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 |
|---|---|---|---|---|---|---|
Alessandro/model_name | [] | null | {
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"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/iwontsmthing1/1678830403864/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; w... |
AlexN/xls-r-300m-fr | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"fr",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"generated_from_trainer",
"hf-asr-leaderboard",
"mozilla-foundation/common_voice_8_0",
"robust-speech-event",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
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"no_repeat_ngram_s... | 17 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MultiLabel_V3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# M... |
AlexN/xls-r-300m-pt | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"pt",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"robust-speech-event",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
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"no_repeat_ngram_s... | 15 | null | # Model Card for hestyle-controlnet
### Model Description
Scribble controlnet transferred Hestyle model.
- **Developed by:** Alethea.ai
- **Model type:** PyTorch Checkpoint
- **License:** [Will provide soon.]
- **Finetuned from model [optional]:** Hestyle
## Bias, Risks, and Limitations
[Will provide soon.]
### Recomme... |
Alexander-Learn/bert-finetuned-ner-accelerate | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
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"no_repeat... | 4 | 2023-03-14T22:07:00Z | ---
language:
- da
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: Whisper Tiny Da - HollowVoice
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: de... |
AlirezaBaneshi/testPersianQA | [
"pytorch",
"bert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"BertForQuestionAnswering"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_n... | 4 | null | ---
license: creativeml-openrail-m
language:
- en
tags:
- LoRA
- Lycoris
- stable diffusion
- ffxiv
- final fantasy xiv
- meteion
---
# 24 Cans of Monster: Meteion FFXIV Lycoris Model
Full previews are here at the moment: https://civitai.com/models/19689/24-cans-of-monster-meteion-ffxiv-endwalker-spoilers
I will be ... |
Aliskin/xlm-roberta-base-finetuned-marc | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: unit4
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
... |
Allybaby21/Allysai | [] | null | {
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"num_beams... | 0 | null | ---
license: mit
---
<h1 align="center">arabert-finetuned-caner</h1>
<p align="center">An ongoing project for implementation of NLP methods in the field of islamic studies.</p>
### Named Entity Recognition
briefly:
* We had to prepair CANERCorpus dataset which is avialable at [huggingface](https://huggingface.co/dat... |
Aloka/mbart50-ft-si-en | [
"pytorch",
"tensorboard",
"mbart",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MBartForConditionalGeneration"
],
"model_type": "mbart",
"task_specific_params": {
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},
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"no_re... | 4 | null | from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
# Let's chat for 5 lines
for step in range(5):
# encode the new user input, add the eos_token ... |
Alstractor/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": {
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"max_length": null
},
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... | 40 | null | # AMR prediction with LGBMClassifier models
This repository contains a Python script for predicting antimicrobial resistance (AMR) using the LGBMClassifier model. The script reads input datasets from a directory, applies feature extraction techniques to obtain k-mer features, trains and tests the models using cross-val... |
Amalq/distilroberta-base-finetuned-anxiety-depression | [] | null | {
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"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
... |
AmanPriyanshu/DistilBert-Sentiment-Analysis | [
"tf",
"distilbert",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
"task_specific_params": {
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},
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"min_length": null,
"no_repea... | 7 | 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
... |
AmazonScience/qanlu | [
"pytorch",
"roberta",
"question-answering",
"en",
"dataset:atis",
"transformers",
"license:cc-by-4.0",
"autotrain_compatible",
"has_space"
] | question-answering | {
"architectures": [
"RobertaForQuestionAnswering"
],
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},
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"max_length": null,
"min_length": null,
"no_re... | 494 | null | ---
language:
- en
- cy
pipeline_tag: translation
tags:
- translation
- marian
metrics:
- bleu
- cer
- wer
- wil
- wip
- chrf
widget:
- text: "The doctor will be late to attend to patients this morning."
example_title: "Example 1"
license: apache-2.0
model-index:
- name: "mt-dspec-health-en-cy"
results:
- task:... |
Amba/wav2vec2-large-xls-r-300m-tr-colab | [] | null | {
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"num_beams... | 0 | null | ---
language:
- en
- cy
license: apache-2.0
pipeline_tag: translation
tags:
- translation
- marian
metrics:
- bleu
- cer
- chrf
- cer
- wer
- wil
- wip
widget:
- text: "The Curriculum and Assessment (Wales) Act 2021 (the Act) established the Curriculum for Wales and replaced the general curriculum used u... |
Andranik/TestQaV1 | [
"pytorch",
"rust",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
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"RobertaForQuestionAnswering"
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},
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"min_length": null,
"no_re... | 4 | 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
... |
AndrewNLP/redditDepressionPropensityClassifiers | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: DQPN_decay
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics... |
Andrey1989/mbart-finetuned-en-to-kk | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- CartPole-v1
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: DQPN_decay
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics... |
Andrey78/my_nlp_test_model | [] | null | {
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"num_beams... | 0 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/barackobama-joebiden-realdonaldtrump/1678850778048/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4p... |
Andrianos/bert-base-greek-punctuation-prediction-finetuned | [
"pytorch",
"bert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"BertForTokenClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat... | 0 | null | ---
license: mit
datasets:
- koliskos/fake_news
language:
- en
---
# Model Card for Model ID
Model is used to detect whether a news story is fake or legitimate.
- **Developed by:** koliskos
- **Model type:** Text Classification
- **Language(s) (NLP):** English
- **License:** mit
- **Finetuned from model:** DistilBE... |
AnonymousSub/AR_consert | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"BertModel"
],
"model_type": "bert",
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"no_repeat_ngram_size": nul... | 2 | null | ---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-RealLifeViolenceSituations-subset
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and c... |
AnonymousSub/AR_rule_based_roberta_twostagetriplet_epochs_1_shard_1 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
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"no_repeat_ngram_size... | 6 | 2023-03-15T05:40:28Z | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt2-confluence
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-confluence
This mode... |
AnonymousSub/AR_rule_based_roberta_twostagetriplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
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"min_length": null,
"no_repeat_ngram_size... | 2 | null | ---
license: cc-by-4.0
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-clickbait-spoiling-2
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. -->
# xlm... |
AnonymousSub/SR_declutr | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
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},
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"no_repeat_ngram_size... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: my_awesome_model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: test
args: pla... |
AnonymousSub/SR_rule_based_bert_quadruplet_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... | 1 | null | ---
license: mit
---
Pretrained models of our method **DirectMHP**
Title: *DirectMHP: Direct 2D Multi-Person Head Pose Estimation with Full-range Angles*
Paper link: https://arxiv.org/abs/2302.01110
Code link: https://github.com/hnuzhy/DirectMHP
# Mulit-Person Head Pose Estimation Task (trained on CMU-HPE)
* Direc... |
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": {
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},
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"no_repeat_ngram_size": nul... | 1 | 2023-03-15T06:30:59Z | ---
license: mit
language:
- en
---
# BERT-Tiny (uncased)
This is the smallest version of 24 smaller BERT models (English only, uncased, trained with WordPiece masking)
released by [google-research/bert](https://github.com/google-research/bert).
These BERT models was released as TensorFlow checkpoints, however, this ... |
AnonymousSub/SR_rule_based_hier_triplet_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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"no_repeat_ngram_size": nul... | 1 | 2023-03-15T06:33:28Z | ---
language:
- en
datasets:
- en_core_web_sm
thumbnail: >-
https://huggingface.co/giovannefeitosa/chatbot-about-pele/raw/main/images/pele.jpeg
tags:
- question-answering
- chatbot
- brazil
license: cc-by-nc-4.0
pipeline_tag: text2text-generation
library_name: sklearn
---
# Chatbot about Pele
This is demo project.
... |
AnonymousSub/SR_rule_based_roberta_hier_triplet_epochs_1_shard_10 | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
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"no_repeat_ngram_size... | 6 | null | ---
license: mit
language:
- ko
---
# Kconvo-roberta: Korean conversation RoBERTa ([github](https://github.com/HeoTaksung/Domain-Robust-Retraining-of-Pretrained-Language-Model))
- There are many PLMs (Pretrained Language Models) for Korean, but most of them are trained with written language.
- Here, we introduce a ret... |
AnonymousSub/SR_rule_based_roberta_hier_triplet_epochs_1_shard_1_wikiqa_copy | [
"pytorch",
"roberta",
"feature-extraction",
"transformers"
] | feature-extraction | {
"architectures": [
"RobertaModel"
],
"model_type": "roberta",
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},
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"min_length": null,
"no_repeat_ngram_size... | 2 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
---
# {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 clustering or semanti... |
AnonymousSub/SR_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... | 2 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: indonesian_financial_sentiment_analysis
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove thi... |
AnonymousSub/bert_hier_diff_equal_wts_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... | 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... |
AnonymousSub/bert_mean_diff_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 | 2023-03-15T07:54:09Z | ---
library_name: keras
license: apache-2.0
datasets:
- kailashsp/class-images
pipeline_tag: text-to-image
---
## Model description
This is a Stable Diffusion model fine-tuned using Dreambooth on pokemon
to get cuter pokemons
## Intended uses & limitations
More information needed
## Training and evaluation data
... |
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 | 2023-03-15T07:55:32Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-finetuned-cryptos
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/bert_triplet_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... | 1 | null | ---
license: mit
language:
- en
---
# BERT-Medium (uncased)
This is one of 24 smaller BERT models (English only, uncased, trained with WordPiece masking)
released by [google-research/bert](https://github.com/google-research/bert).
These BERT models was released as TensorFlow checkpoints, however, this is the converte... |
AnonymousSub/cline-emanuals-s10-AR | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 27 | 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
{}
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This modelcard aims to be a base tem... |
AnonymousSub/cline-s10-AR | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 31 | 2023-03-15T08:05:48Z | ---
license: mit
language:
- en
---
# BERT-Small (uncased)
This is one of 24 smaller BERT models (English only, uncased, trained with WordPiece masking)
released by [google-research/bert](https://github.com/google-research/bert).
These BERT models was released as TensorFlow checkpoints, however, this is the converted... |
AnonymousSub/cline-s10-SR | [] | 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 | 2023-03-15T08:07:57Z | ---
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/cline | [
"pytorch",
"roberta",
"transformers"
] | null | {
"architectures": [
"LecbertForPreTraining"
],
"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_n... | 2 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: T5_Translation_ko_jp
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/cline_emanuals | [
"pytorch",
"roberta",
"transformers"
] | null | {
"architectures": [
"LecbertForPreTraining"
],
"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_n... | 3 | null | ---
license: creativeml-openrail-m
datasets:
- Duskfallcrew/FFXIV_Data_and_Lora
- Duskfallcrew/miqoteupdate
language:
- en
tags:
- Lycoris
- LoHA
- Lora
- stable diffusion
- text to image
- ffxiv
- miqote
---
Output udpates coming soon, we have some but if you need to see them before we put them here- we have the mode... |
AnonymousSub/consert-emanuals-s10-SR | [
"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: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Model Card for Unit 1 of the [Diffusion Models Class ๐งจ](https://github.com/huggingface/diffusion-models-class)
This model is a diffusion model for unconditional image generation of cute ๐ฆ.
## Usage
```pyth... |
AnonymousSub/consert-s10-AR | [
"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... | 31 | null | ---
library_name: stable-baselines3
tags:
- Taxi-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type:... |
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 | 2023-03-15T08:25:26Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: generative_reader_nq_squad_v2
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 ... |
AnonymousSub/declutr-model | [
"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 | 2023-03-15T08:26:35Z | # โ hakoA & hakoB
I conducted custom fi... |
AnonymousSub/rule_based_bert_quadruplet_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... | 8 | 2023-03-15T08:58:08Z | ---
tags:
- autotrain
- vision
- image-classification
datasets:
- mouss/autotrain-data-bikes_1
widget:
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg
example_title: Tiger
- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg
example_title: Teapot
- s... |
AnonymousSub/rule_based_hier_triplet_0.1_epochs_1_shard_1_squad2.0 | [
"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... | 2 | 2023-03-15T09:32:36Z | 1 OneCount: 8619 -- Precision: 0.875624
0 ZeroCount: 345 -- Precision: 0.785507
|
AnonymousSub/rule_based_roberta_bert_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 | 2023-03-15T10:11:15Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-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. -->
# dist... |
AnonymousSub/rule_based_roberta_hier_quadruplet_0.1_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 | 2023-03-15T10:13:18Z | ---
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_quadruplet_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 | 2023-03-15T10:14:42Z | # Vocabulary Trimmed [lmqg/mt5-small-koquad-qg](https://huggingface.co/lmqg/mt5-small-koquad-qg): `vocabtrimmer/mt5-small-koquad-qg-trimmed-ko-5000`
This model is a trimmed version of [lmqg/mt5-small-koquad-qg](https://huggingface.co/lmqg/mt5-small-koquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-tr... |
AnonymousSub/rule_based_roberta_hier_quadruplet_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
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 2 | 2023-03-15T10:14:49Z | # Vocabulary Trimmed [lmqg/mt5-small-ruquad-qg](https://huggingface.co/lmqg/mt5-small-ruquad-qg): `vocabtrimmer/mt5-small-ruquad-qg-trimmed-ru-5000`
This model is a trimmed version of [lmqg/mt5-small-ruquad-qg](https://huggingface.co/lmqg/mt5-small-ruquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-tr... |
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": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 24 | 2023-03-15T10:15:01Z | # Vocabulary Trimmed [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg): `vocabtrimmer/mt5-small-esquad-qg-trimmed-es-5000`
This model is a trimmed version of [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-tr... |
AnonymousSub/rule_based_roberta_hier_triplet_0.1_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 | 2023-03-15T10:15:02Z | # Vocabulary Trimmed [lmqg/mt5-small-frquad-qg](https://huggingface.co/lmqg/mt5-small-frquad-qg): `vocabtrimmer/mt5-small-frquad-qg-trimmed-fr-5000`
This model is a trimmed version of [lmqg/mt5-small-frquad-qg](https://huggingface.co/lmqg/mt5-small-frquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-tr... |
AnonymousSub/rule_based_roberta_hier_triplet_0.1_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
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 2 | 2023-03-15T10:15:05Z | # Vocabulary Trimmed [lmqg/mt5-small-itquad-qg](https://huggingface.co/lmqg/mt5-small-itquad-qg): `vocabtrimmer/mt5-small-itquad-qg-trimmed-it-5000`
This model is a trimmed version of [lmqg/mt5-small-itquad-qg](https://huggingface.co/lmqg/mt5-small-itquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-tr... |
AnonymousSub/rule_based_roberta_twostagetriplet_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
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | 2023-03-15T10:30:23Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: clinico-roberta-biomedical-finetuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread an... |
AnonymousSub/rule_based_roberta_twostagetriplet_epochs_1_shard_1_wikiqa | [
"pytorch",
"roberta",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"RobertaForSequenceClassification"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"... | 24 | 2023-03-15T10:30:38Z | # Vocabulary Trimmed [lmqg/mt5-small-ruquad-qg](https://huggingface.co/lmqg/mt5-small-ruquad-qg): `vocabtrimmer/mt5-small-ruquad-qg-trimmed-ru-10000`
This model is a trimmed version of [lmqg/mt5-small-ruquad-qg](https://huggingface.co/lmqg/mt5-small-ruquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
AnonymousSub/rule_based_roberta_twostagetriplet_hier_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... | 5 | 2023-03-15T10:31:35Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-ja-60000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
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 | 2023-03-15T10:34:22Z | Universele Mark Rutte model.
Gebruik trigger mrkrut en je gezonde boerenverstand ;-)
Muppet prompt: (mrkrut) as a (muppet), vray renderer, highly detailed felt, hyper real photo realistic artstation cgsociety masterpiece
Seed:415127944
Resolutie: 512x768
Sampler: Euler
Steps: 50
GFC: 8.0 |
AnonymousSub/rule_based_twostagetriplet_hier_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 | 2023-03-15T10:36:20Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: christoph-sl
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
conf... |
AnonymousSub/specter-bert-model_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 | 2023-03-15T10:36:53Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-ko-5000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of ... |
AnonymousSub/specter-bert-model_copy_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... | 26 | 2023-03-15T10:38:49Z | # Vocabulary Trimmed [lmqg/mt5-small-jaquad-qg](https://huggingface.co/lmqg/mt5-small-jaquad-qg): `vocabtrimmer/mt5-small-jaquad-qg-trimmed-ja-15000`
This model is a trimmed version of [lmqg/mt5-small-jaquad-qg](https://huggingface.co/lmqg/mt5-small-jaquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
AnonymousSub/specter-bert-model_squad2.0 | [
"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... | 1 | 2023-03-15T10:38:51Z | # Vocabulary Trimmed [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg): `vocabtrimmer/mt5-small-esquad-qg-trimmed-es-10000`
This model is a trimmed version of [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
AnonymousSub/unsup-consert-emanuals | [
"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 | 2023-03-15T10:44:20Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-es-90000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
AnonymousSub/unsup-consert-papers-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... | 9 | 2023-03-15T10:44:20Z | # Vocabulary Trimmed [lmqg/mt5-small-itquad-qg](https://huggingface.co/lmqg/mt5-small-itquad-qg): `vocabtrimmer/mt5-small-itquad-qg-trimmed-it-15000`
This model is a trimmed version of [lmqg/mt5-small-itquad-qg](https://huggingface.co/lmqg/mt5-small-itquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
Anonymreign/savagebeta | [] | 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 | 2023-03-15T10:45:41Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-ko-30000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
Anorak/nirvana | [
"pytorch",
"pegasus",
"text2text-generation",
"unk",
"dataset:Anorak/autonlp-data-Niravana-test2",
"transformers",
"autonlp",
"co2_eq_emissions",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"PegasusForConditionalGeneration"
],
"model_type": "pegasus",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"n... | 7 | 2023-03-15T10:46:02Z | # Vocabulary Trimmed [lmqg/mt5-small-ruquad-qg](https://huggingface.co/lmqg/mt5-small-ruquad-qg): `vocabtrimmer/mt5-small-ruquad-qg-trimmed-ru-15000`
This model is a trimmed version of [lmqg/mt5-small-ruquad-qg](https://huggingface.co/lmqg/mt5-small-ruquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
Anthos23/distilbert-base-uncased-finetuned-sst2 | [
"tf",
"tensorboard",
"distilbert",
"text-classification",
"transformers",
"generated_from_keras_callback",
"license:apache-2.0"
] | 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,
... | 21 | 2023-03-15T10:47:20Z | ---
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
... |
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 | 2023-03-15T10:47:33Z | ---
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... |
Antony/mint_model | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-03-15T10:51:21Z | # Vocabulary Trimmed [lmqg/mt5-small-jaquad-qg](https://huggingface.co/lmqg/mt5-small-jaquad-qg): `vocabtrimmer/mt5-small-jaquad-qg-trimmed-ja-30000`
This model is a trimmed version of [lmqg/mt5-small-jaquad-qg](https://huggingface.co/lmqg/mt5-small-jaquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
gaurishhs/API | [] | 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 | 2023-03-15T10:54:44Z | # Vocabulary Trimmed [lmqg/mt5-small-frquad-qg](https://huggingface.co/lmqg/mt5-small-frquad-qg): `vocabtrimmer/mt5-small-frquad-qg-trimmed-fr-60000`
This model is a trimmed version of [lmqg/mt5-small-frquad-qg](https://huggingface.co/lmqg/mt5-small-frquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
ArBert/albert-base-v2-finetuned-ner-agglo | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | 2023-03-15T11:01:04Z | # Vocabulary Trimmed [lmqg/mt5-small-koquad-qg](https://huggingface.co/lmqg/mt5-small-koquad-qg): `vocabtrimmer/mt5-small-koquad-qg-trimmed-ko-30000`
This model is a trimmed version of [lmqg/mt5-small-koquad-qg](https://huggingface.co/lmqg/mt5-small-koquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
ArBert/albert-base-v2-finetuned-ner-kmeans | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | 2023-03-15T11:03:48Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-ja-120000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary o... |
ArBert/albert-base-v2-finetuned-ner | [
"pytorch",
"tensorboard",
"albert",
"token-classification",
"dataset:conll2003",
"transformers",
"generated_from_trainer",
"license:apache-2.0",
"model-index",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 19 | 2023-03-15T11:04:45Z | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-TASTESet-ner
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it... |
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 | 2023-03-15T11:16:20Z | # Vocabulary Trimmed [lmqg/mt5-small-itquad-qg](https://huggingface.co/lmqg/mt5-small-itquad-qg): `vocabtrimmer/mt5-small-itquad-qg-trimmed-it-60000`
This model is a trimmed version of [lmqg/mt5-small-itquad-qg](https://huggingface.co/lmqg/mt5-small-itquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
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 | 2023-03-15T11:19:04Z | # Vocabulary Trimmed [lmqg/mt5-small-koquad-qg](https://huggingface.co/lmqg/mt5-small-koquad-qg): `vocabtrimmer/mt5-small-koquad-qg-trimmed-ko-60000`
This model is a trimmed version of [lmqg/mt5-small-koquad-qg](https://huggingface.co/lmqg/mt5-small-koquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
Aracatto/Catto | [] | 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 | 2023-03-15T11:23:44Z | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: unsupervised-fine-tune-roberta-exist-5
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... |
AragornII/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 | 2023-03-15T11:26:13Z | # Vocabulary Trimmed [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg): `vocabtrimmer/mt5-small-esquad-qg-trimmed-es-30000`
This model is a trimmed version of [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
Arcanos/1 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
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
... |
Archie/myProject | [] | 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 | 2023-03-15T11:36:51Z | # Vocabulary Trimmed [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg): `vocabtrimmer/mt5-small-esquad-qg-trimmed-es-120000`
This model is a trimmed version of [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-... |
Arghyad/Loki_small | [] | 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 | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-ru-5000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of ... |
Aries/T5_question_answering | [
"pytorch",
"jax",
"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... | 5 | 2023-03-15T11:44:12Z | ---
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... |
Arina/Erine | [] | 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 | 2023-03-15T11:45:03Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-ru-15000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
ArjunKadya/HuggingFace | [] | 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 | 2023-03-15T11:45:53Z | ---
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... |
Arkadiusz/Test-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 | 2023-03-15T11:47:51Z | ---
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... |
Arnold/common_voiceha | [] | 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 | 2023-03-15T11:51:43Z | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Prgrg/ja-en-JESC-v3.0
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. -->
# Prgrg/ja-en-... |
Arnold/wav2vec2-hausa-demo-colab | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-03-15T11:52:01Z | # Vocabulary Trimmed [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg): `vocabtrimmer/mt5-small-esquad-qg-trimmed-es-60000`
This model is a trimmed version of [lmqg/mt5-small-esquad-qg](https://huggingface.co/lmqg/mt5-small-esquad-qg) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-t... |
Arpita/opus-mt-en-ro-finetuned-synthon-to-reactant | [] | 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 | 2023-03-15T12:06:27Z | ---
license: openrail
language:
- en
datasets:
- ErfanMoosaviMonazzah/fake-news-detection-English
metrics:
- f1
pipeline_tag: text-classification
tags:
- fake news detection
- tiny bert
widget:
- text: "Militant blast, gun attack kill 18 police in Egypt's Sinai"
example_title: "True News"
- text: "Trump Is Literally ... |
Ashkanmh/bert-base-parsbert-uncased-finetuned | [
"pytorch",
"tensorboard",
"bert",
"fill-mask",
"transformers",
"generated_from_trainer",
"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 | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-fr-30000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
Augustvember/WokkaBot9 | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-03-15T12:54:07Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-es-5000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of ... |
Augustvember/wokka4 | [
"conversational"
] | conversational | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | 2023-03-15T12:56:38Z | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-es-10000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
Axon/resnet34-v1 | [
"dataset:ImageNet",
"arxiv:1512.03385",
"Axon",
"Elixir",
"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 | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-es-60000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
Ayah/GPT2-DBpedia | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-it-5000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of ... |
Aybars/ModelOnTquad | [
"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... | 8 | null | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-it-15000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
Aybars/XLM_Turkish | [
"pytorch",
"xlm-roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"XLMRobertaForQuestionAnswering"
],
"model_type": "xlm-roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
... | 4 | 2023-03-15T13:27:47Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: output
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. -->
# output
... |
Ayham/albert_bert_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 12 | null | # Vocabulary Trimmed [google/mt5-small](https://huggingface.co/google/mt5-small): `vocabtrimmer/mt5-small-trimmed-it-30000`
This model is a trimmed version of [google/mt5-small](https://huggingface.co/google/mt5-small) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of... |
Ayham/bert_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | 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... |
Ayham/bertgpt2_cnn | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: pixelcoper-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics... |
Ayham/distilbert_bert_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 11 | 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
... |
Ayham/distilbert_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 5 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-cartpole
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: me... |
Ayham/roberta_bert_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 12 | 2023-03-15T13:54:42Z | ---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain ๐ค"
datasets:
- aszfcxcgszdx/autotrain-data-multi-lingual-summarization
co2_eq_emissions:
emissions: 13.328572874208332
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 41234106312
- CO2 Emissions (i... |
Ayham/roberta_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... | 4 | null | ---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain ๐ค"
datasets:
- aszfcxcgszdx/autotrain-data-multi-lingual-summarization
co2_eq_emissions:
emissions: 12.703463244389663
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 41234106313
- CO2 Emissions (i... |
Ayham/roberta_gpt2_new_max64_summarization_cnndm | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | ---
language:
- uz
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access ... |
Ayham/roberta_gpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 31 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: clinico-xlm-roberta-finetuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it,... |
Ayham/xlnet_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 13 | null | ---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-CartPole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type:... |
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