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 |
|---|---|---|---|---|---|---|---|
AnonymousSub/declutr-model-emanuals | [
"pytorch",
"roberta",
"fill-mask",
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tags:
- generated_from_trainer
model-index:
- name: kcbert-large-finetuned-unsmile
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. -->
# kcbert-large-finetuned-u... | [
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AnonymousSub/rule_based_bert_hier_diff_equal_wts_epochs_1_shard_10 | [
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widget:
- text: "PROCEDURE: Chest xray. COMPARISON: last seen on 1/1/2020 and also record dated of March 1st, 2019. FINDINGS: patchy airspace opacities. IMPRESSION: The results of the chest xray of January 1 2020 are the most concerning ones. The patient was transmitted to another service of UH Medical Center under... | [
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widget:
- text: "PROCEDURE: Chest xray. COMPARISON: last seen on 1/1/2020 and also record dated of March 1st, 2019. FINDINGS: patchy airspace opacities. IMPRESSION: The results of the chest xray of January 1 2020 are the most concerning ones. The patient was transmitted to another service of UH Medical Center under... | [
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AnonymousSub/rule_based_bert_triplet_epochs_1_shard_1_squad2.0 | [
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tags:
- generated_from_trainer
model-index:
- name: results
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. -->
# results
This model was trained from scratch on... | [
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AnonymousSub/rule_based_hier_quadruplet_0.1_epochs_1_shard_1_squad2.0 | [
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"no_repeat_n... | 4 | null | ---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: ksabeh/roberta-base-attribute-correction-mlm-titles-2
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 com... | [
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AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1 | [
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license: gpl-2.0
language: ar
---
A model which is jointly trained and fine-tuned on Quran, Saheefa and nahj-al-balaqa. All Datasets are available [Here](https://github.com/language-ml/course-nlp-ir-1-text-exploring/tree/main/exploring-datasets/religious_text). Code will be available soon ...
Some Examples for fil... | [
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AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_10 | [
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license: mit
---
Classifier of news affecting the stock price in the next 10 minutes | [
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AnonymousSub/rule_based_hier_quadruplet_epochs_1_shard_1_wikiqa | [
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"no_rep... | 30 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- metrics:
- type: mean_reward
value: 270.09 +/- 19.04
name: mean_reward
task:
type: reinforcement-learning
name: re... | [
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0... |
AnonymousSub/rule_based_hier_triplet_0.1_epochs_1_shard_1_squad2.0 | [
"pytorch",
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"no_repeat_n... | 2 | null | ---
tags:
- generated_from_trainer
datasets:
- uob_singlish
model-index:
- name: malaya-speech_Mrbrown_finetune1
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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AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1 | [
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tags:
- hf_diffuse
---
# Dummy diffusion model following architecture of https://github.com/lucidrains/denoising-diffusion-pytorch
Run the model as follows:
```python
from diffusers import UNetModel, GaussianDiffusion
import torch
# 1. Load model
unet = UNetModel.from_pretrained("fusing/ddpm_dummy")
# 2. Do on... | [
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AnonymousSub/rule_based_hier_triplet_epochs_1_shard_10 | [
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license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ksabeh/bert-base-uncased-mlm-electronics-attribute-correction
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then ... | [
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AnonymousSub/rule_based_hier_triplet_epochs_1_shard_1_squad2.0 | [
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"no_repeat_n... | 2 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bart-paraphrase-finetuned-xsum-v5
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. -->
# b... | [
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AnonymousSub/rule_based_only_classfn_epochs_1_shard_10 | [
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"no_repeat_ngram_size": nul... | 7 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- metrics:
- type: mean_reward
value: 602.00 +/- 193.99
name: mean_reward
task:
type: reinforcement-learning
... | [
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AnonymousSub/rule_based_only_classfn_twostage_epochs_1_shard_1 | [
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"no_repeat_ngram_size": nul... | 10 | 2022-06-09T09:56:35Z |
# Visual Semantic with BERT-CNN
This model can be used to assign an object-to-caption semantic relatedness score, which is valuable for (1) caption diverse re-ranking (this work),
and (2) (as an application)
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AnonymousSub/rule_based_roberta_bert_quadruplet_epochs_1_shard_10 | [
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tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
task:
type: reinforcement-learning
name: reinforc... | [
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"no_re... | 2 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
task:
type: reinforcement-learning
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AnonymousSub/rule_based_roberta_bert_quadruplet_epochs_1_shard_1_wikiqa | [
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"... | 23 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/osanseviero/1654769951427/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
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license: apache-2.0
tags:
- generated_from_trainer
datasets:
- uob_singlish
model-index:
- name: wav2vec2-xls-r-300m_Mrbrown_finetune1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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library_name: keras
tags:
- SpeakerRecognition
- Fast Fourier Transform (FFT)
- Convnet
- speech-recordings
- SpeechClassification
---
## Model description
This model helps to classify speakers from the frequency domain representation of speech recordings, obtained via Fast Fourier Transform (FFT).
The model is cr... | [
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license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: TEdetection_distiBERT_mLM_V2_shuffleplus3
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.... | [
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AnonymousSub/rule_based_roberta_twostagetriplet_epochs_1_shard_1_squad2.0 | [
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"no_re... | 4 | null | ---
language: zh
tags:
- summarization
inference: False
---
# Randeng-Pegasus-523M-Chinese
- Github: [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM/blob/main/fengshen/examples/pegasus/pretrain_pegasus.sh)
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AnonymousSub/rule_based_roberta_twostagetriplet_hier_epochs_1_shard_1_squad2.0 | [
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language: zh
tags:
- summarization
- chinese
inference: False
---
# Randeng-Pegasus-238M-Chinese
- Github: [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM/blob/main/fengshen/examples/pegasus/pretrain_pegasus.sh)
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"... | 23 | null | ---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
task:
type: reinforcement-learning
name: reinforc... | [
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AnonymousSub/specter-bert-model | [
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tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- qualitydatalab/autotrain-data-car-review-project
co2_eq_emissions: 0.061185706621337065
---
# Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 966432120
- CO2 Emissions (in grams): 0.0611857066213370... | [
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Anorak/nirvana | [
"pytorch",
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"unk",
"dataset:Anorak/autonlp-data-Niravana-test2",
"transformers",
"autonlp",
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"n... | 7 | 2022-06-09T13:23:24Z | ---
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
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AnthonyNelson/DialoGPT-small-ricksanchez | [
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"no_repeat_ngram_size... | 12 | 2022-06-09T13:26:40Z | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- metrics:
- type: mean_reward
value: 7.56 +/- 2.71
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
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ArJakusz/DialoGPT-small-stark | [
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"no_repeat_ngram_size... | 8 | 2022-06-09T15:02:08Z | ---
tags:
- DNA
license: mit
---
## MiniDNA model
This is a distilled version of [DNABERT](https://github.com/jerryji1993/DNABERT) by using MiniLM technique. It has a BERT architecture with 6 layers and 768 hidden units, pre-trained on 6-mer DNA sequences. For more details on the pre-training scheme and methods, pl... | [
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ArJakusz/DialoGPT-small-starky | [] | null | {
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library_name: keras
tags:
- computer-vision
- generative
- variational-autoencoder
- vq-vae
---
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training Metrics
Model history needed
## Model Plot
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Archie/myProject | [] | null | {
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"num_beams... | 0 | 2022-06-09T16:11:52Z | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
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Arnold/wav2vec2-hausa-demo-colab | [] | null | {
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"num_beams... | 0 | 2022-06-09T17:06:01Z | ---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de-fr
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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AshtonBenson/DialoGPT-small-quentin-coldwater | [] | null | {
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"num_beams... | 0 | 2022-06-09T18:33:18Z | ---
language: en
thumbnail: http://www.huggingtweets.com/midudev/1654800505422/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
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Augustvember/WokkaBot | [] | null | {
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"num_beams... | 0 | 2022-06-09T20:06:56Z | ---
tags:
- generated_from_keras_callback
model-index:
- name: CAP_coded_US_Congressional_bills
results: []
widget:
- text: "A bill to prohibt discrimination in employment because of race, color, religion, national origin, or ancestry"
example_title: "example 1"
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Augustvember/WokkaBot99 | [] | null | {
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license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
model-index:
- name: ner_marathi_bert
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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AvatarXD/DialoGPT-medium-Blitzo | [
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"no_repeat_ngram_size... | 14 | null | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
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value: 374.00 +/- 214.89
name: mean_reward
task:
type: reinforcement-learning
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Axon/resnet18-v1 | [
"dataset:ImageNet",
"arxiv:1512.03385",
"Axon",
"Elixir",
"license:apache-2.0"
] | null | {
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tags:
- diffusion
license: mit
---
Latent Diffusion
**Paper**: [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/abs/2112.10752)
**Abstract**:
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state... | [
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0.06792408227920532,
0.03565191850066185,
-0.014473430812358856,
-0.002867086324840784,
... |
Axon/resnet50-v1 | [
"dataset:ImageNet",
"arxiv:1512.03385",
"Axon",
"Elixir",
"license:apache-2.0"
] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NLP-CIC-WFU_Clinical_Cases_NER_Paragraph_Tokenized_mBERT_cased_fine_tuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access... | [
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Ayato/DialoGTP-large-Yuri | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- conversational
---
# Omar Dialog GPT Model Medium 10
# Trained on discord channels:
# half of Dragalia chat | [
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Ayham/albert_gpt2_Full_summarization_cnndm | [
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"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
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"no_re... | 9 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: emotion
type: emotion
args: default... | [
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Ayham/bert_distilgpt2_summarization_cnn_dailymail | [
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"dataset:cnn_dailymail",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
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],
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"no_re... | 6 | 2022-06-10T00:30:02Z | ---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-base-cased-finetuned-filtered-0609
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread... | [
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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": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 12 | null | ---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: vit_test_1_95
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9501661062240601
---
# vit_test_1_95
Auto... | [
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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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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 4 | null | Task:
Given a set of input keywords, generate a corresponding text output for a section in the legal domain.
Dataset:
We used the Contract Understanding Atticus Dataset (CUAD).
It is a corpus of 13,000+ labels in 510 commercial legal contracts.
They have been manually labeled under the supervision of experienced law... | [
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Ayham/roberta_gpt2_summarization_xsum | [
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"encoder-decoder",
"text2text-generation",
"dataset:xsum",
"transformers",
"generated_from_trainer",
"autotrain_compatible"
] | text2text-generation | {
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"no_re... | 6 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- enoriega/odinsynth_dataset
model-index:
- name: rule_learning_margin_1mm
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... | [
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Ayou/chinese_mobile_bert | [
"pytorch",
"mobilebert",
"fill-mask",
"transformers",
"license:apache-2.0",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"MobileBertForMaskedLM"
],
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},
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"min_length": null,
"no_repea... | 16 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- metrics:
- type: mean_reward
value: 7.54 +/- 2.73
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Tax... | [
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Azaghast/DistilBART-SCP-ParaSummarization | [
"pytorch",
"bart",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"BartForConditionalGeneration"
],
"model_type": "bart",
"task_specific_params": {
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},
"summarization": {
"early_stopping": true,
"length_penalty": 2,
"max_length": 142,
"min_length": 56,
"no_repeat_ngr... | 8 | null | ---
language: zh
pipeline_tag: fill-mask
widget:
- text: "根据新闻报道，三大[MASK]数午后集体涨超1％。"
- text: "用各种途径支持中小[MASK]企业融资。"
tags:
- bert
license: apache-2.0
---
## Chinese DKPLM (Decomposable Knowledge-enhanced Pre-trained Language Model) for the financial domain
For Chinese natural language processing in specific domains, we ... | [
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Azizun/Geotrend-10-epochs | [
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"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
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"no_repeat... | 6 | null | ---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: MiniLM-L12-H384-uncased-mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics... | [
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Azura/data | [] | null | {
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"num_beams... | 0 | null | ---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-Taxi-v3
results:
- metrics:
- type: mean_reward
value: 7.56 +/- 2.71
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Tax... | [
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Backedman/DialoGPT-small-Anika | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
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},
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"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilrubert-2ndfinetune-epru
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 ... | [
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Battlehooks/distilbert-base-uncased-finetuned-squad | [] | null | {
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"num_beams... | 0 | 2022-06-10T12:19:45Z | ---
library_name: stable-baselines3
tags:
- Humanoid-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- metrics:
- type: mean_reward
value: 380.12 +/- 81.26
name: mean_reward
task:
type: reinforcement-learning
name: reinf... | [
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BatuhanYilmaz/bert-finetuned-mrpc | [] | null | {
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tags:
- conversational
---
# House MD DialoGPT Model | [
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BatuhanYilmaz/bert-finetuned-ner | [] | null | {
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"num_beams... | 0 | 2022-06-10T12:24:12Z | ---
language: en
datasets:
- ccdv/pubmed-summarization
license: apache-2.0
---
## Introduction
[Google's LongT5: Efficient Text-To-Text Transformer for Long Sequences](https://arxiv.org/pdf/2112.07916.pdf) introduced as an extension of a successful [T5 model](https://arxiv.org/pdf/1910.10683.pdf).
This is an uno... | [
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BatuhanYilmaz/bert-finetuned-nerxD | [] | null | {
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"num_beams... | 0 | 2022-06-10T12:36:40Z | ---
library_name: keras
tags:
- image-classification
- computer-vision
- consistency-regularization
- cifar10
---
## Model description
### Consistency training with supervision
[Keras Example Link](https://keras.io/examples/vision/consistency_training/)
In this example, we have trained an image classification model... | [
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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",
"task_specific_params": {
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},
"summarization": {
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"min_length": null,
"no_repea... | 18 | null | ---
library_name: keras
tags:
- image-classification
- computer-vision
- consistency-regularization
- cifar10
---
## Model description
### Consistency training with supervision
[Keras Example Link](https://keras.io/examples/vision/consistency_training/)
In this example, we have trained an image classification model... | [
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BatuhanYilmaz/dummy-model | [
"tf",
"camembert",
"fill-mask",
"transformers",
"generated_from_keras_callback",
"license:mit",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"CamembertForMaskedLM"
],
"model_type": "camembert",
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_... | 6 | null | ---
tags:
- generated_from_trainer
datasets:
- ydshieh/coco_dataset_script
model-index:
- name: clip-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, then remove this comment.... | [
-0.03780701756477356,
-0.0044204359874129295,
0.0022593941539525986,
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0.04638344421982765,
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-0.025450002402067184,
0.01674862764775753,
0.05... |
BatuhanYilmaz/marian-finetuned-kde4-en-to-fr | [] | null | {
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},
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"num_beams... | 0 | 2022-06-10T12:49:12Z | ---
language:
- "ja"
tags:
- "japanese"
- "masked-lm"
license: "cc-by-sa-4.0"
pipeline_tag: "fill-mask"
mask_token: "[MASK]"
widget:
- text: "日本に着いたら[MASK]を訪ねなさい。"
---
# deberta-large-japanese-unidic
## Model Description
This is a DeBERTa(V2) model pre-trained on 青空文庫 texts with BertJapaneseTokenizer. You can fine-t... | [
-0.0052348352037370205,
-0.05038422718644142,
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0.0852920264005661,
0.01137905940413475,
-0.010146328248083591,
0.010935906320810318,
0.04... |
BatuhanYilmaz/mlm-finetuned-imdb | [] | null | {
"architectures": null,
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},
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"max_length": null,
"min_length": null,
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"num_beams... | 0 | null | ---
language:
- "ja"
tags:
- "japanese"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "cc-by-sa-4.0"
pipeline_tag: "token-classification"
widget:
- text: "国境の長いトンネルを抜けると雪国であった。"
---
# deberta-large-japanese-unidic-luw-upos
## Model Description
This is a DeBERTa... | [
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0.078757643699646,
0.006049085408449173,
-0.004301948007196188,
0.016084490343928337,
0.0... |
Baybars/wav2vec2-xls-r-1b-turkish | [
"pytorch",
"tensorboard",
"wav2vec2",
"automatic-speech-recognition",
"tr",
"dataset:common_voice",
"transformers",
"common_voice",
"generated_from_trainer"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 13 | null | ---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
model-index:
- name: camembert-base-finetuned-LineCause
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 r... | [
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0.05201466754078865,
0.028036145493388176,
-0.024147292599081993,
0.0060418774373829365,
0.0... |
Bharathdamu/wav2vec2-large-xls-r-300m-hindi3-colab | [] | null | {
"architectures": null,
"model_type": null,
"task_specific_params": {
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},
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"min_length": null,
"no_repeat_ngram_size": null,
"num_beams... | 0 | null | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# {MODEL_NAME}
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like cluster... | [
-0.03682786226272583,
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0.08364398777484894,
0.03946809098124504,
0.013144438154995441,
0.00234610796906054,
0.04092745... |
Bharathdamu/wav2vec2-model-hindi-stt | [] | null | {
"architectures": null,
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},
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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:
- metrics:
- type: mean_reward
value: 817.50 +/- 327.32
name: mean_reward
task:
type: reinforcement-learning
... | [
-0.03956395387649536,
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0.017721308395266533,
0.... |
BigSalmon/BestMask2 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible",
"has_space"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
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},
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"min_length": null,
"no_repeat_ngra... | 10 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/smallmutuals/1654888348503/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; wi... | [
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-0.003713704412803054,
-0.018042702227830887,
... |
BigSalmon/FormalBerta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngra... | 10 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/jana_aych_ess/1654888920998/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... | [
-0.0029817395843565464,
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0.06494694203138351,
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0.029858294874429703,
0.01153553370386362,
-0.0070137339644134045,
-0.008159758523106575,
... |
BigSalmon/FormalBerta3 | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 4 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: TEdetection_distilBERT_mLM_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. -->
# TEde... | [
-0.02398531883955002,
-0.01104021817445755,
-0.007549268659204245,
0.01460205763578415,
0.02200576849281788,
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0.05224483832716942,
0.012840846553444862,
-0.026822853833436966,
0.014250497333705425,
0.05... |
BigSalmon/GPT2HardandEasy | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4... | [
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0.03463543578982353,
-0.0018815075745806098,
-0.003238419070839882,
0.0034772397484630346... |
BigSalmon/GPTNeo350MInformalToFormalLincoln4 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 11 | null | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should p... | [
-0.02729734592139721,
0.029358450323343277,
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0.027149004861712456,
0.02... |
BigSalmon/GPTNeo350MInformalToFormalLincoln6 | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers",
"has_space"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 14 | null | ---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: TEdetection_distiBERT_NER_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. -->
# TEdet... | [
-0.021859467029571533,
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0.0065255905501544476,
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0.05248413234949112,
0.013588898815214634,
-0.025227177888154984,
0.007429592311382294,
0... |
BigSalmon/GoodMaskResults | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 9 | null | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilrubert-tiny-2ndfinetune-epru
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 re... | [
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0.06483796238899231,
0.02109134942293167,
-0.028656810522079468,
0.015080812387168407,
0.... |
BigSalmon/InformalToFormalLincoln22 | [
"pytorch",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 6 | null | ---
language: en
---
# LFTW R1 Target
The R1 Target model from [Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection](https://arxiv.org/abs/2012.15761)
## Citation Information
```bibtex
@inproceedings{vidgen2021lftw,
title={Learning from the Worst: Dynamically Generated Dataset... | [
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0.009225691668689251,
... |
BigSalmon/MrLincoln2 | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 9 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/jedwill1999/1654902604867/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; wid... | [
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... |
BigSalmon/NEO125InformalToFormalLincoln | [
"pytorch",
"gpt_neo",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPTNeoForCausalLM"
],
"model_type": "gpt_neo",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram... | 8 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/froliki2108/1654905851117/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; wid... | [
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0.03406117856502533,
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-0.01684706099331379,
... |
BigSalmon/ParaphraseParentheses | [
"pytorch",
"tensorboard",
"gpt2",
"text-generation",
"transformers"
] | text-generation | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
"task_specific_params": {
"conversational": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 10 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/tonebot_/1654906535396/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; width:... | [
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0.03497376665472984,
0.012250039726495743,
0.00008542139403289184,
-0.012154027819633484,
... |
BigSalmon/PhraseBerta | [
"pytorch",
"roberta",
"fill-mask",
"transformers",
"autotrain_compatible"
] | fill-mask | {
"architectures": [
"RobertaForMaskedLM"
],
"model_type": "roberta",
"task_specific_params": {
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},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngra... | 10 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: SCRATCH_ja-en_helsinki
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. -->
# SCRATCH_ja-e... | [
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0.012912871316075325,
0.05... |
BlightZz/DialoGPT-medium-Kurisu | [
"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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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngram_size... | 19 | null | ---
tags:
- conversational
---
# Harry Potter DialoGPT Model | [
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0.028363337740302086,
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0.010642281733453274,
0.0... |
Botslity/Bot | [] | null | {
"architectures": null,
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"num_beams... | 0 | null | ---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilrubert-tiny-2nd-finetune-epru
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 r... | [
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0.0... |
Branex/gpt-neo-2.7B | [] | null | {
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},
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"num_beams... | 0 | null | ---
language: es
tags:
- sagemaker
- vit
- ImageClassification
- generated_from_trainer
license: apache-2.0
datasets:
- cifar10
metrics:
- accuracy
model-index:
- name: vit_base-224-in21k-ft-cifar10
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: "Ci... | [
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0.... |
CALM/backup | [
"lean_albert",
"transformers"
] | null | {
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"LeanAlbertForPretraining",
"LeanAlbertForTokenClassification",
"LeanAlbertForSequenceClassification"
],
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"len... | 4 | null | 在bert-base-chinese基础上进行新闻语料库的增量预训练的模型，token采用的是bert-base-chinese
Model
模型导出时将生成 config.json 和 pytorch_model.bin 参数文件
Tokenizer
这是一个将纯文本转换为编码的过程。注意，Tokenizer 并不涉及将词转化为词向量的过程，仅仅是将纯文本分词，添加[MASK]标记、[SEP]、[CLS]标记，并转换为字典索引。Tokenizer 类导出时将分为三个文件
vocab.txt 词典文件，每一行为一个词或词的一部分
special_tokens_map.json 特殊标记的定义方式
tokenizer_config.j... | [
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0.... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-poetry | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:1905.05700",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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},
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"min_length": null,
"no_rep... | 42 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: ppo
results:
- metrics:
- type: mean_reward
value: 240.31 +/- 12.46
name: mean_reward
task:
type: reinforcement-learning
name: re... | [
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0.022118307650089264,
... |
CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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},
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"min_length": null,
"no_rep... | 73 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
met... | [
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0.0331... |
CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment | [
"pytorch",
"tf",
"bert",
"text-classification",
"ar",
"arxiv:2103.06678",
"transformers",
"license:apache-2.0"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
"model_type": "bert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_rep... | 574 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-ksponspeech
results: []
---
# wav2vec2-ksponspeech
This model is a fine-tuned version of [Wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results ... | [
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0... |
Canadiancaleb/DialoGPT-small-walter | [
"pytorch",
"gpt2",
"text-generation",
"transformers",
"conversational"
] | conversational | {
"architectures": [
"GPT2LMHeadModel"
],
"model_type": "gpt2",
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},
"summarization": {
"early_stopping": null,
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"min_length": null,
"no_repeat_ngram_size... | 13 | null | ---
tags:
- FrozenLake-v1-4x4
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- metrics:
- type: mean_reward
value: 0.78 +/- 0.41
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-learni... | [
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0.01985332742333412,
... |
Canadiancaleb/jessebot | [] | null | {
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},
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"num_beams... | 0 | null | This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/).
The model is trained using Hurricane Dorian 2019 event (training, development, and test data are used for training) from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRIS... | [
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0.01203409768640995,
0.04558... |
Canyonevo/DialoGPT-medium-KingHenry | [] | null | {
"architectures": null,
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},
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"num_beams... | 0 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: bert-finetuned-squad
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... |
Capreolus/bert-base-msmarco | [
"pytorch",
"tf",
"jax",
"bert",
"text-classification",
"arxiv:2008.09093",
"transformers"
] | text-classification | {
"architectures": [
"BertForSequenceClassification"
],
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},
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"no_rep... | 238 | 2022-06-11T20:30:24Z | This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/).
The model is trained using Hurricane Dorian 2019 event (training, development, and test data are used for training) from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRIS... | [
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0.04... |
Capreolus/birch-bert-large-msmarco_mb | [
"pytorch",
"tf",
"jax",
"bert",
"next-sentence-prediction",
"transformers"
] | null | {
"architectures": [
"BertForNextSentencePrediction"
],
"model_type": "bert",
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},
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"no_rep... | 1 | null | This model is a BERT-based Location Mention Recognition model that is adopted from the [TLLMR4CM GitHub](https://github.com/rsuwaileh/TLLMR4CM/).
The model is trained using Hurricane Dorian 2019 event (only the training data is used for training) from [IDRISI-R dataset](https://github.com/rsuwaileh/IDRISI) under the Ty... | [
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0... |
Capreolus/electra-base-msmarco | [
"pytorch",
"tf",
"electra",
"text-classification",
"arxiv:2008.09093",
"transformers"
] | text-classification | {
"architectures": [
"ElectraForSequenceClassification"
],
"model_type": "electra",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"... | 110 | null | ---
tags:
- FrozenLake-v1-4x4-4x4
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-slippery
results:
- metrics:
- type: mean_reward
value: 0.75 +/- 0.43
name: mean_reward
task:
type: reinforcement-learning
name: reinforcement-lear... | [
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0.020245622843503952,
... |
CarlosPR/mt5-spanish-memmories-analysis | [
"pytorch",
"mt5",
"text2text-generation",
"transformers",
"autotrain_compatible"
] | text2text-generation | {
"architectures": [
"MT5ForConditionalGeneration"
],
"model_type": "mt5",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no_repeat... | 7 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: music-generation
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. -->
# music-generation
... | [
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... |
Cdial/hausa-asr | [
"wav2vec2",
"automatic-speech-recognition",
"ha",
"dataset:mozilla-foundation/common_voice_8_0",
"transformers",
"mozilla-foundation/common_voice_8_0",
"generated_from_trainer",
"robust-speech-event",
"model_for_talk",
"hf-asr-leaderboard",
"license:apache-2.0",
"model-index"
] | automatic-speech-recognition | {
"architectures": [
"Wav2Vec2ForCTC"
],
"model_type": "wav2vec2",
"task_specific_params": {
"conversational": {
"max_length": null
},
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"max_length": null,
"min_length": null,
"no_repeat_ngram_s... | 8 | 2022-06-11T21:33:30Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-4000instances-opus-leaningRate2e-05-batchSize8-11-action-1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset... | [
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... |
dccuchile/albert-base-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
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"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 34 | null | ---
library_name: stable-baselines3
tags:
- Sokoban-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: PPO
results:
- metrics:
- type: mean_reward
value: -19.90 +/- 0.30
name: mean_reward
task:
type: reinforcement-learning
name: reinfor... | [
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0.... |
dccuchile/albert-base-spanish-finetuned-xnli | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 28 | null | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-4000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
da... | [
-0.012596742250025272,
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0.057346101850271225,
-0.00045957433758303523,
-0.010940049774944782,
-0.0055878083221614... |
dccuchile/albert-large-spanish-finetuned-ner | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
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},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 3 | 2022-06-11T22:22:14Z | ---
tags:
- conversational
---
#A Peter DialoGPT Model | [
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0.01502194069325924,
0.01589341275393963,
0.01577266864478588,
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0.008615351282060146,
0.03184... |
dccuchile/albert-tiny-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
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},
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"max_length": null,
"min_length": null,
"no... | 32 | null | ---
license: mit
datasets:
- MRBrainS18
language:
- en
metrics:
-
tags:
- MedicalNet
- medical images
- medical
- 3D
- Med3D
thumbnail: "https://github.com/Tencent/MedicalNet/blob/master/images/logo.png?raw=true"
---
# MedicalNet
This repository contains a Pytorch implementation of [Med3D: Transfe... | [
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0.... |
dccuchile/albert-tiny-spanish-finetuned-ner | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
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},
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"min_length": null,
"no_re... | 8 | null | Access to model Abhijnan/AxomiyaBERTa is restricted and you are not in the authorized list. Visit https://huggingface.co/Abhijnan/AxomiyaBERTa to ask for access. | [
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... |
dccuchile/albert-tiny-spanish-finetuned-qa-mlqa | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"AlbertForQuestionAnswering"
],
"model_type": "albert",
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},
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"max_length": null,
"min_length": null,
"no_repe... | 7 | null | ---
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- metrics:
- type: mean_reward
value: -140.18 +/- 41.67
name: mean_reward
task:
type: reinforcement-learning
name: r... | [
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0.022711241617798805,
0.0... |
dccuchile/albert-xlarge-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
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},
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"max_length": null,
"min_length": null,
"no... | 26 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/laserboat999/1654991516445/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; wi... | [
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0.001097365515306592,
-0.0187773909419775,
0.0310023... |
dccuchile/albert-xlarge-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
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},
"summarization": {
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"max_length": null,
"min_length": null,
"no... | 24 | null | ---
language: en
thumbnail: http://www.huggingtweets.com/cancer_blood69/1654992058711/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; ... | [
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-0.014080152846872807,
... |
dccuchile/albert-xlarge-spanish-finetuned-qa-mlqa | [
"pytorch",
"albert",
"question-answering",
"transformers",
"autotrain_compatible"
] | question-answering | {
"architectures": [
"AlbertForQuestionAnswering"
],
"model_type": "albert",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repe... | 7 | null | ---
license: mit
datasets:
- MRBrainS18
language:
- en
metrics:
-
tags:
- MedicalNet
- medical images
- medical
- 3D
- Med3D
thumbnail: "https://github.com/Tencent/MedicalNet/blob/master/images/logo.png?raw=true"
---
# MedicalNet
This repository contains a Pytorch implementation of [Med3D: Transfe... | [
-0.029704896733164787,
-0.020457349717617035,
-0.026695426553487778,
0.03753672167658806,
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0.03717901185154915,
0.02055133879184723,
0.00004367430301499553,
0.01855095848441124,
0.... |
dccuchile/albert-xxlarge-spanish-finetuned-mldoc | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
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},
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 26 | 2022-06-12T00:34:13Z | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- un_multi
metrics:
- bleu
model-index:
- name: opus-mt-en-ar-evaluated-en-to-ar-2000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
da... | [
-0.01250512432307005,
-0.0012948133517056704,
0.00160902738571167,
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0.05701440945267677,
-0.0010125316912308335,
-0.01086574699729681,
-0.006058952305465937,
... |
dccuchile/albert-xxlarge-spanish-finetuned-ner | [
"pytorch",
"albert",
"token-classification",
"transformers",
"autotrain_compatible"
] | token-classification | {
"architectures": [
"AlbertForTokenClassification"
],
"model_type": "albert",
"task_specific_params": {
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"max_length": null
},
"summarization": {
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"length_penalty": null,
"max_length": null,
"min_length": null,
"no_re... | 28 | 2022-06-12T00:34:54Z | ---
license: mit
datasets:
- MRBrainS18
language:
- en
metrics:
-
tags:
- MedicalNet
- medical images
- medical
- 3D
- Med3D
thumbnail: "https://github.com/Tencent/MedicalNet/blob/master/images/logo.png?raw=true"
---
# MedicalNet
This repository contains a Pytorch implementation of [Med3D: Transfe... | [
-0.029704896733164787,
-0.020457349717617035,
-0.026695426553487778,
0.03753672167658806,
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0.019793465733528137,
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0.03717901185154915,
0.02055133879184723,
0.00004367430301499553,
0.01855095848441124,
0.... |
dccuchile/albert-xxlarge-spanish-finetuned-pawsx | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 26 | null | ---
license: mit
datasets:
- MRBrainS18
language:
- en
metrics:
-
tags:
- MedicalNet
- medical images
- medical
- 3D
- Med3D
thumbnail: "https://github.com/Tencent/MedicalNet/blob/master/images/logo.png?raw=true"
---
# MedicalNet
This repository contains a Pytorch implementation of [Med3D: Transfe... | [
-0.029704896733164787,
-0.020457349717617035,
-0.026695426553487778,
0.03753672167658806,
0.038510631769895554,
0.019793465733528137,
-0.0130503810942173,
-0.03311868757009506,
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0.03717901185154915,
0.02055133879184723,
0.00004367430301499553,
0.01855095848441124,
0.... |
dccuchile/albert-xxlarge-spanish-finetuned-xnli | [
"pytorch",
"albert",
"text-classification",
"transformers"
] | text-classification | {
"architectures": [
"AlbertForSequenceClassification"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no... | 68 | null | ---
license: mit
datasets:
- MRBrainS18
language:
- en
metrics:
-
tags:
- MedicalNet
- medical images
- medical
- 3D
- Med3D
thumbnail: "https://github.com/Tencent/MedicalNet/blob/master/images/logo.png?raw=true"
---
# MedicalNet
This repository contains a Pytorch implementation of [Med3D: Transfe... | [
-0.029704896733164787,
-0.020457349717617035,
-0.026695426553487778,
0.03753672167658806,
0.038510631769895554,
0.019793465733528137,
-0.0130503810942173,
-0.03311868757009506,
-0.0007565257837995887,
0.03717901185154915,
0.02055133879184723,
0.00004367430301499553,
0.01855095848441124,
0.... |
dccuchile/albert-base-spanish | [
"pytorch",
"tf",
"albert",
"pretraining",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA"
] | null | {
"architectures": [
"AlbertForPreTraining"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngr... | 586 | 2022-06-12T00:52:56Z | ---
license: mit
datasets:
- MRBrainS18
language:
- en
metrics:
-
tags:
- MedicalNet
- medical images
- medical
- 3D
- Med3D
thumbnail: "https://github.com/Tencent/MedicalNet/blob/master/images/logo.png?raw=true"
---
# MedicalNet
This repository contains a Pytorch implementation of [Med3D: Transfe... | [
-0.029704896733164787,
-0.020457349717617035,
-0.026695426553487778,
0.03753672167658806,
0.038510631769895554,
0.019793465733528137,
-0.0130503810942173,
-0.03311868757009506,
-0.0007565257837995887,
0.03717901185154915,
0.02055133879184723,
0.00004367430301499553,
0.01855095848441124,
0.... |
dccuchile/albert-tiny-spanish | [
"pytorch",
"tf",
"albert",
"pretraining",
"es",
"dataset:large_spanish_corpus",
"transformers",
"spanish",
"OpenCENIA"
] | null | {
"architectures": [
"AlbertForPreTraining"
],
"model_type": "albert",
"task_specific_params": {
"conversational": {
"max_length": null
},
"summarization": {
"early_stopping": null,
"length_penalty": null,
"max_length": null,
"min_length": null,
"no_repeat_ngr... | 393 | 2022-06-13T23:23:24Z | ---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: MIX2_ja-en_helsinki
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. -->
# MIX2_ja-en_hels... | [
-0.0018572757253423333,
-0.017803378403186798,
0.018360896036028862,
0.04387246072292328,
0.03196382522583008,
0.0031716509256511927,
0.012441678903996944,
-0.007131624035537243,
-0.04495393857359886,
0.06342263519763947,
0.02282579429447651,
-0.0071045029908418655,
0.016591444611549377,
0... |
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