id stringlengths 11 95 | author stringlengths 3 36 | task_category stringclasses 16
values | tags listlengths 1 4.05k | created_time int64 1.65k 1.74k | last_modified int64 1.62k 1.74k | downloads int64 0 15.6M | likes int64 0 4.86k | README stringlengths 246 1.01M | matched_task listlengths 1 8 | matched_bigbio_names listlengths 1 8 | is_bionlp stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|---|
keeeeenw/MicroLlama-text-embedding | keeeeenw | sentence-similarity | [
"sentence-transformers",
"safetensors",
"llama",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:65749",
"loss:MultipleNegativesRankingLoss",
"loss:SoftmaxLoss",
"loss:CoSENTLoss",
"en",
"dataset:sentence-transformers/all-nli",
"dataset:sentence-transform... | 1,731 | 1,731 | 121 | 1 | ---
base_model: keeeeenw/MicroLlama
datasets:
- sentence-transformers/all-nli
- sentence-transformers/stsb
- sentence-transformers/quora-duplicates
- sentence-transformers/natural-questions
language:
- en
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-simi... | [
"TEXT_CLASSIFICATION"
] | [
"MEDAL"
] | Non_BioNLP |
Godefroyduchalard/solone-embedding-final2 | Godefroyduchalard | sentence-similarity | [
"sentence-transformers",
"safetensors",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:19485",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:OrdalieTech/Solon-embeddings-large-0.1",
"base_model:finetune:OrdalieTech/... | 1,732 | 1,733 | 0 | 0 | ---
base_model: OrdalieTech/Solon-embeddings-large-0.1
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:19485
- loss:MultipleNegativesRankingLoss
widget:
- source_sentence: chef de bord
... | [
"TEXT_CLASSIFICATION"
] | [
"CAS"
] | Non_BioNLP |
pucpr/biobertpt-bio | pucpr | fill-mask | [
"transformers",
"pytorch",
"tf",
"jax",
"bert",
"fill-mask",
"pt",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646 | 1,669 | 76 | 6 | ---
language: pt
widget:
- text: O principal [MASK] da COVID-19 é tosse seca.
- text: O vírus da gripe apresenta um [MASK] constituído por segmentos de ácido ribonucleico.
thumbnail: https://raw.githubusercontent.com/HAILab-PUCPR/BioBERTpt/master/images/logo-biobertpr1.png
---
<img src="https://raw.githubusercontent.c... | [
"NAMED_ENTITY_RECOGNITION"
] | [
"SCIELO"
] | TBD |
ai-forever/bert-base-NER-reptile-5-datasets | ai-forever | token-classification | [
"transformers",
"pytorch",
"bert",
"token-classification",
"PyTorch",
"en",
"dataset:conll2003",
"dataset:wnut_17",
"dataset:jnlpba",
"dataset:conll2012",
"dataset:BTC",
"dataset:dfki-nlp/few-nerd",
"arxiv:2010.02405",
"model-index",
"autotrain_compatible",
"region:us"
] | 1,646 | 1,643 | 165 | 3 | ---
datasets:
- conll2003
- wnut_17
- jnlpba
- conll2012
- BTC
- dfki-nlp/few-nerd
language:
- en
pipeline_tag: false
tags:
- PyTorch
inference: false
model-index:
- name: bert-base-NER-reptile-5-datasets
results:
- task:
type: named-entity-recognition
name: few-shot-ner
dataset:
name: few-ner... | [
"NAMED_ENTITY_RECOGNITION"
] | [
"JNLPBA"
] | BioNLP |
RichardErkhov/EleutherAI_-_pythia-1b-v0-gguf | RichardErkhov | null | [
"gguf",
"arxiv:2101.00027",
"arxiv:2201.07311",
"endpoints_compatible",
"region:us"
] | 1,730 | 1,730 | 478 | 1 | ---
{}
---
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-1b-v0 - GGUF
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/... | [
"QUESTION_ANSWERING",
"TRANSLATION"
] | [
"SCIQ"
] | Non_BioNLP |
SEACrowd/mdeberta-v3_sea_translationese | SEACrowd | text-classification | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"translationese",
"classification",
"sea",
"southeast asia",
"en",
"id",
"ms",
"vi",
"th",
"lo",
"km",
"my",
"tl",
"arxiv:2406.10118",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"... | 1,716 | 1,718 | 23 | 3 | ---
language:
- en
- id
- ms
- vi
- th
- lo
- km
- my
- tl
library_name: transformers
license: apache-2.0
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- translationese
- classification
- sea
- southeast asia
---
<img width="100%" alt="SEACrowd Logo" src="https://github.com/SEACrowd/.github/blob/main/pro... | [
"TRANSLATION"
] | [
"CHIA"
] | Non_BioNLP |
croissantllm/CroissantLLMChat-v0.1 | croissantllm | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"legal",
"code",
"text-generation-inference",
"art",
"conversational",
"fr",
"en",
"dataset:croissantllm/croissant_dataset",
"dataset:croissantllm/CroissantLLM-2201-sft",
"dataset:cerebras/SlimPajama-627B",
"dataset:uonlp/Cultura... | 1,706 | 1,714 | 3,614 | 50 | ---
datasets:
- croissantllm/croissant_dataset
- croissantllm/CroissantLLM-2201-sft
- cerebras/SlimPajama-627B
- uonlp/CulturaX
- pg19
- bigcode/starcoderdata
language:
- fr
- en
license: mit
pipeline_tag: text-generation
tags:
- legal
- code
- text-generation-inference
- art
---
# CroissantLLMChat (190k steps + Chat)... | [
"TRANSLATION"
] | [
"CRAFT"
] | Non_BioNLP |
Shashwat13333/msmarco-distilbert-base-v4 | Shashwat13333 | sentence-similarity | [
"sentence-transformers",
"safetensors",
"distilbert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:150",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"en",
"arxiv:1908.10084",
"arxiv:2205.13147",
"arxiv:1705.00652",
"base_model:sentenc... | 1,738 | 1,738 | 12 | 0 | ---
base_model: sentence-transformers/msmarco-distilbert-base-v4
language:
- en
library_name: sentence-transformers
license: apache-2.0
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_... | [
"TEXT_CLASSIFICATION"
] | [
"CRAFT"
] | Non_BioNLP |
linhphanff/stella_en_1.5B_v5_clone | linhphanff | sentence-similarity | [
"sentence-transformers",
"pytorch",
"safetensors",
"qwen2",
"text-generation",
"mteb",
"transformers",
"sentence-similarity",
"custom_code",
"arxiv:2205.13147",
"license:mit",
"model-index",
"autotrain_compatible",
"text-generation-inference",
"text-embeddings-inference",
"endpoints_co... | 1,727 | 1,727 | 15 | 0 | ---
license: mit
tags:
- mteb
- sentence-transformers
- transformers
- sentence-similarity
model-index:
- name: stella_en_1.5B_v5
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
sunzx0810/gte-Qwen2-7B-instruct-Q5_K_M-GGUF | sunzx0810 | sentence-similarity | [
"sentence-transformers",
"gguf",
"qwen2",
"text-generation",
"mteb",
"transformers",
"Qwen2",
"sentence-similarity",
"llama-cpp",
"gguf-my-repo",
"custom_code",
"base_model:Alibaba-NLP/gte-Qwen2-7B-instruct",
"base_model:quantized:Alibaba-NLP/gte-Qwen2-7B-instruct",
"license:apache-2.0",
... | 1,718 | 1,719 | 114 | 6 | ---
base_model: Alibaba-NLP/gte-Qwen2-7B-instruct
license: apache-2.0
tags:
- mteb
- sentence-transformers
- transformers
- Qwen2
- sentence-similarity
- llama-cpp
- gguf-my-repo
model-index:
- name: gte-qwen2-7B-instruct
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactual... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
LiteLLMs/Llama3-OpenBioLLM-8B-GGUF | LiteLLMs | null | [
"gguf",
"llama-3",
"llama",
"Mixtral",
"instruct",
"finetune",
"chatml",
"DPO",
"RLHF",
"gpt4",
"distillation",
"GGUF",
"en",
"arxiv:2305.18290",
"arxiv:2303.13375",
"arxiv:2212.13138",
"arxiv:2305.09617",
"arxiv:2402.07023",
"base_model:meta-llama/Meta-Llama-3-8B",
"base_model... | 1,714 | 1,714 | 25 | 0 | ---
base_model: meta-llama/Meta-Llama-3-8B
language:
- en
license: llama3
tags:
- llama-3
- llama
- Mixtral
- instruct
- finetune
- chatml
- DPO
- RLHF
- gpt4
- distillation
- GGUF
widget:
- example_title: OpenBioLLM-8B
messages:
- role: system
content: You are an expert and experienced from the healthcare and ... | [
"QUESTION_ANSWERING"
] | [
"MEDQA",
"PUBMEDQA"
] | BioNLP |
twadada/nmc-cls-100_correct | twadada | null | [
"mteb",
"model-index",
"region:us"
] | 1,726 | 1,726 | 0 | 0 | ---
tags:
- mteb
model-index:
- name: nomic_classification_100
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: None
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accur... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
minhtuan7akp/gte-base-vietnamese-finetune-matryoshka | minhtuan7akp | sentence-similarity | [
"sentence-transformers",
"safetensors",
"new",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:21892",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"custom_code",
"arxiv:1908.10084",
"arxiv:2205.13147",
"arxiv:1705.00652",
"base_model:Ali... | 1,741 | 1,741 | 10 | 0 | ---
base_model: Alibaba-NLP/gte-multilingual-base
library_name: sentence-transformers
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
- cosine_recall@5
- cos... | [
"TEXT_CLASSIFICATION"
] | [
"CHIA"
] | Non_BioNLP |
legaltextai/modernbert-embed-ft-const-legal-matryoshka | legaltextai | sentence-similarity | [
"sentence-transformers",
"safetensors",
"modernbert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:842",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"en",
"arxiv:1908.10084",
"arxiv:2205.13147",
"arxiv:1705.00652",
"base_model:nomic-a... | 1,739 | 1,739 | 29 | 1 | ---
base_model: nomic-ai/modernbert-embed-base
language:
- en
library_name: sentence-transformers
license: apache-2.0
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_... | [
"TEXT_CLASSIFICATION"
] | [
"BEAR",
"CAS"
] | Non_BioNLP |
croissantllm/base_35k | croissantllm | text2text-generation | [
"transformers",
"pytorch",
"llama",
"text-generation",
"legal",
"code",
"text-generation-inference",
"art",
"text2text-generation",
"fr",
"en",
"dataset:cerebras/SlimPajama-627B",
"dataset:uonlp/CulturaX",
"dataset:pg19",
"dataset:bigcode/starcoderdata",
"license:mit",
"autotrain_com... | 1,705 | 1,706 | 5 | 0 | ---
datasets:
- cerebras/SlimPajama-627B
- uonlp/CulturaX
- pg19
- bigcode/starcoderdata
language:
- fr
- en
license: mit
pipeline_tag: text2text-generation
tags:
- legal
- code
- text-generation-inference
- art
---
# CroissantLLM - Base (35k steps)
This model is part of the CroissantLLM initiative, and corresponds t... | [
"TRANSLATION"
] | [
"CRAFT"
] | Non_BioNLP |
serdarcaglar/roberta-base-biomedical-es | serdarcaglar | fill-mask | [
"transformers",
"pytorch",
"safetensors",
"roberta",
"fill-mask",
"es",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,694 | 1,695 | 46 | 1 | ---
language:
- es
---
language:
- es
tags:
- biomedical
- spanish
metrics:
- ppl
# Biomedical language model for Spanish
## Table of contents
<details>
<summary>Click to expand</summary>
- [Model description](#model-description)
- [Intended uses and limitations](#intended-use)
- [How to use](#how-to-use)
- [Lim... | [
"NAMED_ENTITY_RECOGNITION",
"TEXT_CLASSIFICATION"
] | [
"CODIESP",
"SCIELO"
] | BioNLP |
sultan/BioM-ALBERT-xxlarge-PMC | sultan | fill-mask | [
"transformers",
"pytorch",
"albert",
"fill-mask",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646 | 1,699 | 534 | 4 | ---
{}
---
# BioM-Transformers: Building Large Biomedical Language Models with BERT, ALBERT and ELECTRA
# Abstract
The impact of design choices on the performance
of biomedical language models recently
has been a subject for investigation. In
this paper, we empirically study biomedical
domain adaptation with large t... | [
"TEXT_CLASSIFICATION"
] | [
"BLURB",
"CHEMPROT"
] | BioNLP |
clinicalnlplab/me-llama | clinicalnlplab | null | [
"transformers",
"medical",
"health",
"llama",
"llama2",
"en",
"dataset:togethercomputer/RedPajama-Data-1T",
"dataset:bigbio/med_qa",
"arxiv:2402.12749",
"license:llama2",
"endpoints_compatible",
"region:us"
] | 1,717 | 1,717 | 0 | 12 | ---
datasets:
- togethercomputer/RedPajama-Data-1T
- bigbio/med_qa
language:
- en
library_name: transformers
license: llama2
tags:
- medical
- health
- llama
- llama2
---
# Me-LLaMA
## Model Overview
The Me-LLaMA model consists of two foundation models: Me-LLaMA 13B and Me-LLaMA 70B, along with their chat-enhanced c... | [
"RELATION_EXTRACTION",
"SUMMARIZATION"
] | [
"MEDNLI",
"MEDQA",
"PUBMEDQA"
] | BioNLP |
raghavlight/TDTE | raghavlight | null | [
"safetensors",
"mteb",
"model-index",
"region:us"
] | 1,718 | 1,718 | 0 | 3 | ---
tags:
- mteb
model-index:
- name: 0523_mistralv2_sum3echo512_bbcc_8_16_16
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | BioNLP |
Geolumina/instructor-xl | Geolumina | sentence-similarity | [
"sentence-transformers",
"pytorch",
"t5",
"text-embedding",
"embeddings",
"information-retrieval",
"beir",
"text-classification",
"language-model",
"text-clustering",
"text-semantic-similarity",
"text-evaluation",
"prompt-retrieval",
"text-reranking",
"feature-extraction",
"sentence-si... | 1,709 | 1,738 | 9 | 1 | ---
language: en
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- text-embedding
- embeddings
- information-retrieval
- beir
- text-classification
- language-model
- text-clustering
- text-semantic-similarity
- text-evaluation
- prompt-retrieval
- text-reranking
- sentence-transformers
- feature-extraction... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
Shashwat13333/bge-base-en-v1.5 | Shashwat13333 | sentence-similarity | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:150",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"en",
"arxiv:1908.10084",
"arxiv:2205.13147",
"arxiv:1705.00652",
"base_model:BAAI/bge-base... | 1,738 | 1,738 | 4 | 0 | ---
base_model: BAAI/bge-base-en-v1.5
language:
- en
library_name: sentence-transformers
license: apache-2.0
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
... | [
"TEXT_CLASSIFICATION"
] | [
"CRAFT"
] | Non_BioNLP |
BSC-NLP4BIA/biomedical-term-classifier-setfit | BSC-NLP4BIA | text-classification | [
"sentence-transformers",
"pytorch",
"roberta",
"setfit",
"text-classification",
"bert",
"biomedical",
"lexical semantics",
"bionlp",
"es",
"license:apache-2.0",
"region:us"
] | 1,716 | 1,716 | 21 | 0 | ---
language:
- es
license: apache-2.0
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- bert
- biomedical
- lexical semantics
- bionlp
---
# Biomedical term classifier with SetFit in Spanish
## Table of contents
<details>
<summary>Click to expand</summary>
- [Model des... | [
"TEXT_CLASSIFICATION"
] | [
"CANTEMIST",
"DISTEMIST",
"PHARMACONER",
"SYMPTEMIST"
] | BioNLP |
mav23/gte-Qwen2-1.5B-instruct-GGUF | mav23 | sentence-similarity | [
"sentence-transformers",
"gguf",
"mteb",
"transformers",
"Qwen2",
"sentence-similarity",
"arxiv:2308.03281",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us",
"conversational"
] | 1,728 | 1,728 | 631 | 2 | ---
license: apache-2.0
tags:
- mteb
- sentence-transformers
- transformers
- Qwen2
- sentence-similarity
model-index:
- name: gte-qwen2-7B-instruct
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: ... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
model-attribution-challenge/bloom-2b5 | model-attribution-challenge | text-generation | [
"transformers",
"pytorch",
"bloom",
"feature-extraction",
"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",
"... | 1,660 | 1,664 | 31 | 0 | ---
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
- zhs
- zht
- zu
license: bigscience-bloom-rail-1.0
pipeline_tag: text-gener... | [
"QUESTION_ANSWERING",
"SUMMARIZATION"
] | [
"PUBMEDQA",
"SCIQ"
] | Non_BioNLP |
twadada/mpn | twadada | null | [
"mteb",
"model-index",
"region:us"
] | 1,725 | 1,725 | 0 | 0 | ---
tags:
- mteb
model-index:
- name: mpnet_main
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: None
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
valu... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
Cloyne/vietnamese-sbert | Cloyne | sentence-similarity | [
"sentence-transformers",
"safetensors",
"roberta",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:120210",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:keepitreal/vietnamese-sbert",
"base_model:finetune:keepitrea... | 1,730 | 1,730 | 157 | 0 | ---
base_model: keepitreal/vietnamese-sbert
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:120210
- loss:MultipleNegativesRankingLoss
widget:
- source_sentence: Chủ tịch Ủy ban nhân dâ... | [
"TEXT_CLASSIFICATION"
] | [
"CHIA"
] | Non_BioNLP |
jonathanjordan21/paraphrase-multilingual-MiniLM-L12-v2-helpfulness | jonathanjordan21 | sentence-similarity | [
"sentence-transformers",
"tensorboard",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:21362",
"loss:CoSENTLoss",
"loss:BatchSemiHardTripletLoss",
"loss:SoftmaxLoss",
"loss:CosineSimilarityLoss",
"en",
"dataset:jonathanjordan21/h... | 1,730 | 1,730 | 9 | 0 | ---
base_model: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
datasets:
- jonathanjordan21/helpfulness-classification
language:
- en
library_name: sentence-transformers
metrics:
- pearson_cosine
- spearman_cosine
- pearson_manhattan
- spearman_manhattan
- pearson_euclidean
- spearman_euclidean
- pearson_d... | [
"TEXT_CLASSIFICATION",
"SEMANTIC_SIMILARITY",
"TRANSLATION",
"SUMMARIZATION"
] | [
"CRAFT"
] | Non_BioNLP |
zeroMN/SHMT | zeroMN | audio-text-to-text | [
"transformers",
"transformer",
"multimodal",
"vqa",
"text",
"audio",
"audio-text-to-text",
"en",
"zh",
"dataset:zeroMN/nlp_corpus_zh",
"dataset:zeroMN/hanlp_date-zh",
"dataset:nyu-mll/glue",
"dataset:aps/super_glue",
"dataset:facebook/anli",
"dataset:tasksource/babi_nli",
"dataset:zero... | 1,736 | 1,737 | 99 | 1 | ---
datasets:
- zeroMN/nlp_corpus_zh
- zeroMN/hanlp_date-zh
- nyu-mll/glue
- aps/super_glue
- facebook/anli
- tasksource/babi_nli
- zeroMN/AVEdate
- sick
- snli
- scitail
- hans
- alisawuffles/WANLI
- tasksource/recast
- sileod/probability_words_nli
- joey234/nan-nli
- pietrolesci/nli_fever
- pietrolesci/breaking_nli
-... | [
"QUESTION_ANSWERING"
] | [
"HEAD-QA",
"MEDQA",
"SCICITE",
"SCIFACT",
"SCIQ",
"SCITAIL"
] | Non_BioNLP |
zjunlp/OneKE | zjunlp | text-generation | [
"transformers",
"pytorch",
"llama",
"text-generation",
"en",
"zh",
"dataset:zjunlp/iepile",
"dataset:zjunlp/InstructIE",
"arxiv:2402.14710",
"license:cc-by-nc-sa-4.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,708 | 1,714 | 353 | 42 | ---
datasets:
- zjunlp/iepile
- zjunlp/InstructIE
language:
- en
- zh
license: cc-by-nc-sa-4.0
---
<p align="center">
<a href="https://github.com/zjunlp/deepke"> <img src="assets/oneke_logo.png" width="400"/></a>
<p>
<p align="center">
<a href="https://oneke.openkg.cn/">
<img alt="Documentation" src... | [
"NAMED_ENTITY_RECOGNITION",
"RELATION_EXTRACTION",
"EVENT_EXTRACTION"
] | [
"BEAR"
] | Non_BioNLP |
w601sxs/b1ade-embed-kd | w601sxs | sentence-similarity | [
"sentence-transformers",
"safetensors",
"bert",
"mteb",
"sentence-similarity",
"model-index",
"autotrain_compatible",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | 1,716 | 1,716 | 276 | 1 | ---
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- mteb
model-index:
- name: b1ade_embed_kd
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification
type: mteb/amazon_counterfactual
config: default
split: test
... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
vidhi0206/setfit-paraphrase-mpnet-base-v2 | vidhi0206 | 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"
] | 1,705 | 1,707 | 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: 'versace art portfolio up for sale the art collection of murdered fashion... | [
"TEXT_CLASSIFICATION",
"TRANSLATION"
] | [
"MEDAL"
] | Non_BioNLP |
NickyNicky/StaticEmbedding-MatryoshkaLoss-gemma-2-2b-en-es | NickyNicky | sentence-similarity | [
"sentence-transformers",
"safetensors",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:4322286",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:2205.13147",
"arxiv:1705.00652",
"license:apache-2.0",
"autotrain_comp... | 1,737 | 1,737 | 0 | 2 | ---
library_name: sentence-transformers
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:4322286
- loss:MatryoshkaLoss
- loss:MultipleNegativesRankingLoss
widget:
- source_sentence: how to sign legal do... | [
"TEXT_CLASSIFICATION"
] | [
"CRAFT"
] | Non_BioNLP |
BAAI/bge-large-zh-v1.5 | BAAI | feature-extraction | [
"sentence-transformers",
"pytorch",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"zh",
"arxiv:2401.03462",
"arxiv:2312.15503",
"arxiv:2311.13534",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"autotrain_compatible",
"text-embeddings-inference",
"endpoi... | 1,694 | 1,712 | 210,152 | 490 | ---
language:
- zh
license: mit
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
<h1 align="center">FlagEmbedding</h1>
<h4 align="center">
<p>
<a href=#model-list>Model List</a> |
<a href=#frequently-asked-questions>FAQ</a> |
<a href=#usage>Usa... | [
"SEMANTIC_SIMILARITY",
"SUMMARIZATION"
] | [
"BEAR"
] | Non_BioNLP |
CAiRE/UniVaR-lambda-80 | CAiRE | sentence-similarity | [
"sentence-transformers",
"safetensors",
"nomic_bert",
"feature-extraction",
"sentence-similarity",
"mteb",
"transformers",
"transformers.js",
"custom_code",
"en",
"arxiv:2402.01613",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"text-embeddings-inference",
"endpoints_co... | 1,718 | 1,718 | 8 | 0 | ---
language:
- en
library_name: sentence-transformers
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- feature-extraction
- sentence-similarity
- mteb
- transformers
- transformers.js
model-index:
- name: epoch_0_model
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCou... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
Muennighoff/SGPT-2.7B-weightedmean-msmarco-specb-bitfit | Muennighoff | sentence-similarity | [
"sentence-transformers",
"pytorch",
"gpt_neo",
"feature-extraction",
"sentence-similarity",
"mteb",
"arxiv:2202.08904",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646 | 1,679 | 30 | 3 | ---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: SGPT-2.7B-weightedmean-msmarco-specb-bitfit
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/am... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
Severian/nomic | Severian | feature-extraction | [
"sentence-transformers",
"nomic_bert",
"feature-extraction",
"sentence-similarity",
"mteb",
"transformers",
"transformers.js",
"custom_code",
"en",
"arxiv:2402.01613",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,707 | 1,707 | 9 | 0 | ---
language:
- en
library_name: sentence-transformers
license: apache-2.0
pipeline_tag: feature-extraction
tags:
- feature-extraction
- sentence-similarity
- mteb
- transformers
- transformers.js
model-index:
- name: epoch_0_model
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCoun... | [
"SUMMARIZATION"
] | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
RichardErkhov/EleutherAI_-_pythia-160m-v0-gguf | RichardErkhov | null | [
"gguf",
"arxiv:2101.00027",
"arxiv:2201.07311",
"endpoints_compatible",
"region:us"
] | 1,730 | 1,730 | 103 | 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-160m-v0 - GGUF
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.c... | [
"QUESTION_ANSWERING",
"TRANSLATION"
] | [
"SCIQ"
] | Non_BioNLP |
medspaner/flair-clinical-trials-temp-ents | medspaner | null | [
"license:cc-by-nc-4.0",
"region:us"
] | 1,695 | 1,727 | 0 | 0 | ---
license: cc-by-nc-4.0
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: flair-clinical-trials-temp-ents
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 com... | [
"NAMED_ENTITY_RECOGNITION"
] | [
"SCIELO"
] | BioNLP |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.