id stringlengths 6 113 | author stringlengths 2 36 | task_category stringclasses 39
values | tags listlengths 1 4.05k | created_time int64 1,646B 1,742B | last_modified timestamp[s]date 2020-05-14 13:13:12 2025-03-18 10:01:09 | downloads int64 0 118M | likes int64 0 4.86k | README stringlengths 30 1.01M | matched_task listlengths 1 10 | is_bionlp stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|
Helsinki-NLP/opus-mt-tc-base-ro-uk | Helsinki-NLP | translation | [
"transformers",
"pytorch",
"tf",
"safetensors",
"marian",
"text2text-generation",
"translation",
"opus-mt-tc",
"ro",
"uk",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,648,125,719,000 | 2023-10-10T21:36:02 | 20 | 0 | ---
language:
- ro
- uk
license: cc-by-4.0
tags:
- translation
- opus-mt-tc
model-index:
- name: opus-mt-tc-base-ro-uk
results:
- task:
type: translation
name: Translation ron-ukr
dataset:
name: flores101-devtest
type: flores_101
args: ron ukr devtest
metrics:
- type: bleu
... | [
"TRANSLATION"
] | Non_BioNLP |
puettmann/LlaMaestra-3.2-1B-Translation-Q8_0-GGUF | puettmann | translation | [
"transformers",
"gguf",
"translation",
"text-generation",
"llama-cpp",
"gguf-my-repo",
"en",
"it",
"base_model:puettmann/LlaMaestra-3.2-1B-Translation",
"base_model:quantized:puettmann/LlaMaestra-3.2-1B-Translation",
"license:llama3.2",
"endpoints_compatible",
"region:us",
"conversational"... | 1,733,692,929,000 | 2024-12-08T21:22:17 | 168 | 1 | ---
base_model: LeonardPuettmann/LlaMaestra-3.2-1B-Instruct-v0.1
language:
- en
- it
library_name: transformers
license: llama3.2
tags:
- translation
- text-generation
- llama-cpp
- gguf-my-repo
---
# LeonardPuettmann/LlaMaestra-3.2-1B-Instruct-v0.1-Q8_0-GGUF
This model was converted to GGUF format from [`LeonardPuett... | [
"TRANSLATION"
] | TBD |
sbulut/finetuned-kde4-en-to-tr | sbulut | translation | [
"transformers",
"tensorboard",
"safetensors",
"marian",
"text2text-generation",
"translation",
"generated_from_trainer",
"dataset:kde4",
"base_model:Helsinki-NLP/opus-mt-tc-big-tr-en",
"base_model:finetune:Helsinki-NLP/opus-mt-tc-big-tr-en",
"license:cc-by-4.0",
"model-index",
"autotrain_com... | 1,706,903,598,000 | 2024-02-02T21:57:41 | 16 | 0 | ---
base_model: Helsinki-NLP/opus-mt-tc-big-tr-en
datasets:
- kde4
license: cc-by-4.0
metrics:
- bleu
tags:
- translation
- generated_from_trainer
model-index:
- name: marian-finetuned-kde4-en-to-tr
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
... | [
"TRANSLATION"
] | Non_BioNLP |
interneuronai/az-gptneo | interneuronai | null | [
"peft",
"safetensors",
"base_model:EleutherAI/gpt-neo-2.7B",
"base_model:adapter:EleutherAI/gpt-neo-2.7B",
"region:us"
] | 1,710,019,353,000 | 2024-03-09T21:34:37 | 2 | 0 | ---
base_model: EleutherAI/gpt-neo-2.7B
library_name: peft
---
Model Details
Original Model: EleutherAI/gpt-neo-2.7B
Fine-Tuned For: Azerbaijani language understanding and generation
Dataset Used: Azerbaijani translation of the Stanford Alpaca dataset
Fine-Tuning Method: Self-instruct method
This m... | [
"TRANSLATION"
] | Non_BioNLP |
kuotient/Seagull-13b-translation-AWQ | kuotient | translation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"translate",
"awq",
"translation",
"ko",
"dataset:squarelike/sharegpt_deepl_ko_translation",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"region:us"
] | 1,708,761,757,000 | 2024-02-24T09:09:52 | 7 | 2 | ---
datasets:
- squarelike/sharegpt_deepl_ko_translation
language:
- ko
license: cc-by-nc-sa-4.0
pipeline_tag: translation
tags:
- translate
- awq
---
# **Seagull-13b-translation-AWQ 📇**
## This is quantized version of original model: Seagull-13b-translation.
*... | [
"TRANSLATION"
] | Non_BioNLP |
sheetalp91/setfit-model-1 | sheetalp91 | text-classification | [
"sentence-transformers",
"pytorch",
"roberta",
"setfit",
"text-classification",
"arxiv:2209.11055",
"license:apache-2.0",
"region:us"
] | 1,683,032,788,000 | 2023-05-02T13:06:43 | 9 | 0 | ---
license: apache-2.0
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
---
# sheetalp91/setfit-model-1
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 learni... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
research-backup/mbart-large-cc25-squad-qa | research-backup | text2text-generation | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"question answering",
"en",
"dataset:lmqg/qg_squad",
"arxiv:2210.03992",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,680,291,835,000 | 2023-05-06T12:48:31 | 13 | 0 | ---
datasets:
- lmqg/qg_squad
language: en
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
pipeline_tag: text2text-generation
tags:
- question answering
widget:
- text: 'question: What is a person called is practicing heresy?, context: Heresy
is any provocative belief or theory that ... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
Pdmk/t5-small-finetuned-summary_pd | Pdmk | summarization | [
"transformers",
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"summarization",
"generated_from_trainer",
"base_model:google-t5/t5-small",
"base_model:finetune:google-t5/t5-small",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"... | 1,692,652,866,000 | 2023-08-23T20:12:08 | 18 | 0 | ---
base_model: t5-small
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: t5-small-finetuned-summary_pd
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread a... | [
"SUMMARIZATION"
] | Non_BioNLP |
knowledgator/gliner-bi-small-v1.0 | knowledgator | token-classification | [
"gliner",
"pytorch",
"NER",
"GLiNER",
"information extraction",
"encoder",
"entity recognition",
"token-classification",
"multilingual",
"dataset:urchade/pile-mistral-v0.1",
"dataset:numind/NuNER",
"dataset:knowledgator/GLINER-multi-task-synthetic-data",
"license:apache-2.0",
"region:us"
] | 1,723,964,191,000 | 2024-08-25T11:38:26 | 122 | 10 | ---
datasets:
- urchade/pile-mistral-v0.1
- numind/NuNER
- knowledgator/GLINER-multi-task-synthetic-data
language:
- multilingual
library_name: gliner
license: apache-2.0
pipeline_tag: token-classification
tags:
- NER
- GLiNER
- information extraction
- encoder
- entity recognition
---
# About
GLiNER is a Named Entit... | [
"NAMED_ENTITY_RECOGNITION"
] | Non_BioNLP |
mrm8488/spanish-TinyBERT-betito-finetuned-xnli-es | mrm8488 | text-classification | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:xnli",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,772,951,000 | 2022-03-09T07:29:03 | 117 | 0 | ---
datasets:
- xnli
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: spanish-TinyBERT-betito-finetuned-xnli-es
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: xnli
type: xnli
args: es
metrics:
- type: accuracy
... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
etri-lirs/gbst-kebyt5-large-preview | etri-lirs | fill-mask | [
"transformers",
"pytorch",
"gbswt5",
"text2text-generation",
"fill-mask",
"custom_code",
"ko",
"en",
"ja",
"zh",
"arxiv:2106.12672",
"license:other",
"autotrain_compatible",
"region:us"
] | 1,707,808,911,000 | 2024-11-25T04:10:05 | 0 | 2 | ---
language:
- ko
- en
- ja
- zh
license: other
pipeline_tag: fill-mask
---
# Model Card for GBST-KEByT5-large (1.23B #params)
<!-- Provide a quick summary of what the model is/does. -->
KEByT5: Korean-Enhanced/Enriched Byte-level Text-to-Text Transfer Transformer(T5)의 GBST 버전으로,
CharFormer(Tay et al., 2021)를 기반으로 합니... | [
"RELATION_EXTRACTION",
"TRANSLATION"
] | Non_BioNLP |
tmnam20/bert-base-multilingual-cased-rte-100 | tmnam20 | text-classification | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"en",
"dataset:tmnam20/VieGLUE",
"base_model:google-bert/bert-base-multilingual-cased",
"base_model:finetune:google-bert/bert-base-multilingual-cased",
"license:apache-2.0",
"model-index",
"autotrain_compat... | 1,705,388,075,000 | 2024-01-16T06:55:47 | 15 | 0 | ---
base_model: bert-base-multilingual-cased
datasets:
- tmnam20/VieGLUE
language:
- en
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-base-multilingual-cased-rte-100
results:
- task:
type: text-classification
name: Text Classification
dataset:
... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
mustozsarac/finetuned-one-epoch-multi-qa-mpnet-base-dot-v1 | mustozsarac | sentence-similarity | [
"sentence-transformers",
"safetensors",
"mpnet",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:62964",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:sentence-transformers/multi-qa-mpnet-base-dot-v1",
"base_model:... | 1,719,486,539,000 | 2024-06-27T11:09:15 | 5 | 0 | ---
base_model: sentence-transformers/multi-qa-mpnet-base-dot-v1
datasets: []
language: []
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:62964
- loss:MultipleNegativesRankingLoss
widg... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
RichardErkhov/01-ai_-_Yi-6B-Chat-8bits | RichardErkhov | null | [
"safetensors",
"llama",
"arxiv:2403.04652",
"arxiv:2311.16502",
"arxiv:2401.11944",
"8-bit",
"bitsandbytes",
"region:us"
] | 1,728,215,196,000 | 2024-10-06T11:50:00 | 6 | 0 | ---
{}
---
Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Yi-6B-Chat - bnb 8bits
- Model creator: https://huggingface.co/01-ai/
- Original model: https://huggingface.co/01... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
monsterbeasts/LishizhenGPT | monsterbeasts | text-generation | [
"transformers",
"pytorch",
"safetensors",
"bloom",
"text-generation",
"ak",
"ar",
"as",
"bm",
"bn",
"ca",
"code",
"en",
"es",
"eu",
"fon",
"fr",
"gu",
"hi",
"id",
"ig",
"ki",
"kn",
"lg",
"ln",
"ml",
"mr",
"ne",
"nso",
"ny",
"or",
"pa",
"pt",
"rn",
... | 1,713,863,131,000 | 2024-05-09T04:44:44 | 12 | 0 | ---
datasets:
- bigscience/xP3mt
language:
- ak
- ar
- as
- bm
- bn
- ca
- code
- en
- es
- eu
- fon
- fr
- gu
- hi
- id
- ig
- ki
- kn
- lg
- ln
- ml
- mr
- ne
- nso
- ny
- or
- pa
- pt
- rn
- rw
- sn
- st
- sw
- ta
- te
- tn
- ts
- tum
- tw
- ur
- vi
- wo
- xh
- yo
- zh
- zu
license: bigscience-bloom-rail-1.0
pipelin... | [
"COREFERENCE_RESOLUTION",
"TRANSLATION"
] | Non_BioNLP |
tyzp-INC/bench2-all-MiniLM-L6-v2-tuned | tyzp-INC | text-classification | [
"sentence-transformers",
"pytorch",
"bert",
"setfit",
"text-classification",
"arxiv:2209.11055",
"license:apache-2.0",
"region:us"
] | 1,690,125,523,000 | 2023-07-23T15:18:48 | 9 | 0 | ---
license: apache-2.0
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
---
# tyzp-INC/bench2-all-MiniLM-L6-v2-tuned
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 fe... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
tner/twitter-roberta-base-dec2021-tweetner7-2020 | tner | token-classification | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"dataset:tner/tweetner7",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,656,839,252,000 | 2022-09-27T15:35:03 | 18 | 0 | ---
datasets:
- tner/tweetner7
metrics:
- f1
- precision
- recall
pipeline_tag: token-classification
widget:
- text: 'Get the all-analog Classic Vinyl Edition of `Takin'' Off` Album from {@herbiehancock@}
via {@bluenoterecords@} link below: {{URL}}'
example_title: NER Example 1
model-index:
- name: tner/twitter-r... | [
"NAMED_ENTITY_RECOGNITION"
] | Non_BioNLP |
AlexWortega/qwen11k | AlexWortega | sentence-similarity | [
"sentence-transformers",
"safetensors",
"qwen2",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:1077240",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:Qwen/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.... | 1,731,699,134,000 | 2024-11-15T19:33:05 | 13 | 0 | ---
base_model: Qwen/Qwen2.5-0.5B-Instruct
library_name: sentence-transformers
metrics:
- pearson_cosine
- spearman_cosine
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:1077240
- loss:MultipleNegativesRankingLoss
widget... | [
"TEXT_CLASSIFICATION",
"SEMANTIC_SIMILARITY"
] | Non_BioNLP |
tycjan/distilbert-pl-store-products-retrieval | tycjan | sentence-similarity | [
"sentence-transformers",
"safetensors",
"distilbert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:2400",
"loss:MultipleNegativesRankingLoss",
"dataset:tycjan/product-query-retrieval-dataset",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:sentence-... | 1,739,737,663,000 | 2025-02-16T20:28:19 | 9 | 0 | ---
base_model: sentence-transformers/quora-distilbert-multilingual
datasets:
- tycjan/product-query-retrieval-dataset
library_name: sentence-transformers
metrics:
- cosine_accuracy
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- data... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
Helsinki-NLP/opus-mt-is-de | Helsinki-NLP | translation | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"is",
"de",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,263,744,000 | 2023-08-16T11:58:29 | 66 | 0 | ---
language:
- is
- de
license: apache-2.0
tags:
- translation
---
### isl-deu
* source group: Icelandic
* target group: German
* OPUS readme: [isl-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/isl-deu/README.md)
* model: transformer-align
* source language(s): isl
* target language(... | [
"TRANSLATION"
] | Non_BioNLP |
TransferGraph/CAMeL-Lab_bert-base-arabic-camelbert-mix-did-nadi-finetuned-lora-tweet_eval_irony | TransferGraph | text-classification | [
"peft",
"safetensors",
"parquet",
"text-classification",
"dataset:tweet_eval",
"base_model:CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi",
"base_model:adapter:CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi",
"license:apache-2.0",
"model-index",
"region:us"
] | 1,709,055,210,000 | 2024-02-27T17:33:32 | 0 | 0 | ---
base_model: CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi
datasets:
- tweet_eval
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- parquet
- text-classification
model-index:
- name: CAMeL-Lab_bert-base-arabic-camelbert-mix-did-nadi-finetuned-lora-tweet_eval_irony
results:
- task:
type... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
poltextlab/xlm-roberta-large-polish-parlspeech-cap-v3 | poltextlab | text-classification | [
"pytorch",
"xlm-roberta",
"text-classification",
"pl",
"region:us"
] | 1,738,318,286,000 | 2025-02-26T16:08:46 | 0 | 0 | ---
language:
- pl
metrics:
- accuracy
- f1-score
tags:
- text-classification
- pytorch
extra_gated_prompt: 'Our models are intended for academic use only. If you are not
affiliated with an academic institution, please provide a rationale for using our
models. Please allow us a few business days to manua... | [
"TRANSLATION"
] | Non_BioNLP |
shinjiyamas/reddit-construct-classify | shinjiyamas | null | [
"transformers",
"RobertaWithFeatures",
"license:mit",
"endpoints_compatible",
"region:us"
] | 1,717,137,448,000 | 2024-05-31T08:54:47 | 6 | 1 | ---
license: mit
---
# Project Name
Provide a brief introduction to what the project does and its target audience. Describe the problems it solves or the functionality it offers.
## Features
- Custom integration of numerical features with text data using RoBERTa.
- Ability to handle complex text classi... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
CATIE-AQ/QAmembert | CATIE-AQ | question-answering | [
"transformers",
"pytorch",
"safetensors",
"camembert",
"question-answering",
"fr",
"dataset:etalab-ia/piaf",
"dataset:fquad",
"dataset:lincoln/newsquadfr",
"dataset:pragnakalp/squad_v2_french_translated",
"dataset:CATIE-AQ/frenchQA",
"arxiv:1910.09700",
"doi:10.57967/hf/0821",
"license:mit... | 1,673,368,406,000 | 2024-11-26T10:46:29 | 114 | 14 | ---
datasets:
- etalab-ia/piaf
- fquad
- lincoln/newsquadfr
- pragnakalp/squad_v2_french_translated
- CATIE-AQ/frenchQA
language: fr
library_name: transformers
license: mit
metrics:
- f1
- exact_match
pipeline_tag: question-answering
widget:
- text: Combien de personnes utilisent le français tous les jours ?
context:... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
Priyanka-Balivada/electra-5-epoch-sentiment | Priyanka-Balivada | text-classification | [
"transformers",
"pytorch",
"electra",
"text-classification",
"generated_from_trainer",
"dataset:tweet_eval",
"base_model:google/electra-small-discriminator",
"base_model:finetune:google/electra-small-discriminator",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compat... | 1,698,574,972,000 | 2024-02-20T14:32:28 | 20 | 0 | ---
base_model: google/electra-small-discriminator
datasets:
- tweet_eval
license: apache-2.0
metrics:
- accuracy
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: electra-5-epoch-sentiment
results:
- task:
type: text-classification
name: Text Classification
dataset:
nam... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
MemorialStar/distilbert-base-uncased-finetuned-emotion | MemorialStar | text-classification | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_co... | 1,709,366,604,000 | 2024-03-02T10:47:06 | 4 | 0 | ---
base_model: distilbert/distilbert-base-uncased
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: ... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
Helsinki-NLP/opus-mt-es-tll | Helsinki-NLP | translation | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"es",
"tll",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,263,744,000 | 2023-08-16T11:33:37 | 357 | 0 | ---
license: apache-2.0
tags:
- translation
---
### opus-mt-es-tll
* source languages: es
* target languages: tll
* OPUS readme: [es-tll](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/es-tll/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* d... | [
"TRANSLATION"
] | Non_BioNLP |
BatirayErbayVodafone/testg | BatirayErbayVodafone | text-generation | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"conversational",
"arxiv:2009.03300",
"arxiv:1905.07830",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1905.10044",
"arxiv:1907.10641",
"arxiv:1811.00937",
"arxiv:1809.02789",
"arxiv:1911.01547",
"arxiv:1705.03551",
"arxiv:2... | 1,725,916,794,000 | 2024-09-10T04:52:10 | 7 | 0 | ---
base_model: google/gemma-2-9b
library_name: transformers
license: gemma
pipeline_tag: text-generation
tags:
- conversational
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
agree to Google’s usage license. To do this, please ensu... | [
"QUESTION_ANSWERING",
"SUMMARIZATION"
] | Non_BioNLP |
dmedhi/eng2french-t5-small | dmedhi | translation | [
"peft",
"safetensors",
"translation",
"transformers",
"en",
"fr",
"dataset:opus100",
"base_model:google-t5/t5-small",
"base_model:adapter:google-t5/t5-small",
"license:apache-2.0",
"region:us"
] | 1,702,984,347,000 | 2023-12-19T18:12:31 | 12 | 0 | ---
base_model: t5-small
datasets:
- opus100
language:
- en
- fr
library_name: peft
license: apache-2.0
tags:
- translation
- safetensors
- transformers
---
# Model Card for Model ID
A language translation model fine-tuned on **opus100** dataset for *English to French* translation.
## Model Description
- **Model t... | [
"TRANSLATION"
] | Non_BioNLP |
elybes/IFRS_en_ar_translation | elybes | translation | [
"transformers",
"safetensors",
"marian",
"text2text-generation",
"finance",
"IFRS",
"translation",
"ar",
"en",
"dataset:elybes/IFRS",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,722,330,593,000 | 2024-08-13T20:39:10 | 28 | 1 | ---
datasets:
- elybes/IFRS
language:
- ar
- en
metrics:
- bleu
pipeline_tag: translation
tags:
- finance
- IFRS
- translation
---
| [
"TRANSLATION"
] | Non_BioNLP |
LoneStriker/bagel-7b-v0.1-5.0bpw-h6-exl2-2 | LoneStriker | text-generation | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"dataset:ai2_arc",
"dataset:unalignment/spicy-3.1",
"dataset:codeparrot/apps",
"dataset:facebook/belebele",
"dataset:boolq",
"dataset:jondurbin/cinematika-v0.1",
"dataset:drop",
"dataset:lmsys/lmsys-chat-1m",
"d... | 1,702,490,552,000 | 2023-12-13T18:06:31 | 6 | 0 | ---
datasets:
- ai2_arc
- unalignment/spicy-3.1
- codeparrot/apps
- facebook/belebele
- boolq
- jondurbin/cinematika-v0.1
- drop
- lmsys/lmsys-chat-1m
- TIGER-Lab/MathInstruct
- cais/mmlu
- Muennighoff/natural-instructions
- openbookqa
- piqa
- Vezora/Tested-22k-Python-Alpaca
- cakiki/rosetta-code
- Open-Orca/SlimOrca
... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
Lots-of-LoRAs/Mistral-7B-Instruct-v0.2-4b-r16-task660 | Lots-of-LoRAs | null | [
"pytorch",
"safetensors",
"en",
"arxiv:1910.09700",
"arxiv:2407.00066",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.2",
"license:mit",
"region:us"
] | 1,736,086,147,000 | 2025-01-05T14:09:13 | 0 | 0 | ---
base_model: mistralai/Mistral-7B-Instruct-v0.2
language: en
library_name: pytorch
license: mit
---
# Model Card for Mistral-7B-Instruct-v0.2-4b-r16-task660
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -... | [
"TRANSLATION"
] | Non_BioNLP |
pardeep/distilbert-base-uncased-finetuned-emotion-ch02 | pardeep | text-classification | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,658,053,868,000 | 2022-07-17T10:54:29 | 104 | 0 | ---
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-emotion-ch02
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
args: de... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
potsawee/t5-large-generation-race-QuestionAnswer | potsawee | text2text-generation | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"en",
"dataset:race",
"arxiv:2301.12307",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,677,109,278,000 | 2023-03-12T16:10:27 | 83 | 16 | ---
datasets:
- race
language:
- en
library_name: transformers
license: apache-2.0
pipeline_tag: text2text-generation
---
# t5-large fine-tuned to RACE for Generating Question+Answer
- Input: `context` (e.g. news article)
- Output: `question <sep> answer`
This model generates **abstractive** answers following the RACE... | [
"QUESTION_ANSWERING",
"SUMMARIZATION"
] | Non_BioNLP |
Atharvgarg/bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-old | Atharvgarg | text2text-generation | [
"transformers",
"pytorch",
"tensorboard",
"encoder-decoder",
"text2text-generation",
"summarisation",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,659,021,898,000 | 2022-07-28T16:04:21 | 20 | 0 | ---
license: apache-2.0
metrics:
- rouge
tags:
- summarisation
- generated_from_trainer
model-index:
- name: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-old
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to... | [
"SUMMARIZATION"
] | Non_BioNLP |
aiola/roberta-large-corener | aiola | fill-mask | [
"transformers",
"pytorch",
"roberta",
"fill-mask",
"NER",
"named entity recognition",
"RE",
"relation extraction",
"entity mention detection",
"EMD",
"coreference resolution",
"en",
"dataset:Ontonotes",
"dataset:CoNLL04",
"license:afl-3.0",
"autotrain_compatible",
"endpoints_compatib... | 1,653,466,421,000 | 2022-07-03T14:16:17 | 102 | 2 | ---
datasets:
- Ontonotes
- CoNLL04
language:
- en
license: afl-3.0
tags:
- NER
- named entity recognition
- RE
- relation extraction
- entity mention detection
- EMD
- coreference resolution
---
# CoReNer
## Demo
We released an online demo so you can easily play with the model. Check it out: [http://corener-demo.ai... | [
"NAMED_ENTITY_RECOGNITION",
"RELATION_EXTRACTION",
"COREFERENCE_RESOLUTION"
] | Non_BioNLP |
gigauser/kcbert_nsmc_tuning | gigauser | text-classification | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:nsmc",
"base_model:beomi/kcbert-base",
"base_model:finetune:beomi/kcbert-base",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,720,360,869,000 | 2024-07-08T06:00:35 | 12 | 0 | ---
base_model: beomi/kcbert-base
datasets:
- nsmc
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: kcbert_nsmc_tuning
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: nsmc
type: nsmc
config: default
... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
seongwkim/distilbert-base-uncased-finetuned-emotion | seongwkim | text-classification | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,650,526,006,000 | 2022-04-21T08:34:19 | 120 | 0 | ---
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
args: default... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
cgus/granite-3.2-8b-instruct-preview-exl2 | cgus | text-generation | [
"exllamav2",
"granite",
"language",
"granite-3.2",
"text-generation",
"conversational",
"arxiv:0000.00000",
"base_model:ibm-granite/granite-3.2-8b-instruct-preview",
"base_model:quantized:ibm-granite/granite-3.2-8b-instruct-preview",
"license:apache-2.0",
"4-bit",
"exl2",
"region:us"
] | 1,739,051,780,000 | 2025-02-09T09:37:46 | 60 | 0 | ---
base_model:
- ibm-granite/granite-3.2-8b-instruct-preview
library_name: exllamav2
license: apache-2.0
pipeline_tag: text-generation
tags:
- language
- granite-3.2
inference: false
---
# Granite-3.2-8B-Instruct-Preview-exl2
Original model: [Granite-3.2-8B-Instruct-Preview](https://huggingface.co/ibm-granite/granite-... | [
"TEXT_CLASSIFICATION",
"SUMMARIZATION"
] | Non_BioNLP |
cbpuschmann/BERT-klimacoder_v0.3 | cbpuschmann | text-classification | [
"tensorboard",
"safetensors",
"bert",
"autotrain",
"text-classification",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"region:us"
] | 1,733,152,651,000 | 2024-12-02T15:18:12 | 4 | 0 | ---
base_model: google-bert/bert-base-uncased
tags:
- autotrain
- text-classification
widget:
- text: I love AutoTrain
---
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 0.05558604374527931
f1: 0.9881956155143339
precision: 0.9881956155143339
recall: 0.988195615514... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
pathfinderNdoma/online-doctor-model | pathfinderNdoma | question-answering | [
"transformers",
"safetensors",
"bert",
"question-answering",
"base_model:dmis-lab/biobert-v1.1",
"base_model:finetune:dmis-lab/biobert-v1.1",
"license:creativeml-openrail-m",
"endpoints_compatible",
"region:us"
] | 1,729,704,679,000 | 2024-10-23T17:58:48 | 8 | 0 | ---
base_model:
- dmis-lab/biobert-v1.1
library_name: transformers
license: creativeml-openrail-m
pipeline_tag: question-answering
---
library_name: transformers
tags: [biomedical, question-answering, healthcare]
---
# Model Card for Online Doctor Model
This model is a fine-tuned version of the `dmis-lab/biober... | [
"QUESTION_ANSWERING"
] | BioNLP |
RichardErkhov/EleutherAI_-_pythia-70m-deduped-8bits | RichardErkhov | text-generation | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"arxiv:2304.01373",
"arxiv:2101.00027",
"arxiv:2201.07311",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"8-bit",
"bitsandbytes",
"region:us"
] | 1,713,858,590,000 | 2024-04-23T07:50:27 | 5 | 0 | ---
{}
---
Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-70m-deduped - bnb 8bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://hugg... | [
"QUESTION_ANSWERING",
"TRANSLATION"
] | Non_BioNLP |
tmnam20/xlm-roberta-base-sst2-10 | tmnam20 | text-classification | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"en",
"dataset:tmnam20/VieGLUE",
"base_model:FacebookAI/xlm-roberta-base",
"base_model:finetune:FacebookAI/xlm-roberta-base",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compat... | 1,705,403,424,000 | 2024-01-16T11:12:06 | 7 | 0 | ---
base_model: xlm-roberta-base
datasets:
- tmnam20/VieGLUE
language:
- en
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-sst2-10
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: tmnam20/VieGLUE/SST2
... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
RichardErkhov/bigscience_-_bloomz-1b7-8bits | RichardErkhov | text-generation | [
"transformers",
"safetensors",
"bloom",
"text-generation",
"arxiv:2211.01786",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"8-bit",
"bitsandbytes",
"region:us"
] | 1,721,473,944,000 | 2024-07-20T11:14:08 | 76 | 0 | ---
{}
---
Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
bloomz-1b7 - bnb 8bits
- Model creator: https://huggingface.co/bigscience/
- Original model: https://huggingface.... | [
"COREFERENCE_RESOLUTION",
"TRANSLATION"
] | Non_BioNLP |
fabiancpl/nlbse25_java | fabiancpl | text-classification | [
"setfit",
"safetensors",
"bert",
"sentence-transformers",
"text-classification",
"generated_from_setfit_trainer",
"arxiv:2209.11055",
"region:us"
] | 1,734,056,469,000 | 2024-12-13T02:21:16 | 8 | 0 | ---
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget: []
inference: true
---
# SetFit
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. ... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
anismahmahi/G2-with-noPropaganda-multilabel-setfit-model | anismahmahi | text-classification | [
"setfit",
"safetensors",
"mpnet",
"sentence-transformers",
"text-classification",
"generated_from_setfit_trainer",
"arxiv:2209.11055",
"base_model:sentence-transformers/paraphrase-mpnet-base-v2",
"base_model:finetune:sentence-transformers/paraphrase-mpnet-base-v2",
"model-index",
"region:us"
] | 1,704,503,277,000 | 2024-01-06T01:08:14 | 3 | 0 | ---
base_model: sentence-transformers/paraphrase-mpnet-base-v2
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: But the author is Bharath Ganesh.
- text: The documents, which suggest al... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
eunbi-jeong/gpt2 | eunbi-jeong | translation | [
"translation",
"en",
"dataset:hellaswag",
"region:us"
] | 1,692,944,278,000 | 2023-08-25T06:19:07 | 0 | 0 | ---
datasets:
- hellaswag
language:
- en
pipeline_tag: translation
---
| [
"TRANSLATION"
] | Non_BioNLP |
jaesani/large_eng_summarizer | jaesani | summarization | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"code",
"summarization",
"en",
"dataset:npc-engine/light-batch-summarize-dialogue",
"base_model:facebook/bart-large-cnn",
"base_model:finetune:facebook/bart-large-cnn",
"license:mit",
"autotrain_compatible",
"endpoints_compatible... | 1,726,744,387,000 | 2024-09-19T12:30:22 | 29 | 0 | ---
base_model:
- facebook/bart-large-cnn
datasets:
- npc-engine/light-batch-summarize-dialogue
language:
- en
library_name: transformers
license: mit
metrics:
- accuracy
pipeline_tag: summarization
tags:
- code
---
Model Card: Large English Summarizer
Model Overview
This model is a large-scale transformer-based summa... | [
"SUMMARIZATION"
] | Non_BioNLP |
fathyshalab/reklambox2-6-17 | fathyshalab | text-classification | [
"sentence-transformers",
"pytorch",
"xlm-roberta",
"setfit",
"text-classification",
"arxiv:2209.11055",
"license:apache-2.0",
"region:us"
] | 1,677,796,147,000 | 2023-03-03T00:08:34 | 8 | 0 | ---
license: apache-2.0
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
---
# fathyshalab/reklambox2-6-17
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... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
leejaymin/etri-ones-llama3.1-8b-ko | leejaymin | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,723,828,689,000 | 2024-09-06T07:53:30 | 8 | 1 | ---
library_name: transformers
tags: []
---
# Model Card for `leejaymin/etri-ones-llama3.1-8b-ko`
## Model Summary
This model is a fine-tuned version of LLaMA 3.1 (8B) using QLoRA (Quantized Low-Rank Adaptation) techniques, specifically trained on Korean language datasets. It is optimized for understanding and gener... | [
"TRANSLATION",
"SUMMARIZATION"
] | Non_BioNLP |
SakshamJain/Temp | SakshamJain | summarization | [
"transformers",
"t5",
"text2text-generation",
"summarization",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,698,907,147,000 | 2023-11-02T06:41:59 | 14 | 0 | ---
pipeline_tag: summarization
---
| [
"SUMMARIZATION"
] | Non_BioNLP |
yjgwak/klue-bert-base-finetuned-squad-kor-v1 | yjgwak | question-answering | [
"transformers",
"pytorch",
"safetensors",
"bert",
"question-answering",
"korean",
"klue",
"squad-kor-v1",
"ko",
"arxiv:2105.09680",
"license:cc-by-sa-4.0",
"endpoints_compatible",
"region:us"
] | 1,694,142,664,000 | 2023-09-11T02:52:58 | 206 | 1 | ---
language: ko
license: cc-by-sa-4.0
tags:
- korean
- klue
- squad-kor-v1
mask_token: '[MASK]'
widget:
- text: 바그너는 괴테의 파우스트를 읽고 무엇을 쓰고자 했는가?
context: 1839년 바그너는 괴테의 파우스트을 처음 읽고 그 내용에 마음이 끌려 이를 소재로 해서 하나의 교향곡을 쓰려는 뜻을 갖는다.
이 시기 바그너는 1838년에 빛 독촉으로 산전수전을 다 걲은 상황이라 좌절과 실망에 가득했으며 메피스토펠레스를 만나는 파우스트의 심경에 공감했다고
한다.... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
pinzhenchen/sft-lora-de-pythia-2b8 | pinzhenchen | null | [
"generation",
"question answering",
"instruction tuning",
"de",
"arxiv:2309.08958",
"license:cc-by-nc-4.0",
"region:us"
] | 1,709,682,763,000 | 2024-03-05T23:52:46 | 0 | 0 | ---
language:
- de
license: cc-by-nc-4.0
tags:
- generation
- question answering
- instruction tuning
---
### Model Description
This HF repository contains base LLMs instruction tuned (SFT) with LoRA and then used to study whether monolingual or multilingual instruction tuning is more favourable.
* [GitHub](https://... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
TheBloke/Airoboros-M-7B-3.1.2-GGUF | TheBloke | null | [
"transformers",
"gguf",
"mistral",
"dataset:jondurbin/airoboros-3.1",
"base_model:jondurbin/airoboros-m-7b-3.1.2",
"base_model:quantized:jondurbin/airoboros-m-7b-3.1.2",
"license:apache-2.0",
"region:us"
] | 1,697,733,712,000 | 2023-10-19T16:45:56 | 437 | 13 | ---
base_model: jondurbin/airoboros-m-7b-3.1.2
datasets:
- jondurbin/airoboros-3.1
license: apache-2.0
model_name: Airoboros M 7B 3.1.2
inference: false
model_creator: Jon Durbin
model_type: mistral
prompt_template: '[INST] <<SYS>>
You are a helpful, unbiased, uncensored assistant.
<</SYS>>
{prompt} [/INST]
... | [
"QUESTION_ANSWERING",
"SUMMARIZATION"
] | Non_BioNLP |
Netta1994/setfit_baai_wix_qa_gpt-4o_improved-cot-instructions_two_reasoning_only_reasoning_1726 | Netta1994 | text-classification | [
"setfit",
"safetensors",
"bert",
"sentence-transformers",
"text-classification",
"generated_from_setfit_trainer",
"arxiv:2209.11055",
"base_model:BAAI/bge-base-en-v1.5",
"base_model:finetune:BAAI/bge-base-en-v1.5",
"model-index",
"region:us"
] | 1,726,754,851,000 | 2024-09-19T14:08:07 | 7 | 0 | ---
base_model: BAAI/bge-base-en-v1.5
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: "Reasoning for Good:\n1. **Context Grounding**: The answer is well-supported\
\ by the provide... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
rdpratti/distilbert-base-uncased-finetuned-emotion | rdpratti | text-classification | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,678,134,812,000 | 2023-03-17T12:57:20 | 11 | 0 | ---
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
args: split
... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
Helsinki-NLP/opus-mt-en-cel | Helsinki-NLP | translation | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"en",
"gd",
"ga",
"br",
"kw",
"gv",
"cy",
"cel",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,263,744,000 | 2023-08-16T11:29:12 | 47 | 0 | ---
language:
- en
- gd
- ga
- br
- kw
- gv
- cy
- cel
license: apache-2.0
tags:
- translation
---
### eng-cel
* source group: English
* target group: Celtic languages
* OPUS readme: [eng-cel](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-cel/README.md)
* model: transformer
* source la... | [
"TRANSLATION"
] | Non_BioNLP |
gokulsrinivasagan/distilbert_lda_5_v1_book_mrpc | gokulsrinivasagan | text-classification | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"en",
"dataset:glue",
"base_model:gokulsrinivasagan/distilbert_lda_5_v1_book",
"base_model:finetune:gokulsrinivasagan/distilbert_lda_5_v1_book",
"model-index",
"autotrain_compatible",
... | 1,733,759,151,000 | 2024-12-09T15:46:52 | 4 | 0 | ---
base_model: gokulsrinivasagan/distilbert_lda_5_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_5_v1_book_mrpc
results:
- task:
type: text-classification
name: Text Classification
datase... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
openaccess-ai-collective/manticore-13b-chat-pyg | openaccess-ai-collective | text-generation | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:anon8231489123/ShareGPT_Vicuna_unfiltered",
"dataset:ehartford/wizard_vicuna_70k_unfiltered",
"dataset:ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered",
"dataset:QingyiSi/Alpaca-CoT",
"dataset:teknium/GPT... | 1,684,772,517,000 | 2023-06-07T12:32:40 | 3,537 | 30 | ---
datasets:
- anon8231489123/ShareGPT_Vicuna_unfiltered
- ehartford/wizard_vicuna_70k_unfiltered
- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
- QingyiSi/Alpaca-CoT
- teknium/GPT4-LLM-Cleaned
- teknium/GPTeacher-General-Instruct
- metaeval/ScienceQA_text_only
- hellaswag
- openai/summarize_from_feedback
- ... | [
"SUMMARIZATION"
] | Non_BioNLP |
UNIST-Eunchan/Pegasus-x-base-govreport-12288-1024-numepoch-10 | UNIST-Eunchan | text2text-generation | [
"transformers",
"pytorch",
"pegasus_x",
"text2text-generation",
"generated_from_trainer",
"dataset:govreport-summarization",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,689,819,644,000 | 2023-07-22T03:05:31 | 30 | 0 | ---
datasets:
- govreport-summarization
tags:
- generated_from_trainer
model-index:
- name: Pegasus-x-base-govreport-12288-1024-numepoch-10
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... | [
"SUMMARIZATION"
] | Non_BioNLP |
LongSafari/hyenadna-tiny-1k-seqlen-d256-hf | LongSafari | text-generation | [
"transformers",
"safetensors",
"hyenadna",
"text-generation",
"dna",
"biology",
"genomics",
"hyena",
"custom_code",
"arxiv:2306.15794",
"arxiv:2302.10866",
"license:bsd-3-clause",
"autotrain_compatible",
"region:us"
] | 1,699,020,703,000 | 2024-01-24T17:22:45 | 166 | 0 | ---
license: bsd-3-clause
tags:
- dna
- biology
- genomics
- hyena
---
# HyenaDNA
Welcome! HyenaDNA is a long-range genomic foundation model pretrained on context lengths of up to **1 million tokens** at **single nucleotide resolution**.
See below for an [overview](#model) of the model and training. Better yet, che... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
neurips-user/neurips-deberta-combined-1 | neurips-user | text-classification | [
"transformers",
"tensorboard",
"safetensors",
"deberta-v2",
"text-classification",
"autotrain",
"dataset:neurips-bert-combined5/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,715,825,301,000 | 2024-05-16T02:28:17 | 16 | 0 | ---
datasets:
- neurips-bert-combined5/autotrain-data
tags:
- autotrain
- text-classification
widget:
- text: I love AutoTrain
---
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 0.4513716995716095
f1: 0.8037383177570093
precision: 0.7543859649122807
recall: 0.86
a... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
Thang203/general_nlp_research_paper | Thang203 | text-classification | [
"bertopic",
"text-classification",
"region:us"
] | 1,712,792,211,000 | 2024-04-10T23:36:54 | 4 | 0 | ---
library_name: bertopic
pipeline_tag: text-classification
tags:
- bertopic
---
# general_nlp_research_paper
This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datase... | [
"NAMED_ENTITY_RECOGNITION",
"RELATION_EXTRACTION",
"TEXT_CLASSIFICATION",
"COREFERENCE_RESOLUTION",
"EVENT_EXTRACTION",
"QUESTION_ANSWERING",
"SEMANTIC_SIMILARITY",
"TRANSLATION",
"SUMMARIZATION",
"PARAPHRASING"
] | Non_BioNLP |
SyedShaheer/bart-large-cnn-samsum_tuned_V2_1 | SyedShaheer | summarization | [
"transformers",
"pytorch",
"bart",
"text2text-generation",
"summarization",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,714,640,840,000 | 2024-05-02T09:17:38 | 10 | 0 | ---
pipeline_tag: summarization
---
| [
"SUMMARIZATION"
] | Non_BioNLP |
agentlans/mdeberta-v3-base-readability | agentlans | text-classification | [
"safetensors",
"deberta-v2",
"multilingual",
"readability",
"text-classification",
"dataset:agentlans/tatoeba-english-translations",
"base_model:microsoft/mdeberta-v3-base",
"base_model:finetune:microsoft/mdeberta-v3-base",
"license:mit",
"region:us"
] | 1,728,705,039,000 | 2024-10-12T09:55:59 | 50 | 0 | ---
base_model:
- microsoft/mdeberta-v3-base
datasets:
- agentlans/tatoeba-english-translations
license: mit
pipeline_tag: text-classification
tags:
- multilingual
- readability
---
# DeBERTa V3 Base for Multilingual Readability Assessment
This is a fine-tuned version of the multilingual DeBERTa model (mdeberta) for a... | [
"TRANSLATION"
] | Non_BioNLP |
mrm8488/mbart-large-finetuned-opus-es-en-translation | mrm8488 | translation | [
"transformers",
"pytorch",
"safetensors",
"mbart",
"text2text-generation",
"translation",
"es",
"en",
"dataset:opus100",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,263,745,000 | 2023-04-05T10:32:38 | 298 | 2 | ---
datasets:
- opus100
language:
- es
- en
tags:
- translation
---
### mbart-large-es-en
This is mbart-large-cc25, finetuned on opus100 for Spanish to English translation.
It scores BLEU **28.25** on validation dataset
It scores BLEU **28.28** on test
dataset | [
"TRANSLATION"
] | Non_BioNLP |
TransferGraph/zenkri_autotrain-Arabic_Poetry_by_Subject-920730230-finetuned-lora-tweet_eval_emotion | TransferGraph | text-classification | [
"peft",
"safetensors",
"parquet",
"text-classification",
"dataset:tweet_eval",
"base_model:zenkri/autotrain-Arabic_Poetry_by_Subject-920730230",
"base_model:adapter:zenkri/autotrain-Arabic_Poetry_by_Subject-920730230",
"model-index",
"region:us"
] | 1,709,211,139,000 | 2024-02-29T12:52:22 | 0 | 0 | ---
base_model: zenkri/autotrain-Arabic_Poetry_by_Subject-920730230
datasets:
- tweet_eval
library_name: peft
metrics:
- accuracy
tags:
- parquet
- text-classification
model-index:
- name: zenkri_autotrain-Arabic_Poetry_by_Subject-920730230-finetuned-lora-tweet_eval_emotion
results:
- task:
type: text-classif... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
ElizaClaPa/SentimentAnalysis-YelpReviews-OptimizedModel | ElizaClaPa | text-classification | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,720,963,951,000 | 2024-07-16T07:09:10 | 98 | 0 | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
Sentiment Analysis Model to predict the label from a review given, the labels go from 1 star to 5 stars.
## Model Details
### Model Description
<!-- Provide a longer summary of what th... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
fine-tuned/BAAI_bge-large-en-15062024-atex-webapp | fine-tuned | feature-extraction | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"mteb",
"Science",
"Technology",
"Medicine",
"Philosophy",
"Research",
"en",
"dataset:fine-tuned/BAAI_bge-large-en-15062024-atex-webapp",
"dataset:allenai/c4",
"license:apache-2.0",
"autotrain_... | 1,718,416,051,000 | 2024-06-15T01:48:01 | 7 | 0 | ---
datasets:
- fine-tuned/BAAI_bge-large-en-15062024-atex-webapp
- allenai/c4
language:
- en
license: apache-2.0
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
- Science
- Technology
- Medicine
- Philosophy
- Research
---
This model is a fine-tuned vers... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
Nishthaa321/autotrain-qr7os-gstst | Nishthaa321 | text-classification | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"autotrain",
"dataset:autotrain-qr7os-gstst/autotrain-data",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,709,029,538,000 | 2024-02-27T10:26:05 | 6 | 0 | ---
datasets:
- autotrain-qr7os-gstst/autotrain-data
tags:
- autotrain
- text-classification
widget:
- text: I love AutoTrain
---
# Model Trained Using AutoTrain
- Problem type: Text Classification
## Validation Metrics
loss: 0.2146722972393036
f1: 1.0
precision: 1.0
recall: 1.0
auc: 1.0
accuracy: 1.0
| [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
GAIR/rst-gaokao-writing-11b | GAIR | text2text-generation | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"arxiv:2206.11147",
"license:afl-3.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,662,064,399,000 | 2022-09-04T01:42:02 | 10 | 2 | ---
license: afl-3.0
---
<p align="center">
<br>
<img src="https://expressai-xlab.s3.amazonaws.com/rst/intro_rst.png" width="1000"/>
<br>
</p>
# reStructured Pre-training (RST)
official [repository](https://github.com/ExpressAI/reStructured-Pretraining), [paper](https://arxiv.org/pdf/2206.11147.pdf), [east... | [
"NAMED_ENTITY_RECOGNITION",
"RELATION_EXTRACTION",
"TEXT_CLASSIFICATION",
"QUESTION_ANSWERING",
"SUMMARIZATION",
"PARAPHRASING"
] | Non_BioNLP |
justinthelaw/Phi-3-mini-128k-instruct-4bit-128g-GPTQ | justinthelaw | text-generation | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"nlp",
"code",
"custom_code",
"conversational",
"en",
"dataset:Salesforce/wikitext",
"base_model:microsoft/Phi-3-mini-128k-instruct",
"base_model:quantized:microsoft/Phi-3-mini-128k-instruct",
"license:apache-2.0",
"autotrain_compat... | 1,722,363,533,000 | 2024-08-03T12:37:46 | 242 | 1 | ---
base_model: microsoft/Phi-3-mini-128k-instruct
datasets:
- Salesforce/wikitext
language:
- en
license: apache-2.0
pipeline_tag: text-generation
tags:
- nlp
- code
- phi3
- custom_code
- conversational
---
# Phi-3-mini-128k-instruct GPTQ 4-bit 128g Group Size
- Model creator: [Microsoft](https://huggingface.co/mic... | [
"SUMMARIZATION"
] | Non_BioNLP |
ein3108/bert-finetuned-sem_eval-english | ein3108 | text-classification | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:sem_eval_2018_task_1",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
... | 1,730,773,762,000 | 2024-11-05T02:30:04 | 8 | 0 | ---
base_model: bert-base-uncased
datasets:
- sem_eval_2018_task_1
library_name: transformers
license: apache-2.0
metrics:
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-finetuned-sem_eval-english
results:
- task:
type: text-classification
name: Text Classification
dataset:... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
RichardErkhov/macadeliccc_-_OmniCorso-7B-gguf | RichardErkhov | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | 1,716,324,329,000 | 2024-05-21T23:20:54 | 7 | 0 | ---
{}
---
Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
OmniCorso-7B - GGUF
- Model creator: https://huggingface.co/macadeliccc/
- Original model: https://huggingface.co... | [
"TRANSLATION"
] | Non_BioNLP |
DandinPower/deberta-v2-xlarge-otat | DandinPower | text-classification | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"nycu-112-2-datamining-hw2",
"generated_from_trainer",
"en",
"dataset:DandinPower/review_onlytitleandtext",
"base_model:microsoft/deberta-v2-xlarge",
"base_model:finetune:microsoft/deberta-v2-xlarge",
"license:mit",
"model-ind... | 1,713,553,851,000 | 2024-04-19T21:55:26 | 5 | 0 | ---
base_model: microsoft/deberta-v2-xlarge
datasets:
- DandinPower/review_onlytitleandtext
language:
- en
license: mit
metrics:
- accuracy
tags:
- nycu-112-2-datamining-hw2
- generated_from_trainer
model-index:
- name: deberta-v2-xlarge-otat
results:
- task:
type: text-classification
name: Text Classif... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
leeolivia77/custom_summarization_dataset | leeolivia77 | null | [
"region:us"
] | 1,726,810,166,000 | 2024-09-20T05:29:29 | 0 | 0 | ---
{}
---
# Dataset Card for Custom Text Dataset
## Dataset Name
Custom Text Dataset for Summarization
## Overview
A dataset created for summarizing articles.
## Composition
Contains pairs of articles and their summaries.
## Collection Process
Data was collected from CNN/Daily Mail.
## Preprocessing
Text cleaned... | [
"SUMMARIZATION"
] | Non_BioNLP |
lilyray/results | lilyray | text-classification | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"model-index",
"autotrain_compatible"... | 1,709,600,157,000 | 2024-03-10T14:59:22 | 31 | 0 | ---
base_model: distilbert-base-uncased
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: results
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
config: split
... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
juanjucm/whisper-large-v3-turbo-OpenHQ-GL-EN | juanjucm | automatic-speech-recognition | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"gl",
"en",
"dataset:juanjucm/OpenHQ-SpeechT-GL-EN",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:mit",
"endpoints_c... | 1,734,973,321,000 | 2025-02-06T17:07:06 | 65 | 0 | ---
base_model: openai/whisper-large-v3-turbo
datasets:
- juanjucm/OpenHQ-SpeechT-GL-EN
language:
- gl
- en
library_name: transformers
license: mit
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v3-turbo-gl-en
results: []
---
# whisper-large-v3-turbo-OpenHQ-GL-EN
This model is a f... | [
"TRANSLATION"
] | Non_BioNLP |
Helsinki-NLP/opus-mt-id-sv | Helsinki-NLP | translation | [
"transformers",
"pytorch",
"tf",
"marian",
"text2text-generation",
"translation",
"id",
"sv",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,263,744,000 | 2023-08-16T11:58:09 | 49 | 0 | ---
license: apache-2.0
tags:
- translation
---
### opus-mt-id-sv
* source languages: id
* target languages: sv
* OPUS readme: [id-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/id-sv/README.md)
* dataset: opus
* model: transformer-align
* pre-processing: normalization + SentencePiece
* downl... | [
"TRANSLATION"
] | Non_BioNLP |
zhuwch/all-MiniLM-L6-v2 | zhuwch | sentence-similarity | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"en",
"dataset:s2orc",
"dataset:flax-sentence-embeddings/stackexchange_xml",
"dataset:ms_marco",
"dataset:gooaq",
"dataset:yahoo_answers_topics",
"dataset:code_search_net",
"dataset:search_qa",
"datase... | 1,695,195,422,000 | 2023-09-20T10:07:25 | 13 | 0 | ---
datasets:
- s2orc
- flax-sentence-embeddings/stackexchange_xml
- ms_marco
- gooaq
- yahoo_answers_topics
- code_search_net
- search_qa
- eli5
- snli
- multi_nli
- wikihow
- natural_questions
- trivia_qa
- embedding-data/sentence-compression
- embedding-data/flickr30k-captions
- embedding-data/altlex
- embedding-dat... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
timtarusov/distilbert-base-uncased-finetuned-emotion | timtarusov | text-classification | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,263,745,000 | 2022-02-13T08:48:03 | 114 | 0 | ---
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
args: default... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
VexPoli/distilbart-summarization-top-list | VexPoli | text2text-generation | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"generated_from_trainer",
"base_model:sshleifer/distilbart-xsum-6-6",
"base_model:finetune:sshleifer/distilbart-xsum-6-6",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,739,379,123,000 | 2025-02-12T18:07:58 | 17 | 0 | ---
base_model: sshleifer/distilbart-xsum-6-6
library_name: transformers
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbart-summarization-top-list
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should p... | [
"SUMMARIZATION"
] | Non_BioNLP |
TransferGraph/boychaboy_MNLI_roberta-base-finetuned-lora-tweet_eval_irony | TransferGraph | text-classification | [
"peft",
"safetensors",
"parquet",
"text-classification",
"dataset:tweet_eval",
"model-index",
"region:us"
] | 1,709,055,056,000 | 2024-02-29T13:37:12 | 0 | 0 | ---
base_model: boychaboy/MNLI_roberta-base
datasets:
- tweet_eval
library_name: peft
metrics:
- accuracy
tags:
- parquet
- text-classification
model-index:
- name: boychaboy_MNLI_roberta-base-finetuned-lora-tweet_eval_irony
results:
- task:
type: text-classification
name: Text Classification
datase... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
mertyrgn/distilbert-base-uncased-finetuned-emotion | mertyrgn | text-classification | [
"transformers",
"pytorch",
"tensorboard",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,652,622,001,000 | 2022-08-13T14:42:02 | 26 | 0 | ---
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
args: default... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
Xenova/distilbart-xsum-12-1 | Xenova | summarization | [
"transformers.js",
"onnx",
"bart",
"text2text-generation",
"summarization",
"base_model:sshleifer/distilbart-xsum-12-1",
"base_model:quantized:sshleifer/distilbart-xsum-12-1",
"region:us"
] | 1,693,932,378,000 | 2024-10-08T13:41:48 | 60 | 0 | ---
base_model: sshleifer/distilbart-xsum-12-1
library_name: transformers.js
pipeline_tag: summarization
---
https://huggingface.co/sshleifer/distilbart-xsum-12-1 with ONNX weights to be compatible with Transformers.js.
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML g... | [
"SUMMARIZATION"
] | Non_BioNLP |
vocabtrimmer/mbart-large-cc25-trimmed-ja-jaquad-qa | vocabtrimmer | text2text-generation | [
"transformers",
"pytorch",
"mbart",
"text2text-generation",
"question answering",
"ja",
"dataset:lmqg/qg_jaquad",
"arxiv:2210.03992",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,680,768,012,000 | 2023-04-06T08:04:59 | 10 | 0 | ---
datasets:
- lmqg/qg_jaquad
language: ja
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
pipeline_tag: text2text-generation
tags:
- question answering
widget:
- text: 'question: 新型車両として6000系が構想されたのは、製造費用のほか、どんな費用を抑えるためだったの?, context: 三多摩地区開発による沿線人口の増加、相模原線延伸による多摩ニュータウン乗り入れ、都営地下鉄10号線(現... | [
"QUESTION_ANSWERING"
] | Non_BioNLP |
AI-Sweden-Models/gpt-sw3-356m | AI-Sweden-Models | text-generation | [
"transformers",
"pytorch",
"safetensors",
"gpt2",
"text-generation",
"da",
"sv",
"no",
"en",
"is",
"license:other",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,671,021,117,000 | 2024-01-29T13:20:22 | 4,352 | 1 | ---
language:
- da
- sv
- 'no'
- en
- is
license: other
---
# Model description
[AI Sweden](https://huggingface.co/AI-Sweden-Models/)
**Base models**
[GPT-Sw3 126M](https://huggingface.co/AI-Sweden-Models/gpt-sw3-126m/) | [GPT-Sw3 356M](https://huggingface.co/AI-Sweden-Models/gpt-sw3-356m/) | [GPT-Sw3 1.3B](https:... | [
"SUMMARIZATION"
] | Non_BioNLP |
ucuncubayram/distilbert-emotion | ucuncubayram | text-classification | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:emotion",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_co... | 1,715,513,680,000 | 2024-05-12T11:53:33 | 4 | 0 | ---
base_model: distilbert-base-uncased
datasets:
- emotion
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
confi... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
mrapacz/interlinear-en-philta-emb-auto-diacritics-ob | mrapacz | text2text-generation | [
"transformers",
"pytorch",
"morph-t5-auto",
"text2text-generation",
"en",
"dataset:mrapacz/greek-interlinear-translations",
"license:cc-by-sa-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,738,957,967,000 | 2025-02-21T21:31:02 | 62 | 0 | ---
base_model:
- PhilTa
datasets:
- mrapacz/greek-interlinear-translations
language:
- en
library_name: transformers
license: cc-by-sa-4.0
metrics:
- bleu
---
# Model Card for Ancient Greek to English Interlinear Translation Model
This model performs interlinear translation from Ancient Greek to English, maintaining ... | [
"TRANSLATION"
] | Non_BioNLP |
vgarg/usecase_classifier_large_17_04_24 | vgarg | text-classification | [
"setfit",
"safetensors",
"xlm-roberta",
"sentence-transformers",
"text-classification",
"generated_from_setfit_trainer",
"arxiv:2209.11055",
"base_model:intfloat/multilingual-e5-large",
"base_model:finetune:intfloat/multilingual-e5-large",
"model-index",
"region:us"
] | 1,713,337,576,000 | 2024-04-29T08:21:01 | 5 | 0 | ---
base_model: intfloat/multilingual-e5-large
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: What should be Ideal Promo Duration?
- text: Compare the performance of top skus
- text: ... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
apwic/summarization-unipelt-3 | apwic | null | [
"tensorboard",
"generated_from_trainer",
"id",
"base_model:LazarusNLP/IndoNanoT5-base",
"base_model:finetune:LazarusNLP/IndoNanoT5-base",
"license:apache-2.0",
"region:us"
] | 1,720,353,645,000 | 2024-07-07T17:19:15 | 0 | 0 | ---
base_model: LazarusNLP/IndoNanoT5-base
language:
- id
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: summarization-unipelt-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably ... | [
"SUMMARIZATION"
] | Non_BioNLP |
AI4Chem/CHEMLLM-2b-1_5 | AI4Chem | text-generation | [
"transformers",
"safetensors",
"internlm2",
"feature-extraction",
"chemistry",
"text-generation",
"conversational",
"custom_code",
"en",
"zh",
"arxiv:2402.06852",
"license:apache-2.0",
"region:us"
] | 1,719,304,294,000 | 2024-09-17T16:02:49 | 172 | 1 | ---
language:
- en
- zh
license: apache-2.0
pipeline_tag: text-generation
tags:
- chemistry
---
# ChemLLM-2B: Mini LLM for Chemistry and Molecule Science
ChemLLM, The First Open-source Large Language Model for Chemistry and Molecule Science, Build based on InternLM-2 with ❤
[![Paper page](https://huggingface.co/datas... | [
"TRANSLATION"
] | Non_BioNLP |
ChaniM/text-summarization-bart-large-cnn-three-percent | ChaniM | text2text-generation | [
"transformers",
"pytorch",
"tensorboard",
"bart",
"text2text-generation",
"generated_from_trainer",
"dataset:cnn_dailymail",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,686,237,968,000 | 2023-06-09T06:08:20 | 34 | 0 | ---
datasets:
- cnn_dailymail
license: mit
tags:
- generated_from_trainer
model-index:
- name: text-summarization-bart-large-cnn-three-percent
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, t... | [
"SUMMARIZATION"
] | Non_BioNLP |
TheBloke/airoboros-m-7B-3.0-GGUF | TheBloke | null | [
"transformers",
"gguf",
"mistral",
"dataset:jondurbin/airoboros-3.0",
"base_model:jondurbin/airoboros-m-7b-3.0",
"base_model:quantized:jondurbin/airoboros-m-7b-3.0",
"license:apache-2.0",
"region:us"
] | 1,696,546,074,000 | 2023-10-05T23:27:14 | 711 | 4 | ---
base_model: jondurbin/airoboros-m-7b-3.0
datasets:
- jondurbin/airoboros-3.0
license: apache-2.0
model_name: Airoboros M 7B 3.0
inference: false
model_creator: Jon Durbin
model_type: mistral
prompt_template: '[INST] <<SYS>>
You are a help, unbiased, uncensored assistant.
<</SYS>
{prompt} [/INST]
'
quan... | [
"QUESTION_ANSWERING",
"SUMMARIZATION"
] | TBD |
gokulsrinivasagan/distilbert_lda_100_v1_book_wnli | gokulsrinivasagan | text-classification | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"en",
"dataset:glue",
"base_model:gokulsrinivasagan/distilbert_lda_100_v1_book",
"base_model:finetune:gokulsrinivasagan/distilbert_lda_100_v1_book",
"model-index",
"autotrain_compatible... | 1,733,767,932,000 | 2024-12-09T18:12:45 | 15 | 0 | ---
base_model: gokulsrinivasagan/distilbert_lda_100_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_100_v1_book_wnli
results:
- task:
type: text-classification
name: Text Classification
dataset... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
sbintuitions/modernbert-ja-130m | sbintuitions | fill-mask | [
"transformers",
"safetensors",
"modernbert",
"fill-mask",
"ja",
"en",
"arxiv:2412.13663",
"arxiv:2104.09864",
"arxiv:2404.10830",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,738,824,697,000 | 2025-02-27T02:35:36 | 7,603 | 39 | ---
language:
- ja
- en
library_name: transformers
license: mit
pipeline_tag: fill-mask
---
# ModernBERT-Ja-130M
This repository provides Japanese ModernBERT trained by [SB Intuitions](https://www.sbintuitions.co.jp/).
[ModernBERT](https://arxiv.org/abs/2412.13663) is a new variant of the BERT model that combines lo... | [
"NAMED_ENTITY_RECOGNITION"
] | Non_BioNLP |
sarwarbeing/child-labour-remidiation-few-shot | sarwarbeing | text-classification | [
"sentence-transformers",
"pytorch",
"deberta-v2",
"setfit",
"text-classification",
"arxiv:2209.11055",
"license:apache-2.0",
"region:us"
] | 1,693,140,929,000 | 2023-08-27T19:19:50 | 10 | 0 | ---
license: apache-2.0
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
---
# sarwarbeing/child-labour-remidiation-few-shot
This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an effic... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
Alassea/glue_sst_classifier | Alassea | text-classification | [
"transformers",
"pytorch",
"tensorboard",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:glue",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,650,972,834,000 | 2022-04-26T12:20:06 | 113 | 0 | ---
datasets:
- glue
license: apache-2.0
metrics:
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: glue_sst_classifier
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: glue
type: glue
args: sst2
metrics:
- type: f1
... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
davidadamczyk/ModernBERT-base-DPR-8e-05 | davidadamczyk | sentence-similarity | [
"sentence-transformers",
"safetensors",
"modernbert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:11662655",
"loss:CachedMultipleNegativesRankingLoss",
"en",
"dataset:sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1",
"arxiv:1908.100... | 1,740,495,168,000 | 2025-02-25T14:53:13 | 11 | 0 | ---
base_model: answerdotai/ModernBERT-base
datasets:
- sentence-transformers/msmarco-co-condenser-margin-mse-sym-mnrl-mean-v1
language:
- en
library_name: sentence-transformers
metrics:
- cosine_accuracy
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- genera... | [
"TEXT_CLASSIFICATION"
] | Non_BioNLP |
zjunlp/zhixi-13b-lora | zjunlp | text-generation | [
"safetensors",
"code",
"text-generation",
"en",
"zh",
"arxiv:2302.13971",
"arxiv:2305.11527",
"license:apache-2.0",
"region:us"
] | 1,684,816,611,000 | 2023-06-26T07:41:10 | 0 | 22 | ---
language:
- en
- zh
license: apache-2.0
pipeline_tag: text-generation
tags:
- code
---
<p align="center" width="100%">
<a href="" target="_blank"><img src="https://github.com/zjunlp/KnowLM/blob/main/assets/logo_zhixi.png?raw=true" alt="ZJU-KnowLM" style="width: 40%; min-width: 40px; display: block; margin: auto;">... | [
"NAMED_ENTITY_RECOGNITION",
"RELATION_EXTRACTION",
"EVENT_EXTRACTION",
"TRANSLATION"
] | BioNLP |
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