806024312973,
0.0280... |
AdapterHub/roberta-base-pf-conll2000 | [
"roberta",
"en",
"dataset:conll2000",
"arxiv:2104.08247",
"adapter-transformers",
"token-classification",
"adapterhub:chunk/conll2000"
] | token-classification | {
"architectures": null,
"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_ngram_size": null,
"num_... | 3 | null | ---
language:
- "zh"
tags:
- "chinese"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
---
# deberta-base-chinese-ud-goeswith
## Model Description
This is a DeBERTa(V2) model pre-trained on Chinese Wikipedia tex... | [
-0.032296523451805115,
-0.029744276776909828,
-0.015850434079766273,
0.04088093712925911,
0.014710783958435059,
0.04704402759671211,
-0.016400320455431938,
-0.011944836936891079,
-0.029023731127381325,
0.056812211871147156,
0.0001589755993336439,
-0.0043382784351706505,
0.021681461483240128,... |
Aimendo/Triage | [] | 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... | [
-0.04085293412208557,
-0.001059750560671091,
-0.008496969006955624,
0.049169015139341354,
0.02960599772632122,
0.02166340872645378,
-0.025374773889780045,
-0.036969833076000214,
-0.005710117518901825,
0.04942113161087036,
0.01886780373752117,
-0.010478260926902294,
0.020490262657403946,
0.... |
Ajteks/Chatbot | [] | 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:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-course
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metr... | [
-0.007896061055362225,
0.006768930237740278,
-0.016375500708818436,
0.01604905165731907,
0.05803496390581131,
-0.02990930899977684,
0.007953100837767124,
-0.034302547574043274,
-0.027074992656707764,
0.06648487597703934,
0.02679162286221981,
-0.028143765404820442,
-0.0019673393107950687,
0... |
Akaramhuggingface/News | [] | 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
tags:
- stable-diffusion
- text-to-image
- image-to-image
- diffusers
license: creativeml-openrail-m
inference: true
---
**Big update DucHaitenAIart_v3.1**
*Big update of DucHaitenAIart, v3.1 is able to receive more diverse, more detailed prompts with gorgeous colors and more realistic shadows. Th... | [
0.014103604480624199,
-0.03245829418301582,
-0.0033172278199344873,
0.03613044321537018,
0.04835476726293564,
0.01268258597701788,
0.004665549844503403,
-0.029505236074328423,
-0.021367160603404045,
0.04374004900455475,
0.015391803346574306,
0.006946230307221413,
0.004777449183166027,
0.05... |
Akari/albert-base-v2-finetuned-squad | [
"pytorch",
"tensorboard",
"albert",
"question-answering",
"dataset:squad_v2",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"AlbertForQuestionAnswering"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 13 | 2022-12-28T10:38:19Z | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: QRDQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.03935336694121361,
-0.017784547060728073,
-0.024510078132152557,
0.032063502818346024,
0.050236593931913376,
-0.002335460390895605,
-0.010525685735046864,
-0.024250157177448273,
-0.033928822726011276,
0.05436081811785698,
0.022378282621502876,
-0.034240663051605225,
0.01841645874083042,
... |
Akash7897/bert-base-cased-wikitext2 | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"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... | 8 | null | # **roberta-base model is fine tuned on Airline Passenger Complaint Dataset.**
- model can be used to determine the sentiment of the statement
| [
-0.035384710878133774,
-0.007309277076274157,
-0.008122848346829414,
0.06040743738412857,
0.03704754635691643,
0.06334817409515381,
-0.002279553096741438,
0.015605947934091091,
-0.024233803153038025,
0.042636312544345856,
0.050287846475839615,
-0.041696544736623764,
0.04283349588513374,
0.... |
Akash7897/distilbert-base-uncased-finetuned-cola | [
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index"
] | text-classification | {
"architectures": [
"DistilBertForSequenceClassification"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 31 | 2022-12-28T10:42:35Z | ---
inference: true
language:
- en
tags:
- stable-diffusion
- text-to-image
- embedding
license: wtfpl
---
# rr_inferno embedding - SD 2.1
## Exemple of Prompt
"Portrait of a rr_inferno skull skeleton, made of lava, fire, giant, concept art, splash art, global lightning, artwork of a phoenix, nine tails, fie... | [
-0.004742712713778019,
-0.030834686011075974,
-0.009799132123589516,
0.0405396930873394,
0.05678345263004303,
-0.005684959702193737,
0.008567231707274914,
-0.03489059954881668,
-0.007077938411384821,
0.042612750083208084,
0.032377712428569794,
-0.02652374468743801,
-0.025211935862898827,
0... |
Akashpb13/Swahili_xlsr | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"sw",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"model_for_talk",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"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... | 10 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### rbto3v2 Dreambooth model trained by rudzinskimaciej with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111 Col... | [
-0.02673293836414814,
-0.022944534197449684,
-0.033529795706272125,
0.03187791630625725,
0.0251975916326046,
0.024055829271674156,
-0.007014530710875988,
-0.007014179602265358,
-0.013742520473897457,
0.030445896089076996,
0.04148091375827789,
0.012677589431405067,
-0.02092578262090683,
0.0... |
Akashpb13/xlsr_kurmanji_kurdish | [
"pytorch",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"kmr",
"ku",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-... | 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... | 10 | null | ---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- ell-hol/autotrain-data-mt5-dialogsum
co2_eq_emissions:
emissions: 248.06396898781733
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 2644579647
- CO2 Emissions (in grams): 248.0640
... | [
-0.025784742087125778,
-0.01330334972590208,
0.010983241721987724,
0.027573740109801292,
0.030690213665366173,
0.01855795457959175,
-0.036945704370737076,
-0.028454599902033806,
-0.04525028169155121,
0.07686229795217514,
0.01980237290263176,
0.020228588953614235,
0.012429038994014263,
0.03... |
AkshaySg/GrammarCorrection | [] | 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
... | [
-0.03693089634180069,
-0.0025671678595244884,
-0.005006636492908001,
0.025606617331504822,
0.04527363181114197,
-0.021530477330088615,
-0.005054830107837915,
-0.028333554044365883,
-0.03340045362710953,
0.06654062122106552,
0.032650940120220184,
-0.023854820057749748,
0.022763192653656006,
... |
AkshaySg/LanguageIdentification | [
"multilingual",
"dataset:VoxLingua107",
"LID",
"spoken language recognition",
"license:apache-2.0"
] | 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
- wildcard
widget:
- text: a pkblz ball in the middle of a miniature jungle
- text: a photo of a spectral ornate pkblz ball, trending on artstation, realistic
- text: a color... | [
-0.03083660453557968,
-0.019982971251010895,
-0.022236909717321396,
0.03025396168231964,
0.03266742825508118,
0.011611607857048512,
0.006591762416064739,
-0.00016858501476235688,
0.0022101548966020346,
0.04450278729200363,
0.032875217497348785,
0.00691238883882761,
-0.028730448335409164,
0... |
Aleksandar/electra-srb-oscar | [
"pytorch",
"electra",
"fill-mask",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"ElectraForMaskedLM"
],
"model_type": "electra",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
... | [
-0.005804345011711121,
0.0021025987807661295,
-0.03008483164012432,
0.040711238980293274,
0.05357011780142784,
0.012626457028090954,
-0.03180469200015068,
-0.026494881138205528,
-0.027334703132510185,
0.05428934469819069,
0.004355565179139376,
-0.014123511500656605,
0.012798892334103584,
0... |
Ana1315/ana | [] | 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... | [
-0.022796712815761566,
-0.013146143406629562,
0.011902169324457645,
0.030521783977746964,
0.022683685645461082,
0.02389172464609146,
0.005067888181656599,
-0.006979141850024462,
-0.005910850595682859,
0.06221375614404678,
-0.0009392739157192409,
-0.015072447247803211,
0.024574479088187218,
... |
AnonARR/qqp-bert | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 38 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### wolde_eyu_5120512 Dreambooth model trained by Eyuel with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept via A1111 Col... | [
-0.041807517409324646,
-0.006620767526328564,
-0.023875651881098747,
0.03188259154558182,
0.03430654853582382,
0.01694292388856411,
0.004582802299410105,
0.002825439441949129,
-0.014074507169425488,
0.04031207039952278,
0.03748493269085884,
0.003960661590099335,
-0.03168211504817009,
0.016... |
AnonymousSub/AR_EManuals-BERT | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 5 | 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
... | [
-0.03733944520354271,
-0.0023364610970020294,
-0.005160133820027113,
0.02546919323503971,
0.04550693556666374,
-0.021755816414952278,
-0.005507322493940592,
-0.02798042632639408,
-0.033116720616817474,
0.06666384637355804,
0.03239867836236954,
-0.023494964465498924,
0.022529220208525658,
0... |
AnonymousSub/AR_cline | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 2 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | [
-0.022345535457134247,
0.012365269474685192,
-0.028722422197461128,
0.03814024478197098,
0.05548494681715965,
0.02869417890906334,
-0.015597812831401825,
-0.028113724663853645,
-0.03897210955619812,
0.059581268578767776,
0.02961917221546173,
-0.043635983020067215,
0.028056776151061058,
0.0... |
AnonymousSub/AR_rule_based_roberta_only_classfn_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 2 | null | ---
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- food
widget:
- text: a photo of jairzza pizza in the Acropolis
---
# DreamBooth model for the jairzza concept trained by jairNeto on the jairNeto/pizza dataset.
This is a... | [
-0.01814194768667221,
-0.023878011852502823,
-0.008314045146107674,
0.033607762306928635,
0.018926823511719704,
-0.0007016185554675758,
0.010971241630613804,
0.02167642116546631,
-0.007239149417728186,
0.044893331825733185,
0.04065050557255745,
0.0020424067042768,
-0.01573828235268593,
0.0... |
AnonymousSub/AR_rule_based_roberta_twostagequadruplet_hier_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 4 | 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
... | [
-0.03786136582493782,
-0.017817413434386253,
-0.01790112629532814,
0.030078744515776634,
0.05204463750123978,
-0.008434578776359558,
-0.009080993011593819,
-0.029703550040721893,
-0.037298575043678284,
0.05805137753486633,
0.024974588304758072,
-0.028065012767910957,
0.013265613466501236,
... |
AnonymousSub/AR_rule_based_roberta_twostagetriplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 6 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-all
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment.... | [
-0.04243723675608635,
-0.010143929161131382,
0.0036093899980187416,
0.0330071747303009,
0.02294422872364521,
0.024204792454838753,
-0.017378559336066246,
-0.0038780728355050087,
-0.028216926380991936,
0.04835370555520058,
0.025268083438277245,
-0.04956405982375145,
0.023170411586761475,
0.... |
AnonymousSub/AR_rule_based_roberta_twostagetriplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 2 | 2022-12-29T00:12:23Z | ---
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
... | [
-0.037627652287483215,
-0.0028025396168231964,
-0.005026584025472403,
0.02493308298289776,
0.045291781425476074,
-0.02144659496843815,
-0.005586650688201189,
-0.02750970795750618,
-0.03398004546761513,
0.06625524163246155,
0.03227541968226433,
-0.023011071607470512,
0.02291244827210903,
0.... |
AnonymousSub/AR_rule_based_twostage_quadruplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | 2022-12-29T00:25:11Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-en-es
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. ... | [
-0.01408473215997219,
-0.005537268705666065,
0.008382493630051613,
0.023884635418653488,
0.037981413304805756,
0.002705381950363517,
-0.028902726247906685,
-0.01088443212211132,
-0.04080779105424881,
0.04906890541315079,
0.01696285791695118,
-0.02968704327940941,
0.001528941560536623,
0.03... |
AnonymousSub/AR_rule_based_twostagequadruplet_hier_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 2 | 2022-12-29T00:35:01Z | ---
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
... | [
-0.03861193358898163,
-0.0027777841314673424,
-0.0030144713819026947,
0.026165472343564034,
0.04295424744486809,
-0.019819628447294235,
-0.006855051964521408,
-0.02790718898177147,
-0.03369360417127609,
0.06856470555067062,
0.03455609828233719,
-0.021119019016623497,
0.021399233490228653,
... |
AnonymousSub/AR_rule_based_twostagetriplet_hier_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 6 | 2022-12-29T00:43:36Z | ---
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... | [
-0.021767986938357353,
-0.014039347879588604,
0.01105746440589428,
0.030952123925089836,
0.023363657295703888,
0.024191725999116898,
0.005257791839540005,
-0.007456968538463116,
-0.006788077298551798,
0.062419116497039795,
-0.0012949655065312982,
-0.014727160334587097,
0.024600492790341377,
... |
AnonymousSub/AR_specter | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 2 | 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: 701.50 +/- 210.88
name: mean_reward
task:
type: reinforcement-learning
... | [
-0.039231620728969574,
-0.015630850568413734,
-0.01806827448308468,
0.035853590816259384,
0.05066926032304764,
-0.0036687690299004316,
-0.013711545616388321,
-0.026111727580428123,
-0.033087391406297684,
0.05296339839696884,
0.021730445325374603,
-0.032295312732458115,
0.018084116280078888,
... |
AnonymousSub/EManuals_BERT_copy | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 2 | 2022-12-29T01:05:43Z | ---
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- wildcard
widget:
- text: a photo of ramrick character as a pickle
---
# DreamBooth model for the ramrick concept trained by Kayvane on the Kayvane/dreambooth-hackathon-ric... | [
-0.005345003679394722,
-0.0008259138558059931,
-0.014000418595969677,
0.03847059980034828,
0.032337065786123276,
-0.00012073902325937524,
0.009348317980766296,
0.0003150247212033719,
-0.008933180011808872,
0.05638279393315315,
0.046756792813539505,
0.002921720966696739,
-0.01204449962824583,... |
AnonymousSub/SR_EManuals-BERT | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 6 | 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... | [
-0.022054271772503853,
-0.014038673602044582,
0.0111467856913805,
0.030763138085603714,
0.022791575640439987,
0.024274246767163277,
0.0051799737848341465,
-0.00693008815869689,
-0.006997681688517332,
0.06271945685148239,
-0.0018961640307679772,
-0.015209232456982136,
0.02457086555659771,
0... |
AnonymousSub/SR_EManuals-RoBERTa | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 1 | 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
... | [
-0.03722216188907623,
-0.002690491732209921,
-0.005036307033151388,
0.02569645456969738,
0.04550130292773247,
-0.02141827531158924,
-0.005641411989927292,
-0.027445977553725243,
-0.032771773636341095,
0.06663798540830612,
0.03220166638493538,
-0.023359129205346107,
0.023207195103168488,
0.... |
AnonymousSub/SR_SDR_HF_model_base | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 1 | 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... | [
-0.04075843095779419,
-0.0026403290685266256,
-0.007785375230014324,
0.04909138008952141,
0.028407206758856773,
0.02227483130991459,
-0.02554876171052456,
-0.03628526255488396,
-0.006351032294332981,
0.04886719211935997,
0.0178871750831604,
-0.009347395971417427,
0.01986262947320938,
0.031... |
AnonymousSub/SR_bert-base-uncased | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 3 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: t5-small-finetuned-en-to-es
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... | [
-0.02144121751189232,
0.007591621484607458,
0.009812888689339161,
0.02541506662964821,
0.030359743162989616,
-0.0038392823189496994,
-0.020862465724349022,
-0.0040822867304086685,
-0.03537322208285332,
0.05034613609313965,
0.013646259903907776,
-0.02312314137816429,
-0.0014165632892400026,
... |
AnonymousSub/SR_rule_based_hier_quadruplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null | ---
tags:
- generated_from_keras_callback
model-index:
- name: 001_M-BERT-claim-classifier
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. -->
# この「クレーム判別」モデルの使い方
このモデルは、... | [
-0.043647222220897675,
-0.01793183572590351,
-0.0020710041280835867,
0.01519422885030508,
0.02046911232173443,
0.02468453347682953,
-0.0004378501616884023,
-0.004928842652589083,
-0.015510322526097298,
0.053339868783950806,
0.05167161300778389,
-0.0008993990486487746,
0.01084765326231718,
... |
AnonymousSub/SR_rule_based_only_classfn_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | [
-0.023463133722543716,
0.012784593738615513,
-0.02857070416212082,
0.038398195058107376,
0.055083490908145905,
0.029102003201842308,
-0.017235714942216873,
-0.028386471793055534,
-0.03892533853650093,
0.05876348540186882,
0.0297151580452919,
-0.0440945103764534,
0.02808726206421852,
0.0442... |
AnonymousSub/SR_rule_based_only_classfn_twostage_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 2 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- opus_books
metrics:
- bleu
model-index:
- name: my_awesome_opus_books_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus_books
type: opus_books
config:... | [
-0.010191625915467739,
-0.01092604175209999,
0.012582201510667801,
0.04285881668329239,
0.005703280679881573,
-0.002315796446055174,
-0.014243103563785553,
-0.02476373501121998,
-0.01936373859643936,
0.05829141288995743,
0.02311795949935913,
0.00759181659668684,
-0.02546529471874237,
0.035... |
AnonymousSub/SR_rule_based_roberta_bert_triplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 2 | null | Access to model Ralf-ca/my-sentiment-model is restricted and you are not in the authorized list. Visit https://huggingface.co/Ralf-ca/my-sentiment-model to ask for access. | [
-0.0391681082546711,
-0.0028963133227080107,
-0.01834726333618164,
0.004328385926783085,
0.035955026745796204,
0.037145793437957764,
-0.023785345256328583,
-0.00890593696385622,
-0.06348125636577606,
0.04330417886376381,
0.02840851992368698,
-0.024448895826935768,
0.023072216659784317,
0.0... |
AnonymousSub/SR_rule_based_roberta_twostage_quadruplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 4 | null | ---
license: cc-by-nc-sa-4.0
language:
- en
thumbnail: "https://huggingface.co/GeneralAwareness/VintagePhotos/resolve/main/00122-2365281862-color%20photo%20emma%20stone%20in%20the%20style%20of%20Vint.png"
tags:
- stable-diffusion
- v2
- text-to-image
- image-to-image
- Embedding
---
Textual Inversion Embedding by G... | [
-0.006742751691490412,
-0.021586034446954727,
-0.027426304295659065,
0.02763030119240284,
0.040671054273843765,
0.013602807186543941,
0.003255235031247139,
-0.00023162245634011924,
-0.026787377893924713,
0.05640237033367157,
0.017906364053487778,
-0.036206722259521484,
-0.006764458026736975,... |
AnonymousSub/SR_rule_based_roberta_twostagetriplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 8 | null | ---
license: apache-2.0
---
# Erlangshen-BERT-120M-IE-Chinese
* Github: [GTS-Engine](https://github.com/IDEA-CCNL/GTS-Engine)
* Documentation: [GTS-Engine](https://gts-engine-doc.readthedocs.io/en/latest/docs/quick_start.html)
## 简介 Brief Introduction
本模型基于大规模信息抽取数据进行预训练，可支持few-shot、zero-shot场景下的实体识别、关系三元组抽取任务。
Thi... | [
0.002494563814252615,
-0.021708747372031212,
-0.01173221692442894,
0.019325487315654755,
0.0637526661157608,
0.023997832089662552,
-0.017566654831171036,
-0.00014023928088136017,
-0.03405655547976494,
0.06070695444941521,
0.026921970769762993,
-0.0024345791898667812,
0.02829573303461075,
0... |
AnonymousSub/bert_mean_diff_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 4 | null | ---
language: en
license: mit
tags:
- exbert
datasets:
- squad_v2
thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
model-index:
- name: Shobhank-iiitdwd/DistBERT-squad2-QA-768d
results:
- task:
type: question-answering
name: Question A... | [
0.015123904682695866,
-0.03841273486614227,
-0.017020028084516525,
0.04427121952176094,
0.047273535281419754,
0.01640896685421467,
-0.03068412095308304,
0.014624451287090778,
-0.048445940017700195,
0.036928337067365646,
0.029895205050706863,
-0.000810048368293792,
0.0018292416352778673,
0.... |
AnonymousSub/consert-techqa | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"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_n... | 4 | null | ---
license: other
---
model A(*0.48) + model B(*0.32) + model C(*0.20)<br>
anime model<br>
A detailed bird's-eye view of the city, a variety of poses with such a detailed background and clothing patterns, angle variations, underwear in every position on the bed, nudity, and a custom model that is too perfect to do an... | [
-0.004132398869842291,
-0.05068648234009743,
-0.009852303192019463,
0.04994291812181473,
0.03499958664178848,
0.010814256966114044,
0.01316726766526699,
-0.005600424949079752,
-0.03440101817250252,
0.054453060030937195,
0.0365934856235981,
-0.0062972442246973515,
0.02128574252128601,
0.045... |
AnonymousSub/declutr-emanuals-techqa | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"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... | 4 | null | ---
license: apache-2.0
language:
- en
- zh
datasets:
- mnist
metrics:
- accuracy
tags:
- classification
---
MNIST
======
## Intro
hand-written digital recognition
| [
-0.015996400266885757,
-0.02216690219938755,
0.0005811617011204362,
0.03369086980819702,
0.022008055821061134,
0.01809210143983364,
-0.010660642758011818,
0.0024504612665623426,
-0.03817499056458473,
0.048417553305625916,
0.05888637527823448,
0.008861113339662552,
0.012162056751549244,
0.0... |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1_wikiqa_copy | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 2 | 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... | [
-0.01827971637248993,
-0.016717353835701942,
-0.006489653140306473,
0.026204703375697136,
0.04734259471297264,
-0.0026507817674428225,
-0.01842143014073372,
0.006653182674199343,
-0.03847556561231613,
0.05365432798862457,
0.01736641116440296,
-0.006814761087298393,
0.011855335906147957,
0.... |
AnonymousSub/rule_based_roberta_only_classfn_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"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_ngram_size... | 7 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... | [
-0.042796529829502106,
-0.005487662274390459,
-0.011714749969542027,
0.026968929916620255,
0.04685099422931671,
-0.02650737576186657,
0.005304867867380381,
-0.02773277275264263,
-0.03108399547636509,
0.06764333695173264,
0.033669743686914444,
-0.017426297068595886,
0.023003939539194107,
0.... |
AnonymousSub/rule_based_twostagetriplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 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
... | [
-0.03732970356941223,
-0.0028756442479789257,
-0.004681057296693325,
0.025700658559799194,
0.04538745433092117,
-0.02146831899881363,
-0.00551855843514204,
-0.02814510650932789,
-0.03369736298918724,
0.0666671097278595,
0.032188523560762405,
-0.02364865317940712,
0.02303437516093254,
0.001... |
AnonymousSub/rule_based_twostagetriplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_rep... | 27 | null | ---
tags:
- generated_from_trainer
model-index:
- name: test_trainer
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. -->
# test_trainer
This model is a fine-tuned v... | [
-0.03482941910624504,
-0.020544063299894333,
-0.023925499990582466,
0.04876069352030754,
0.03693396970629692,
0.04433930292725563,
-0.007192885968834162,
-0.021222468465566635,
-0.0515352301299572,
0.04248877242207527,
0.025986848399043083,
-0.030177313834428787,
-0.012236424721777439,
0.0... |
AnonymousSub/rule_based_twostagetriplet_hier_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 5 | null | ---
language:
- hi
metrics:
- wer
tags:
- ASR
- Speech Recognition
- Hindi
--- | [
-0.022924598306417465,
-0.02242688462138176,
-0.006763533689081669,
0.01857571303844452,
0.03971630334854126,
0.05046461522579193,
-0.013451896607875824,
0.009837692603468895,
-0.028006603941321373,
0.06935989856719971,
0.024226825684309006,
-0.024189366027712822,
0.005438610911369324,
0.0... |
Anthos23/my-awesome-model | [
"pytorch",
"tf",
"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,
"... | 30 | 2022-12-29T13:10:57Z | ---
license: openrail
library_name: diffusers
tags:
- TPU
- JAX
- Flax
- stable-diffusion
- text-to-image
- text-to-audio
language:
- en
--- | [
-0.018630845472216606,
-0.016805419698357582,
-0.004778839182108641,
0.014659748412668705,
0.047628890722990036,
0.018444662913680077,
0.00529870018362999,
0.002653779461979866,
-0.01617448776960373,
0.03413604944944382,
-0.003932925406843424,
0.012254245579242706,
0.02164522558450699,
0.0... |
Anthos23/sentiment-roberta-large-english-finetuned-sentiment-analysis | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-12-29T13:12:24Z | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3_0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.50 +/- 2.73... | [
-0.019545385614037514,
-0.01670992560684681,
-0.007870417088270187,
0.028566380962729454,
0.04666373133659363,
-0.0012963569024577737,
-0.0199444517493248,
0.00553959421813488,
-0.03667794540524483,
0.051222894340753555,
0.018153825774788857,
-0.004503590054810047,
0.009615092538297176,
0.... |
Antony/mint_model | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-12-29T13:21:07Z | ---
tags:
- autotrain
- vision
- image-classification
datasets:
- ivensamdh/autotrain-data-age3
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- ... | [
-0.005259410943835974,
-0.017127564176917076,
0.015491475351154804,
0.04171016067266464,
0.052293237298727036,
-0.002356743672862649,
-0.02027858793735504,
-0.002598920138552785,
-0.03685234114527702,
0.06936125457286835,
-0.0014865515986457467,
-0.0013312777737155557,
0.007292089052498341,
... |
Anubhav23/indianlegal | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-12-29T13:21:20Z | ---
license: creativeml-openrail-m
tags:
- pytorch
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth-hackathon
- food
widget:
- text: a photo of jirostyle ramen noodles in the park
---
# DreamBooth model for the jirostyle concept trained by Prgckwb on the Prgckwb/jiro-style-ramen dat... | [
-0.009313726797699928,
-0.021020296961069107,
-0.016733596101403236,
0.039340872317552567,
0.04132401943206787,
0.00428872462362051,
0.013140090741217136,
0.014186852611601353,
-0.020840691402554512,
0.06429467350244522,
0.02917475998401642,
0.0032633175142109394,
-0.010647612623870373,
0.... |
Anupam/QuestionClassifier | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-12-29T13:24:29Z | ---
language:
- en
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
Description
Anything Elynia Diffusion is a latent text-to-image diffusion model based on Anything 3.0 and then fine-tuned on the main character of 'Battle for Wesnoth... | [
-0.028399283066391945,
-0.014755431562662125,
-0.02102692797780037,
0.031859979033470154,
0.04091355577111244,
0.013353075832128525,
-0.00833012256771326,
-0.01207706704735756,
-0.014065844938158989,
0.06048843637108803,
0.025858081877231598,
-0.0029973825439810753,
-0.01160570327192545,
0... |
Apisate/DialoGPT-small-jordan | [
"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: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: it
datasets:
- lmqg/qg_itquad
pipeline_tag: text2text-generation
tags:
- answer extraction
widget:
- text: "<hl> Il 6 ottobre 1973 , la Siria e l' Egitto, con il sostegno di altre nazioni arabe, lanciarono un attacco a sorpre... | [
0.011980724520981312,
-0.010051279328763485,
-0.004155471455305815,
0.013653085567057133,
0.05950145423412323,
-0.0043190596625208855,
0.012431907467544079,
0.004143863916397095,
-0.05376675724983215,
0.05441642180085182,
0.04152536392211914,
-0.006768630817532539,
0.000024182392735383473,
... |
ArBert/roberta-base-finetuned-ner-gmm-twitter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-12-29T14:11:28Z | ---
tags:
- generated_from_keras_callback
model-index:
- name: ru_propaganda_model_with_foreign_agent_mask
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. -->
# ru_propaga... | [
-0.037226710468530655,
-0.013831501826643944,
-0.011608944274485111,
0.05772757902741432,
0.05869070440530777,
0.026246216148138046,
-0.018732726573944092,
-0.01616733893752098,
-0.04155494645237923,
0.06888365745544434,
0.01184559054672718,
-0.034473925828933716,
-0.002084784209728241,
0.... |
ArBert/roberta-base-finetuned-ner-gmm | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2022-12-29T14:13:01Z | ---
tags:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metri... | [
-0.014902355149388313,
0.014367395080626011,
-0.007120163645595312,
0.01634080521762371,
0.05433419719338417,
-0.028923580422997475,
0.0052587296813726425,
-0.0363948754966259,
-0.013302790001034737,
0.06902773678302765,
0.030559564009308815,
-0.023011822253465652,
0.005482516251504421,
0.... |
ArBert/roberta-base-finetuned-ner-kmeans-twitter | [
"pytorch",
"tensorboard",
"roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"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_... | 10 | 2022-12-29T14:20:24Z | ---
license: openrail
library_name: diffusers
tags:
- TPU
- JAX
- Flax
- stable-diffusion
- text-to-image
- text-to-audio
language:
- en
--- | [
-0.018630845472216606,
-0.016805419698357582,
-0.004778839182108641,
0.014659748412668705,
0.047628890722990036,
0.018444662913680077,
0.00529870018362999,
0.002653779461979866,
-0.01617448776960373,
0.03413604944944382,
-0.003932925406843424,
0.012254245579242706,
0.02164522558450699,
0.0... |
ArBert/roberta-base-finetuned-ner | [
"pytorch",
"tensorboard",
"roberta",
"token-classification",
"transformers",
"generated_from_trainer",
"license:mit",
"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_... | 3 | 2022-12-29T14:25:19Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- opus_books
metrics:
- bleu
model-index:
- name: my_awesome_opus_books_model_mt5
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus_books
type: opus_books
con... | [
-0.016937924548983574,
-0.009205998852849007,
0.012153811752796173,
0.04428590089082718,
0.0055541908368468285,
0.0049291858449578285,
-0.015059971250593662,
-0.02614217810332775,
-0.01825772225856781,
0.05690368264913559,
0.02701748162508011,
0.006069892551749945,
-0.019465219229459763,
0... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.