modelId stringlengths 4 81 | tags list | pipeline_tag stringclasses 17
values | config dict | downloads int64 0 59.7M | first_commit timestamp[ns, tz=UTC] | card stringlengths 51 438k | embedding list |
|---|---|---|---|---|---|---|---|
AmirBialer/amirbialer-Classifier | [] | null | {
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"num_beams... | 0 | null | ---
license: cc-by-nc-nd-4.0
---
This model is a multi-class classifier, model fine-tuned using the model 'bert-base-uncased'.
It is built around a large corpus of Twitter users' metadata.
It filters the data into 3 main categories - (1) Non-ExpertUser (2) ExpertUser (3) Other.
The aim of this project was to find ... | [
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Andranik/TestQA2 | [
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"no_re... | 8 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
config:... | [
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Andranik/TestQaV1 | [
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"no_re... | 4 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
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AndrewNLP/redditDepressionPropensityClassifiers | [] | null | {
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license: unknown
language:
- pt
tags:
- legal
---
**How to use:**
```python
>>> from transformers import AutoTokenizer, AutoModelForMaskedLM
>>> tokenizer = AutoTokenizer.from_pretrained("mynoguti/BERTimbau_Legal")
>>> model = AutoModelForMaskedLM.from_pretrained("mynoguti/BERTimbau_Legal")
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Andrey1989/mbart-finetuned-en-to-kk | [] | null | {
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license: openrail
---
# Model Card for Model ID
这个模型是用来跑图的
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/modelcard_template.md?plain=1).
# Model Details
## Model Des... | [
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Andrey1989/mbert-finetuned-ner | [
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"license:apache-2.0",
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"no_repeat... | 12 | 2023-02-06T13:22:15Z |
---
language: en
---
<p align="center">
<img src="https://doctr-static.mindee.com/models?id=v0.3.1/Logo_doctr.gif&src=0" width="60%">
</p>
**Optical Character Recognition made seamless & accessible to anyone, powered by TensorFlow 2 & PyTorch**
## Task: recognition
https://github.com/mindee/doctr
### Example usag... | [
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Andrija/SRoBERTa-base | [
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language:
- en
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- figfig/restaurant_order_test
metrics:
- wer
model-index:
- name: restaurant_test_model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: te... | [
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Ann2020/rubert-base-cased-sentence-finetuned-ner_tags | [] | null | {
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license: gpl-2.0
datasets:
- pavanBuduguppa/abcdv1.1_nsp
language:
- en
library_name: transformers
tags:
- contactCenter
- chat
- digital
---
# 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 ... | [
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AnnettJaeger/AnneJae | [] | null | {
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license: apache-2.0
tags:
- generated_from_trainer
- medical
model-index:
- name: stop_reasons_classificator_multilabel
results: []
datasets:
- opentargets/clinical_trial_reason_to_stop
language:
- en
metrics:
- accuracy
library_name: transformers
widget:
- text: "Study stopped due to problems to recruit patien... | [
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Anomic/DialoGPT-medium-loki | [] | null | {
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"num_beams... | 0 | null | ---
license: cc-by-4.0
tags:
- generated_from_trainer
model-index:
- name: translated_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. -->
# translated_model
T... | [
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AnonARR/qqp-bert | [
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"bert",
"text-classification",
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] | text-classification | {
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"no_rep... | 38 | null | ---
language:
- en
pipeline_tag: token-classification
tags:
- medical
---
Protected health information (PHI) anonymization tool. Fine-tuned on the [i2b2 2014 training dataset](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4989908/) from the pretrained `roberta-base` model.
Anonymizes according to the i2b2 2014 standa... | [
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Anonymous/ReasonBERT-BERT | [
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"bert",
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"transformers"
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tags:
- nagatoro
- hayase nagatoro
- makima
- nazuna nanakusa
- lora
---
https://civitai.com/models/6060/nagatoro-hayase-ti NOT LORA. THATS TI
https://civitai.com/models/5662/nazuna-nanakusa-call-of-the-night-lora
https://civitai.com/models/5373/makima-chainsaw-man-lora | [
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AnonymousNLP/pretrained-model-1 | [
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"no_repeat_ngram... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: bert-finetuned-ner-per-v5
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. -->
# bert-fin... | [
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0... |
AnonymousNLP/pretrained-model-2 | [
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"no_repeat_ngram... | 4 | 2023-02-06T15:16:33Z | ---
language:
- en
pipeline_tag: token-classification
tags:
- medical
---
Protected health information (PHI) anonymization tool. Fine-tuned on the [i2b2 2014 training dataset](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4989908/) from the pretrained `bert-base-cased` model.
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AnonymousSub/AR_EManuals-BERT | [
"pytorch",
"bert",
"feature-extraction",
"transformers"
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"no_repeat_ngram_size": nul... | 5 | null | ---
license: apache-2.0
tags:
- setfit
- sentence-transformers
- text-classification
pipeline_tag: text-classification
---
# fathyshalab/massive-roberta
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot lear... | [
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tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: cartpole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
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"no_repeat_ngram_size... | 4 | null | ---
license: apache-2.0
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This is a finetuned DeBERTav3 model from https://huggingface.co/sileod/deberta-v3-base-tasksource-nli.
# Model Details
This model was finetuned on policy data related to the rules laid out in the Sparr... | [
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AnonymousSub/AR_rule_based_roberta_twostagetriplet_epochs_1_shard_10 | [
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"no_repeat_ngram_size... | 2 | 2023-02-06T16:05:27Z | ---
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
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AnonymousSub/AR_specter | [
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---
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... | [
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AnonymousSub/SR_rule_based_roberta_hier_quadruplet_epochs_1_shard_10 | [
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---
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
language: ru
datasets:
- lmqg/qg_ruquad
pipeline_tag: text2text-generation
tags:
- question generation
- answer extraction
widget:
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AnonymousSub/SR_rule_based_roberta_hier_triplet_epochs_1_shard_1 | [
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tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter-PLE-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE... | [
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"... | 26 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-base
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_pfs
type: rishabhjain16/infer_pfs
config: en
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AnonymousSub/declutr-techqa | [
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"no_re... | 5 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-base.en
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: rishabhjain16/infer_pfs
type: rishabhjain16/infer_pfs
config: en
... | [
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AnonymousSub/rule_based_bert_hier_diff_equal_wts_epochs_1_shard_1 | [
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---
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... | [
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pipeline_tag: sentence-similarity
tags:
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---
# {MODEL_NAME}
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pipeline_tag: sentence-similarity
tags:
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---
# {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... | [
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pipeline_tag: sentence-similarity
tags:
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---
# {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... | [
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AnonymousSub/rule_based_bert_triplet_epochs_1_shard_10 | [
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pipeline_tag: sentence-similarity
tags:
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---
# {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... | [
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AnonymousSub/rule_based_bert_triplet_epochs_1_shard_1_wikiqa | [
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pipeline_tag: sentence-similarity
tags:
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---
# {MODEL_NAME}
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AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1 | [
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pipeline_tag: sentence-similarity
tags:
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---
# {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... | [
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AnonymousSub/rule_based_hier_triplet_epochs_1_shard_10 | [
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pipeline_tag: sentence-similarity
tags:
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---
# {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... | [
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AnonymousSub/rule_based_roberta_hier_quadruplet_0.1_epochs_1_shard_1 | [
"pytorch",
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"no_repeat_ngram_size... | 6 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: poetry-gpt2-large-no-hoel_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. -->
# poetry-gpt2-la... | [
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AnonymousSub/rule_based_roberta_hier_quadruplet_0.1_epochs_1_shard_1_squad2.0 | [
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"transformers",
"autotrain_compatible"
] | question-answering | {
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"no_re... | 4 | null | ---
language: en
license: mit
tags:
- vision
- image-to-text
- image-captioning
- visual-question-answering
pipeline_tag: image-to-text
inference: false
---
# BLIP-2, Flan T5-xl, pre-trained only
BLIP-2 model, leveraging [Flan T5-xl](https://huggingface.co/google/flan-t5-xl) (a large language model).
It was introduce... | [
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"no_repeat_ngram_size... | 1 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
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AnonymousSub/rule_based_roberta_twostage_quadruplet_epochs_1_shard_1 | [
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license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: khachouni/my_awesome_qa_model
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. -->
# khac... | [
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0.0509050153195858,
0.006294628139585257,
-0.0145160723477602,
0.00539714191108942,
0.032760... |
AnonymousSub/rule_based_roberta_twostagetriplet_hier_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": {
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"max_length": null,
"min_length": null,
"... | 23 | 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... | [
-0.021278029307723045,
-0.0055296230129897594,
0.010750551708042622,
0.039559975266456604,
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0.006934410892426968,
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0.01048328634351492,
... |
AnonymousSub/rule_based_twostage_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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"min_length": null,
"no_repeat_ngram_size": nul... | 6 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
widget:
- text: duskgem
---
[![Open In Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e6725323046616365... | [
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-0.018255963921546936,
0.0313... |
ArBert/bert-base-uncased-finetuned-ner-gmm | [] | null | {
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"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
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0.029... |
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": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_... | 3 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71
... | [
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Aran/DialoGPT-medium-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 8 | 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
... | [
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Aran/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"no_repeat_ngram_size... | 8 | null | ---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
---
# Example Fine-Tuned Model for Unit 2 of the [Diffusion Models Class 🧨](https://github.com/huggingface/diffusion-models-class)
Describe your model here
## Usage
```python
from diffusers import DDPMPipeline
p... | [
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0.04... |
ArashEsk95/bert-base-uncased-finetuned-sst2 | [] | null | {
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"num_beams... | 0 | null | Please refer to [flaim](https://github.com/bobmcdear/flaim) for sample usage and more information.
| [
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0.... |
Aravinth/test | [] | null | {
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"num_beams... | 0 | null | Please refer to [flaim](https://github.com/bobmcdear/flaim) for sample usage and more information.
| [
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0.... |
ArcQ/gpt-experiments | [] | null | {
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"num_beams... | 0 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
widget:
- text: duskspider
---
[![Open In Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e6725323046616... | [
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-0.019071592018008232,
0.03760... |
AriakimTaiyo/DialoGPT-small-Kumiko | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
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"min_length": null,
"no_repeat_ngram_size... | 11 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-Pixelcopter_v2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
... | [
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-0.0... |
AriakimTaiyo/DialoGPT-small-Rikka | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
license: creativeml-openrail-m
language:
- en
tags:
- art
---
# In short,
- FaceBomb : Covers from anime to 2.5D style. Suited for general use.
- recipe : 0.5((0.5(AbyssOrangeMix2_hard) + 0.5(pastelmix-better-vae-fp32)) + 0.5(CounterfeitV25_25)) + 0.5(dalcefoV3Painting_dalcefoV3Painting)
- ColorBomb : FaceBomb ... | [
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0.0393... |
Arina/Erine | [] | null | {
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"num_beams... | 0 | null | ---
library_name: rl-algo-impls
tags:
- Acrobot-v1
- ppo
- deep-reinforcement-learning
- reinforcement-learning
model-index:
- name: ppo
results:
- metrics:
- type: mean_reward
value: -70.5 +/- 9.68
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
... | [
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... |
ArvinZhuang/BiTAG-t5-large | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"T5ForConditionalGeneration"
],
"model_type": "t5",
"task_specific_params": {
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},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 200,
"min_length": 30,
"no_repeat_ngram_s... | 4 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
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0.02509123831987381,... |
Ashagi/Ashvx | [] | null | {
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"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... | [
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0.... |
AshiNLP/Bert_model | [] | null | {
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"num_beams... | 0 | 2023-02-07T01:25:17Z | ---
library_name: rl-algo-impls
tags:
- CartPole-v1
- ppo
- deep-reinforcement-learning
- reinforcement-learning
model-index:
- name: ppo
results:
- metrics:
- type: mean_reward
value: 500.0 +/- 0.0
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
... | [
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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": {
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},
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"min_length": null,
"no_repeat_ngram_size... | 3 | 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... | [
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0.... |
Ashl3y/model_name | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
library_name: rl-algo-impls
tags:
- QbertNoFrameskip-v4
- ppo
- deep-reinforcement-learning
- reinforcement-learning
model-index:
- name: ppo
results:
- metrics:
- type: mean_reward
value: 13079.69 +/- 3555.52
name: mean_reward
task:
type: reinforcement-learning
name: reinforceme... | [
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Ashok/my-new-tokenizer | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
library_name: rl-algo-impls
tags:
- SpaceInvadersNoFrameskip-v4
- ppo
- deep-reinforcement-learning
- reinforcement-learning
model-index:
- name: ppo
results:
- metrics:
- type: mean_reward
value: 1023.12 +/- 348.15
name: mean_reward
task:
type: reinforcement-learning
name: reinf... | [
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0.051857978105545044,
0.02909100241959095,
-0.025451550260186195,
-0.004863773938268423,
... |
AshtonBenson/DialoGPT-small-quentin-coldwater | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
library_name: rl-algo-impls
tags:
- BreakoutNoFrameskip-v4
- ppo
- deep-reinforcement-learning
- reinforcement-learning
model-index:
- name: ppo
results:
- metrics:
- type: mean_reward
value: 383.31 +/- 42.47
name: mean_reward
task:
type: reinforcement-learning
name: reinforcemen... | [
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Ateeb/FullEmotionDetector | [
"pytorch",
"funnel",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"FunnelForSequenceClassification"
],
"model_type": "funnel",
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},
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"no... | 31 | null | ---
library_name: rl-algo-impls
tags:
- MountainCar-v0
- ppo
- deep-reinforcement-learning
- reinforcement-learning
model-index:
- name: ppo
results:
- metrics:
- type: mean_reward
value: -110.88 +/- 7.11
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learni... | [
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0.018897417932748795,
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-0.005037504713982344,
... |
Axon/resnet50-v1 | [
"dataset:ImageNet",
"arxiv:1512.03385",
"Axon",
"Elixir",
"license:apache-2.0"
] | null | {
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"num_beams... | 0 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Huggy
library_name: ml-agents
---
# **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Libra... | [
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Ayham/albert_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
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"EncoderDecoderModel"
],
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},
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"no_re... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: thanat/bert-finetuned-ner
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. -->
# thanat/b... | [
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0.032753560692071915,
... |
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"
],
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 11 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: Frozen... | [
-0.018093788996338844,
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0.05373752862215042,
-0.0027202749624848366,
-0.007278116419911385,
0.026136184111237526,
... |
Ayham/distilbert_gpt2_summarization_cnndm | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
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"max_length": null
},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 6 | 2023-02-07T03:20:43Z | ---
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
... | [
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0.017164893448352814,
0.0... |
Ayham/distilbert_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
"model_type": "encoder-decoder",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 8 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3-Unit2-part2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.5... | [
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... |
Ayham/distilbert_roberta_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
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},
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"max_length": null,
"min_length": null,
"no_re... | 14 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
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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"
],
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},
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"min_length": null,
"no_re... | 4 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: 2-Taxi-v3-Unit2-part2
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7... | [
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Ayham/roberta_gpt2_summarization_xsum | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
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"EncoderDecoderModel"
],
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"no_re... | 6 | 2023-02-07T03:37:37Z | ---
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
... | [
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0.012063448317348957,
-0.00... |
Ayran/DialoGPT-small-gandalf | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
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"no_repeat_ngram_size... | 11 | null |
---
tags:
- TensorRT
- Text2Image
- Stable Diffusion
- Image2Image
- SDA
---
# burnerbaby/sds converted into TensorRT
<img src="https://i.imgur.com/fQS926g.png"></a>
Model converted from diffusers into TensorRT for accelerated inference up to 4x faster.
originally from: https://github.com/chavinlo/sda-node
This m... | [
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Ayta/Haha | [] | null | {
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"num_beams... | 0 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
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0.0165... |
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": {
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},
"summarization": {
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"max_length": null,
"min_length": null,
... | 8 | null | ---
license: mit
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-plotqa-trained
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
... | [
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0.0... |
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": {
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},
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... | 8 | 2023-02-07T05:46:07Z | ---
tags:
- espnet
- audio
- text-to-speech
language: jp
license: cc-by-4.0
---
## ESPnet2 TTS model
### `mio/tokiwa_midori`
This model was trained by mio using amadeus recipe in [espnet](https://github.com/espnet/espnet/).
... | [
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0.027882425114512444... |
BME-TMIT/foszt2oszt | [
"pytorch",
"encoder-decoder",
"text2text-generation",
"hu",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"EncoderDecoderModel"
],
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},
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"max_length": null,
"min_length": null,
"no_re... | 15 | null | ---
library_name: diffusers
pipeline_tag: text-to-image
tags:
- pepe
---
# How to use
***To prompt you can use the following code***
```python
from diffusers import StableDiffusionPipeline
model_path = "Dipl0/pepe-diffuser"
pipe = StableDiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16... | [
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0.... |
BSC-LT/roberta-large-bne-capitel-ner | [
"pytorch",
"roberta",
"token-classification",
"es",
"dataset:bne",
"dataset:capitel",
"arxiv:1907.11692",
"arxiv:2107.07253",
"transformers",
"national library of spain",
"spanish",
"bne",
"capitel",
"ner",
"license:apache-2.0",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"RobertaForTokenClassification"
],
"model_type": "roberta",
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},
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"max_length": null,
"min_length": null,
"no_... | 5 | null | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_wnli_128
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE WNLI
type: glu... | [
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0.0247451... |
BalajiSathesh/DialoGPT-small-harrypotter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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"max_length": 1000
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | 2023-02-07T07:43:46Z | ---
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 1024 dimensional dense vector space and can be used for tasks like cluste... | [
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Barbarameerr/Barbara | [] | null | {
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"num_beams... | 0 | 2023-02-07T07:58:29Z | ---
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
... | [
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0.... |
Barkavi/totto-t5-base-bert-score-121K | [
"pytorch",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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"T5ForConditionalGeneration"
],
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"no_repeat_ngram_s... | 51 | 2023-02-07T08:03:12Z | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue... | [
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Barleysack/klue-roberta-LSTM | [
"pytorch",
"roberta",
"transformers"
] | null | {
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"QAWithLSTMModel"
],
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"no_repeat_ngram_s... | 6 | 2023-02-07T08:11:24Z | ---
tags:
- generated_from_trainer
datasets:
- custom_squad_v2
model-index:
- name: kobigbird-pure45-94614916
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. -->
# k... | [
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BatuhanYilmaz/distilbert-base-uncased-finetuned-squad-d5716d28 | [
"pytorch",
"distilbert",
"fill-mask",
"en",
"dataset:squad",
"arxiv:1910.01108",
"transformers",
"question-answering",
"license:apache-2.0",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"DistilBertForMaskedLM"
],
"model_type": "distilbert",
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"no_repea... | 18 | 2023-02-07T08:34:07Z | ---
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... | [
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BatuhanYilmaz/mlm-finetuned-imdb | [] | null | {
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"num_beams... | 0 | 2023-02-07T08:42:08Z | ---
license: creativeml-openrail-m
language:
- en
--- | [
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BatuhanYilmaz/mt5-small-finetuned-amazonbooks-en-es | [] | null | {
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"num_beams... | 0 | 2023-02-07T08:42:22Z |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
library_name: ml-agents
---
# **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Age... | [
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Baybars/debateGPT | [] | null | {
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"num_beams... | 0 | 2023-02-07T08:43:04Z | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_rte_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
... | [
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Baybars/wav2vec2-xls-r-300m-cv8-turkish | [
"pytorch",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"common_voice",
"generated_from_trainer",
"hf-asr-leaderboard",
"robust-speech-event",
"license:apache-2.0"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
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"no_repeat_ngram_s... | 5 | 2023-02-07T08:57:46Z | ---
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- generated_from_trainer
datasets:
- squad
- newsqa
- LLukas22/cqadupstack
- LLukas22/fiqa
- LLukas22/scidocs
- deepset/germanquad
- LLukas22/nq
language:
- en
- de
---
# al... | [
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BeIR/query-gen-msmarco-t5-base-v1 | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
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],
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"no_repeat_ngram_s... | 1,816 | 2023-02-07T08:58:21Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: function-arg-swap-model-148k-files-365k-samples
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofr... | [
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BeIR/query-gen-msmarco-t5-large-v1 | [
"pytorch",
"jax",
"t5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
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],
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"no_repeat_ngram_s... | 1,225 | 2023-02-07T08:59:09Z | ---
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... | [
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Beatriz/model_name | [] | null | {
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"num_beams... | 0 | 2023-02-07T09:00:25Z | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### henry Dreambooth model trained by raw-vitor 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 [fast... | [
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Beelow/model | [] | null | {
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"num_beams... | 0 | 2023-02-07T09:07:10Z | ---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: distilbert_sa_GLUE_Experiment_logit_kd_data_aug_sst2_256
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE SST2
type: glu... | [
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Beri/legal-qa | [
"pytorch",
"roberta",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
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"no_re... | 10 | null | # CoCoSoDa: Effective Contrastive Learning for Code Search
Our approach adopts the pre-trained model as the base code/query encoder and optimizes it using multimodal contrastive learning and soft data augmentation.
CoCoSoDa is comprised of the following four components:
* **Pre-trained code/query encoder** captures ... | [
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BertChristiaens/EmojiPredictor | [
"pytorch",
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"token-classification",
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] | token-classification | {
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"DistilBertForTokenClassification"
],
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... | 6 | null | Flan-T5 model was trined with section 32 documents to build an extractive QA system | [
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Bharathdamu/wav2vec2-large-xls-r-300m-hindi2-colab | [] | null | {
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: finetuning-sentiment-model
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: test
... | [
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BigDaddyNe1L/Hhaa | [] | null | {
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"num_beams... | 0 | null | ---
library_name: transformers
---
# Example Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
```
from transformers import AutoTokenizer, T5ForConditionalGeneration
tokenizer = AutoTokenizer.from_pretrained("luqh... | [
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BigSalmon/FormalBerta2 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
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"no_repeat_ngra... | 16 | null | ---
license: mit
language:
- en
widget:
- text: >-
A nervous passenger is about to book a flight ticket, and he asks the
airlines' ticket seller, 'I hope your planes are safe. Do they have a good
track record for safety?' The airline agent replies, 'Sir, I can guarantee
you, we've never had a plane that... | [
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BigSalmon/FormalBerta3 | [
"pytorch",
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"transformers",
"autotrain_compatible"
] | fill-mask | {
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"no_repeat_ngra... | 4 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
... | [
-0.03883327916264534,
-0.016470717266201973,
-0.016190622001886368,
0.036888767033815384,
0.04956389591097832,
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0.05460241436958313,
0.024349750950932503,
-0.034677959978580475,
0.016577262431383133,
... |
BigSalmon/FormalRobertaa | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 5 | null |
---
tags:
- 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... | [
-0.02202409878373146,
-0.005268098786473274,
0.010718973353505135,
0.03941293805837631,
0.03212668001651764,
0.014989905059337616,
-0.02892160788178444,
-0.016275953501462936,
-0.016584137454628944,
0.06172987446188927,
0.006316629704087973,
0.0013960719807073474,
0.010946226306259632,
0.0... |
BigSalmon/FormalRobertaaa | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 12 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: result
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. -->
# result
This model is a fine-tuned ... | [
-0.03478384390473366,
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0.03553566709160805,
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0.05981089174747467,
0.03329666703939438,
-0.024690864607691765,
0.01066520344465971,
0.03... |
BigSalmon/GPT2HardArticleEasyArticle | [
"pytorch",
"jax",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 7 | null |
---
tags:
- unity-ml-agents
- ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-SnowballTarget
library_name: ml-agents
---
# **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget** using... | [
-0.03215588629245758,
-0.002509060315787792,
-0.019616879522800446,
0.05111612007021904,
0.039448775351047516,
0.025832924991846085,
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0.04790657386183739,
0.023311831057071686,
-0.005146805662661791,
0.019715825095772743,
... |
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: openrail
language:
- en
pipeline_tag: image-segmentation
---
<a href="https://www.buymeacoffee.com/s3nh"><img src="https://www.buymeacoffee.com/assets/img/guidelines/download-assets-sm-1.svg" alt=""></a>
<img src = 'https://images.unsplash.com/photo-1438761681033-6461ffad8d80?ixlib=rb-4.0.3&ixid=MnwxMjA... | [
-0.02514035999774933,
-0.022714005783200264,
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0.04723486676812172,
0.053744327276945114,
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0.014575067907571793,
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0.05999179556965828,
0.016721829771995544,
0.008993334136903286,
-0.009263736195862293,
0.041... |
BigSalmon/GPTHeHe | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
tags:
- Pixelcopter-PLE-v0
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: Reinforce-1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Pixelcopter-PLE-v0
type: Pixelcopter-PLE-v0
metrics:
... | [
-0.04173116013407707,
0.015480972826480865,
0.014218862168490887,
0.01741831749677658,
0.049608953297138214,
-0.013611209578812122,
-0.021830538287758827,
-0.024461116641759872,
-0.018837815150618553,
0.0683167576789856,
0.03802097216248512,
-0.006875178776681423,
0.012000123038887978,
-0.... |
BigSalmon/GPTNeo350MInformalToFormalLincoln2 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 8 | null | ---
license: apache-2.0
---
This model is trained on `LibriSpeech` dataset and can only be used for English ASR.
It's a very small model, which means it is suitable for embedded devices. | [
-0.0579301081597805,
0.026400521397590637,
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0.027843235060572624,
0.06081079691648483,
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0.06352023780345917,
0.020340127870440483,
-0.020607247948646545,
0.03290492296218872,
0.0019... |
BigSalmon/InformalToFormalLincoln16 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 8 | null | ---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
---
### Website_design_mockup_1 Dreambooth model trained by JacobPerera with [TheLastBen's fast-DreamBooth](https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb) notebook
Test the concept v... | [
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0.04510689526796341,
0.041898686438798904,
0.015368959866464138,
-0.024452298879623413,
... |
BigSalmon/MrLincoln6 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
tags:
- generated_from_trainer
model-index:
- name: rabbiberel-finetuned-xsum
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. -->
# rabbiberel-finetuned-xsum
Th... | [
-0.015343488194048405,
-0.0027771126478910446,
-0.007869078777730465,
0.017634013667702675,
0.02847851626574993,
0.027948027476668358,
-0.0013361937599256635,
-0.02134331874549389,
-0.03998265787959099,
0.05434691533446312,
0.03944568336009979,
-0.009046414867043495,
0.011454788967967033,
... |
BigSalmon/MrLincoln8 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 12 | null | ---
license: mit
tags:
- generated_from_trainer
model-index:
- name: codeparrot-ds-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. -->
# codeparrot-ds-1
This mode... | [
-0.03676827624440193,
-0.01780342310667038,
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0.04109150916337967,
0.03598760440945625,
0.016317008063197136,
-0.006138154771178961,
0.0032591947820037603,
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0.050506897270679474,
0.020295919850468636,
-0.02148050256073475,
-0.004254578147083521,
0.... |
Blerrrry/Kkk | [] | 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:
- imagefolder
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-pt22k-ft22k-finetunedt
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
c... | [
0.0036304614041000605,
-0.009106624871492386,
-0.003084068652242422,
0.030433138832449913,
0.03136981651186943,
0.006527227815240622,
0.0034387323539704084,
-0.0022792713716626167,
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0.04059039056301117,
0.004267982207238674,
-0.012212752364575863,
0.012469310313463211,
... |
BlightZz/MakiseKurisu | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
"max_length": 1000
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 14 | null | # Wav2Vec2-XLS-R-300-GL
Model train with common voice 12.0 in Galician.
| [
-0.03614562004804611,
-0.026943299919366837,
0.0008650374365970492,
0.03521876037120819,
0.07501013576984406,
0.027287429198622704,
-0.006192052736878395,
0.03505638986825943,
-0.022954057902097702,
0.013233248144388199,
0.032494042068719864,
-0.036617252975702286,
-0.018173685297369957,
0... |
Bloodwarrior/Chikfalay | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
language:
- tr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-tr-demo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
datase... | [
-0.03408776596188545,
-0.0019359900616109371,
-0.021438946947455406,
0.03737524896860123,
0.05842607840895653,
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0.05235890671610832,
0.02620505727827549,
-0.03174669295549393,
0.00571874575689435,
0.02772... |
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