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 |
|---|---|---|---|---|---|---|
AdapterHub/roberta-base-pf-multirc | [
"roberta",
"en",
"arxiv:2104.08247",
"adapter-transformers",
"text-classification",
"adapterhub:rc/multirc"
] | text-classification | {
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"num_... | 2 | null | ---
license: apache-2.0
datasets:
- mmosiolek/pl_alpaca_data_cleaned
language:
- pl
tags:
- alpaca
- llama
- self-instruct
- casual language model
- llm
- gpt
- chat-gpt
---
# Polpaca: The Alpaca Speaks Polish
The blogpost: https://medium.com/@mmosiolek/can-alpacas-learn-languages-df48a03b6d8
[LLaMA](https://ai.face... |
Adinda/Adinda | [
"license:artistic-2.0"
] | null | {
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"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... |
Aimendo/Triage | [] | null | {
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"num_beams... | 0 | null | ---
license: cc-by-4.0
tags:
- generated_from_trainer
datasets:
- qg_squadshifts
metrics:
- bleu
model-index:
- name: t5-small-squad-qg-a2c-spt
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: qg_squadshifts
type: qg_squadshifts
... |
Aimendo/autonlp-triage-35248482 | [
"pytorch",
"bert",
"text-classification",
"en",
"dataset:Aimendo/autonlp-data-triage",
"transformers",
"autonlp",
"co2_eq_emissions"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_rep... | 33 | null | ---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 1.0
- name: NER Recall
type: recall
value: 1.0
- name: NER F Score
... |
AkshatSurolia/ICD-10-Code-Prediction | [
"pytorch",
"bert",
"transformers",
"text-classification",
"license:apache-2.0",
"has_space"
] | text-classification | {
"architectures": null,
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"num_bea... | 994 | null | ---
license: apache-2.0
language:
- tr
pipeline_tag: text-classification
widget:
- text: >-
Seni lanet olası, senin derdin ne ha?
example_title: Example Text
---
--- |
AkshayDev/BERT_Fine_Tuning | [] | null | {
"architectures": null,
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"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... |
AkshaySg/GrammarCorrection | [] | null | {
"architectures": null,
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"num_beams... | 0 | 2023-04-03T11:28:06Z |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... |
Aleksandar1932/distilgpt2-rock | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 11 | 2023-04-03T12:06:17Z | ---
license: apache-2.0
language:
- tr
pipeline_tag: text-classification
widget:
- text: >-
Seni lanet olası, senin derdin ne ha?
example_title: Example Text
---
--- |
Aleksandar1932/gpt2-country | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"no_repeat_ngram_size... | 12 | null | ---
library_name: sample-factory
tags:
- deep-reinforcement-learning
- reinforcement-learning
- sample-factory
model-index:
- name: APPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: doom_health_gathering_supreme
type: doom_health_gathering_sup... |
AlexaRyck/KEITH | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: creativeml-openrail-m
language:
- ja
pipeline_tag: text-to-image
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
library_name: diffusers
---
# HimawariMixV3とは
HimawariMixV3は様々なモデルをマージしたものになります!<br>
今回のV3は2.0の大規模改修モデルとなり更に背景に強くなりました<br>
---
# 特徴
HimawariMixは他のモデルと比較し彩度が高いmodelとなっていて... |
Alexander-Learn/bert-finetuned-ner-accelerate | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"max_length": null,
"min_length": null,
"no_repeat... | 4 | 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... |
Alexander-Learn/bert-finetuned-squad-accelerate | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: mlm-20230403-001-1
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. -->
# mlm-20230403-001-1
Thi... |
AlexeyIgnatov/albert-xlarge-v2-squad-v2 | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
language:
- tr
pipeline_tag: text-classification
widget:
- text: >-
Seni lanet olası, senin derdin ne ha?
example_title: Example Text
---
--- |
AliPotter24/a | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... |
Alireza1044/albert-base-v2-qnli | [
"pytorch",
"tensorboard",
"albert",
"text-classification",
"en",
"dataset:glue",
"transformers",
"generated_from_trainer",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
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},
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"max_length": null,
"min_length": null,
"no... | 41 | null | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... |
AllwynJ/HarryBoy | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | 2023-04-03T12:55:48Z | ---
license: apache-2.0
language:
- tr
pipeline_tag: text-classification
widget:
- text: >-
Seni lanet olası, senin derdin ne ha?
example_title: Example Text
---
--- |
Allybaby21/Allysai | [] | null | {
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"num_beams... | 0 | null | Access to model Izara/TextClassificationOnDiseases is restricted and you are not in the authorized list. Visit https://huggingface.co/Izara/TextClassificationOnDiseases to ask for access. |
AnonymousSub/SR_rule_based_hier_quadruplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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"no_repeat_ngram_size": nul... | 1 | 2023-04-03T15:23:40Z | ---
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: 7.54 +/- 2.74
... |
AnonymousSub/SR_rule_based_roberta_hier_quadruplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
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"no_repeat_ngram_size... | 2 | 2023-04-03T15:28:25Z | ---
language: en
tags:
- multivae
license: apache-2.0
---
### Downloading this model from the Hub
This model was trained with multivae. It can be downloaded or reloaded using the method `load_from_hf_hub`
```python
>>> from multivae.models import AutoModel
>>> model = AutoModel.load_from_hf_hub(hf_hub_path="your_hf_us... |
AnonymousSub/bert_hier_diff_equal_wts_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 1 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: XLMR_HASOC
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. -->
# XLMR_H... |
AnonymousSub/bert_mean_diff_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
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"no_repeat_ngram_size": nul... | 6 | 2023-04-03T16:18:53Z | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: HF_DRL_U4_pixelcopter_reinforcepg
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopte... |
AnonymousSub/bert_mean_diff_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 4 | null | ---
tags:
- CartPole-v1
- 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: CartPole-v1
type: CartPole-v1
metrics:
... |
AnonymousSub/cline | [
"pytorch",
"roberta",
"transformers"
] | null | {
"architectures": [
"LecbertForPreTraining"
],
"model_type": "roberta",
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"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_n... | 2 | 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... |
AnonymousSub/cline_emanuals | [
"pytorch",
"roberta",
"transformers"
] | null | {
"architectures": [
"LecbertForPreTraining"
],
"model_type": "roberta",
"task_specific_params": {
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"min_length": null,
"no_repeat_n... | 3 | 2023-04-03T16:49:34Z | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: HASAN55/bert-finetuned-squadddd
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. -->
# HA... |
AnonymousSub/declutr-model-emanuals | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
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"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: HASAN55/bert-finetuned-squuuad
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. -->
# HAS... |
AnonymousSub/dummy_2 | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
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"no_rep... | 39 | 2023-04-03T17:07:45Z | ---
license: apache-2.0
---

|
AnonymousSub/rule_based_bert_quadruplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
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"min_length": null,
"no_repeat_n... | 3 | 2023-04-03T17:39:52Z | ---
library_name: stable-baselines3
tags:
- PandaReachDense-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v2
type: PandaReach... |
AnonymousSub/rule_based_bert_quadruplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"bert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
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"max_length": null
},
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"max_length": null,
"min_length": null,
"no_rep... | 33 | 2023-04-03T17:41:07Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
config:... |
AnonymousSub/rule_based_bert_triplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
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"BertModel"
],
"model_type": "bert",
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"no_repeat_ngram_size": nul... | 8 | 2023-04-03T17:44:33Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-finetuned-brookstraining
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. -->
#... |
AnonymousSub/rule_based_bert_triplet_epochs_1_shard_10 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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"no_repeat_ngram_size": nul... | 4 | 2023-04-03T17:45:44Z | ---
datasets:
- Izara/ClassificationOnDiseaseDataset
language:
- en
metrics:
- accuracy
library_name: sklearn
pipeline_tag: text-classification
--- |
AnonymousSub/rule_based_only_classfn_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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"min_length": null,
"no_repeat_ngram_size": nul... | 4 | 2023-04-03T18:13:23Z | ---
license: creativeml-openrail-m
---
https://civitai.com/models/28708/noelle-silva-or-black-clover |
AnonymousSub/rule_based_roberta_bert_triplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
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"min_length": null,
"no_repeat_ngram_size... | 2 | 2023-04-03T18:30:48Z | ---
license: creativeml-openrail-m
---
https://civitai.com/models/27577/volleyball-uniform |
AnonymousSub/rule_based_roberta_hier_quadruplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"min_length": null,
"... | 24 | null | Access to model him1411/EDGAR-Tk-instruct-base-inst-tune is restricted and you are not in the authorized list. Visit https://huggingface.co/him1411/EDGAR-Tk-instruct-base-inst-tune to ask for access. |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 4 | 2023-04-03T18:42:19Z | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4... |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | 2023-04-03T18:42:31Z | ---
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
... |
AnonymousSub/rule_based_roberta_hier_triplet_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | 2023-04-03T18:44:26Z | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt2-finetuned-brookstraining
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. -->
# gpt2-finetun... |
AnonymousSub/rule_based_roberta_only_classfn_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_re... | 4 | 2023-04-03T18:53:31Z | ---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Ybhav14/autotrain-data-chat-sum-dialogsum-samsum
co2_eq_emissions:
emissions: 3.0774487291128
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 46317114985
- CO2 Emissions (in grams): ... |
AnonymousSub/rule_based_roberta_only_classfn_twostage_epochs_1_shard_1_squad2.0 | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
"model_type": "roberta",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 2 | 2023-04-03T18:58:51Z | ---
language: hy
tags:
- exbert
- armenian
- mlm
- llm
license: mit
datasets:
- oscar
---
# Model Card for HyeBERT
Pre-trained language model trained on Armenian using a masked language training strategy. The architecture is based on [BERT](https://arxiv.org/abs/1810.04805) but trained exclusively for the Armenian la... |
AnonymousSub/rule_based_roberta_twostagetriplet_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... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-large-new-v1
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. -->
# t5-large-new-v1
Th... |
AnonymousSub/rule_based_twostagetriplet_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": nul... | 10 | null | ---
tags:
- llama
- vicuna
- text-generation-inference
---
**NOTE: Get the new version here: https://huggingface.co/eachadea/vicuna-13b-1.1** |
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 | ---
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
... |
AnonymousSub/rule_based_twostagetriplet_hier_epochs_1_shard_1 | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": nul... | 5 | null | ---
license: apache-2.0
---
# Debate-alpaca-lora
An English debate model by instruct-tuning LLaMA on [Kialo](https://www.kialo.com/) data.
We may ask the model to **support** or **oppose** a claim by the desconding order of impact.
**A quick start for inference**: <a href="https://colab.research.google.com/drive/1... |
AnonymousSub/unsup-consert-base | [
"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 | ---
library_name: stable-baselines3
tags:
- InvertedDoublePendulumBulletEnv-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: InvertedDoublePendulumBul... |
Anthos23/FS-distilroberta-fine-tuned | [
"pytorch",
"roberta",
"text-classification",
"transformers",
"has_space"
] | 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,
"... | 33 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_5e-05
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 ... |
Anubhav23/IndianlegalBert | [] | 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:
- llama
- alpaca
- gpt4
- text-generation-inference
pipeline_tag: conversational
---
GPT4 x Alpaca-13b-native
---
- Converted and quantized by **ItsBradarr** |
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 | null | ---
license: apache-2.0
language:
- tr
pipeline_tag: text-classification
tags:
- code
---
Aşağılayıcı Söylem Tespit Modelimiz
İlk olarak yorumun OFFENSİVE ya da NOT OFFENSİVE olup olmadığını tespit eder.
Yorum OFFENSİVE olarak algılanmışsa alt kategorilerine göre 'INSULT', 'RACIST', 'SEXIST', 'PROFANITY'
olma durumla... |
Aracatto/Catto | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-04-03T21:34:48Z | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_5e-05_ES2
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 t... |
AragornII/DialoGPT-small-harrypotter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-04-03T21:36:59Z | ---
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... |
ArashEsk95/bert-base-uncased-finetuned-cola | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tmvar_0.0001_ES2
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 ... |
ArseniyBolotin/bert-multi-PAD-ner | [
"pytorch",
"jax",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat... | 11 | 2023-04-03T23:16:48Z | ---
license: other
---
This contains the weights for the LLaMA-7b model. This model is under a non-commercial license (see the LICENSE file).
You should only use this repository if you have been granted access to the model by filling out [this form](https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4... |
Atiqah/Atiqah | [
"license:artistic-2.0"
] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
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"early_stopping": null,
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | # Emotion Recognition on Gradio
This repo contains code to launch a [Gradio](https://github.com/gradio-app/gradio) interface for Emotion Recognition on [Gradio Hub](https://hub.gradio.app)
Please see the **original repo**: [omar178/Emotion-recognition](https://github.com/omar178/Emotion-recognition)

## This is just a mirror |
Augustvember/WokkaBot6 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"min_length": null,
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"num_beams... | 0 | null | ---
license: other
---
This contains the weights for the LLaMA-30b model. This model is under a non-commercial license (see the LICENSE file).
You should only use this repository if you have been granted access to the model by filling out [this form](https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR... |
Augustvember/WokkaBotF | [] | null | {
"architectures": null,
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},
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"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: flower-classifier
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9701492786407471
---
# flower-classifie... |
Ayah/GPT2-DBpedia | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | 2023-04-04T02:26:39Z | ---
license: apache-2.0
---
This is a streaming Zipformer Transducer model trained on LibriSpeech and GigaSpeech.
Please see https://github.com/k2-fsa/icefall/pull/984 for more details. |
Ayham/bert_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: POP
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
... |
Ayham/bert_gpt2_summarization_cnndm_new | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | 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... |
Ayham/roberta_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | null | ---
library_name: paddlenlp
---
# linjieccc/tiny-random-uie-m |
Ayham/robertagpt2_cnn | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
library_name: paddlenlp
---
# linjieccc/tiny-random-uie-x |
Ayham/xlmroberta_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 9 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### ssagirl Dreambooth model trained by Fred99774 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 Colab [fa... |
Ayham/xlnet_gpt_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 11 | 2023-04-04T04:08:06Z | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-unit4_2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
met... |
Ayham/xlnet_roberta_new_summarization_cnn_dailymail | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilroberta-base-finetuned-wikitext2
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. -->... |
Ayham/xlnet_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 10 | null | This is a clone of EleutherAI/gpt-j-6b. Only change is config.js - allow larger inputs to TextGeneration pipeline |
Ayham/xlnetgpt2_xsum7 | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
license: other
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: mobilenet_v2_1.0_224-plant-disease-identification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: New Plant Diseases Dataset
type: ima... |
Aymene/opus-mt-en-ro-finetuned-en-to-ro | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
This model is a diffusion model for unconditional image generation of the universe trained for 1400 epochs.
## Usage
```python
from diffusers import DDPMPipeline
pipeline = DDPMPipeline.from_pretrained('ocari... |
Ayoola/wav2vec2-large-xlsr-turkish-demo-colab | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
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},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | Access to model Cletrason/mario-movie-toad-centered is restricted and you are not in the authorized list. Visit https://huggingface.co/Cletrason/mario-movie-toad-centered to ask for access. |
AyushPJ/ai-club-inductions-21-nlp-distilBERT | [
"pytorch",
"distilbert",
"question-answering",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"DistilBertForQuestionAnswering"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 8 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-v2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics:... |
AyushPJ/ai-club-inductions-21-nlp-roBERTa | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"generated_from_trainer",
"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... | 8 | null | ---
language:
- en
license: apache-2.0
---
# BERT multilingual base model (cased)
Pretrained model on the English dataset using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/be... |
AyushPJ/test-squad-trained-finetuned-squad | [
"pytorch",
"tensorboard",
"distilbert",
"question-answering",
"dataset:squad",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"DistilBertForQuestionAnswering"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 8 | 2023-04-04T05:08:24Z | ---
language:
- en
license: apache-2.0
---
# BERT multilingual base model (cased)
Pretrained model on the English dataset using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/be... |
Azaghast/DistilBART-SCP-ParaSummarization | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"BartForConditionalGeneration"
],
"model_type": "bart",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 142,
"min_length": 56,
"no_repeat_ngr... | 8 | null | ---
language:
- en
license: apache-2.0
---
# BERT multilingual base model (cased)
Pretrained model on the English dataset using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/be... |
Azaghast/DistilBERT-SCP-Class-Classification | [
"pytorch",
"distilbert",
"text-classification",
"transformers"
] | 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,
... | 42 | 2023-04-04T05:08:48Z | ---
language:
- en
license: apache-2.0
---
# BERT multilingual base model (cased)
Pretrained model on the English dataset using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/be... |
Azaghast/GPT2-SCP-ContainmentProcedures | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 5 | null | ---
language:
- en
license: apache-2.0
---
# BERT multilingual base model (cased)
Pretrained model on the English dataset using a masked language modeling (MLM) objective.
It was introduced in [this paper](https://arxiv.org/abs/1810.04805) and first released in
[this repository](https://github.com/google-research/be... |
BSC-LT/roberta-base-bne-capitel-ner | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 12 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SoccerTwos
library_name: ml-agents
---
# **poca** Agent playing **SoccerTwos**
This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unit... |
BatuhanYilmaz/distilbert-base-uncased-finetuned-squad-d5716d28 | [
"pytorch",
"distilbert",
"fill-mask",
"en",
"dataset:squad",
"arxiv:1910.01108",
"transformers",
"question-answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repea... | 18 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### Toad-Mario-Movie- Dreambooth model trained by Cletrason 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... |
BearThreat/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,
... | 30 | null | ---
language:
- en
- zh
- de
- fr
library_name: sentence-transformers
license: apache-2.0
---
# ZeroNLG
Without any labeled downstream pairs for training, ZeroNLG is an unified framework that deals with multiple natural language generation (NLG) tasks in a zero-shot manner, including image-to-text, video-to-text, an... |
BigDaddyNe1L/Hhaa | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: my_awesome_qa_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
... |
BigSalmon/BestMask2 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 10 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
language:
- he
library_name: sentence-transformers
---
# imvladikon/sentence-transformers-alephbert[WIP]
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & pa... |
BigSalmon/FormalRobertaaa | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 12 | null | ---
pipeline_tag: text-to-image
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/mod... |
BigSalmon/GPT2HardandEasy | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
---
# Cohere `multilingual-22-12` tokenizer
This is the tokenizer for the Cohere `multilingual-22-12` embedding model: [Cohere Multilingual Embeddings](https://docs.cohere.ai/docs/multilingual-language-models)
You can load it with the transformers library like this:
```python
from transformer... |
BigSalmon/MrLincoln13 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gpt-j-t-q
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt-j-t-q
This model is ... |
BigSalmon/MrLincoln14 | [] | 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 | 2023-04-04T09:44:51Z | ---
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
... |
BigSalmon/MrLincoln3 | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 17 | 2023-04-04T09:48:05Z | ---
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
... |
BigSalmon/NEO125InformalToFormalLincoln | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 8 | null | ---
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... |
BigSalmon/ParaphraseParentheses2.0 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-pixelcopter
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
... |
BigSalmon/Points | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
license: openrail
---
# 本仓库为备份仓库,模型来源于网络
# 命令下载格式:
git lfs clone https://huggingface.co/用户名/项目
(下载全部)
aria2c https://huggingface.co/用户名/项目/resolve/main/目录/文件名
(下载单个文件) |
BigSalmon/Robertsy | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | null | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
{}
---
# AudioLDM
AudioLDM is a latent text-to-audio diffusion model capable of generating realistic audio samples given any text ... |
BigSalmon/T5F | [
"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... | 6 | null | ---
library_name: ml-agents
tags:
- SnowballTarget
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Tech... |
BigSalmon/prepositions | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 7 | null | ---
pipeline_tag: text2text-generation
widget:
- text: Hellooooo
example_title: Ex 0
- text: believ
example_title: Ex 1
language:
- en
tags:
- spell
- spell correction
- spelling
- spelling correction
- english
- english spelling
---
# Model Card for Model ID
This is a model for word-based spell correction tasks.... |
BigTooth/DialoGPT-Megumin | [
"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... | 16 | null | ---
license: mit
language:
- en
pipeline_tag: text-to-image
---
## NVJOBAim v1.0. This is a model for generating crosshair assets. For stable diffusion.
This is a trained model for stable diffusion capable of generating crosshair images for video games. She trained on a large crosshair image dataset, which allows her... |
BigeS/DialoGPT-small-Rick | [
"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... | 10 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: gpt-j-tweet-quset
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt-j-tweet-quset... |
Bilz/DialoGPT-small-harrypotter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- 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: CartPole-v1
type: CartPole-v1
metrics:
... |
Binbin/test | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
library_name: ml-agents
tags:
- Pyramids
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
... |
BinksSachary/ShaxxBot | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- sefaozalpadl/autotrain-data-postnashville_antitrans_telegram
co2_eq_emissions:
emissions: 0.4434488215878769
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 4662211... |
Blabla/Pipipopo | [] | 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:
- AntBulletEnv-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: AntBulletEnv-v0
type: AntBulletEnv-v0
... |
Blackmist786/DialoGPt-small-transformers4 | [
"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... | 4 | null | # Experience 8.0
[Civitai](https://civitai.com/models/5952)


* Include... |
Blaine-Mason/hackMIT-finetuned-sst2 | [
"pytorch",
"tensorboard",
"bert",
"text-classification",
"dataset:glue",
"transformers",
"generated_from_trainer"
] | 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... | 36 | null | ---
license: bigscience-openrail-m
datasets:
- laion/Anh
library_name: transformers
pipeline_tag: text-generation
tags:
- pytorch
- casual-lm
- multilingual
- instruct
- bloomz
---
### Model description
This model is [`bloomz-7b1-mt`](https://huggingface.co/bigscience/bloomz-7b1-mt) model finetuned on instruct datase... |
Botjallu/DialoGPT-small-harrypotter | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-04-04T11:10:20Z | ---
license: apache-2.0
datasets:
- tatsu-lab/alpaca
---
## 🍮 🦙 Flan-Alpaca: Instruction Tuning from Humans and Machines
📣 **FLAN-T5** is also useful in text-to-audio generation. Find our work at [https://github.com/declare-lab/tango](https://github.com/declare-lab/tango) if you are interested.
Our [repository](... |
Branex/gpt-neo-2.7B | [] | 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 | 2023-04-04T11:12:15Z | ---
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
... |
Brokette/projetCS | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"transformers"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 4 | null | ---
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... |
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