id stringlengths 9 104 | author stringlengths 3 36 | task_category stringclasses 32
values | tags listlengths 1 4.05k | created_time int64 1,646B 1,742B | last_modified timestamp[s]date 2021-02-13 00:06:56 2025-03-18 09:30:19 | downloads int64 0 15.6M | likes int64 0 4.86k | README stringlengths 44 1.01M | matched_bigbio_names listlengths 1 8 | is_bionlp stringclasses 3
values |
|---|---|---|---|---|---|---|---|---|---|---|
Baiming123/Calcu_Disease_Similarity | Baiming123 | sentence-similarity | [
"sentence-transformers",
"pytorch",
"bert",
"sentence-similarity",
"dataset:Baiming123/MeSHDS",
"base_model:sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
"base_model:finetune:sentence-transformers/multi-qa-MiniLM-L6-cos-v1",
"doi:10.57967/hf/3108",
"autotrain_compatible",
"text-embeddings-infe... | 1,726,847,893,000 | 2024-12-14T10:10:29 | 0 | 3 | ---
base_model:
- sentence-transformers/multi-qa-MiniLM-L6-cos-v1
datasets:
- Baiming123/MeSHDS
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
---
# Model Description
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensio... | [
"MIRNA"
] | BioNLP |
johnsnowlabs/JSL-MedMNX-7B-SFT | johnsnowlabs | text-generation | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"reward model",
"RLHF",
"medical",
"conversational",
"en",
"license:cc-by-nc-nd-4.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,713,245,240,000 | 2024-04-18T19:25:47 | 2,926 | 3 | ---
language:
- en
library_name: transformers
license: cc-by-nc-nd-4.0
tags:
- reward model
- RLHF
- medical
---
# JSL-MedMNX-7B-SFT
[<img src="https://repository-images.githubusercontent.com/104670986/2e728700-ace4-11ea-9cfc-f3e060b25ddf">](http://www.johnsnowlabs.com)
JSL-MedMNX-7B-SFT is a 7 Billion parameter mod... | [
"MEDQA",
"PUBMEDQA"
] | BioNLP |
RichardErkhov/HPAI-BSC_-_Llama3-Aloe-8B-Alpha-gguf | RichardErkhov | null | [
"gguf",
"arxiv:2405.01886",
"endpoints_compatible",
"region:us",
"conversational"
] | 1,730,286,893,000 | 2024-10-30T15:06:18 | 75 | 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)
Llama3-Aloe-8B-Alpha - GGUF
- Model creator: https://huggingface.co/HPAI-BSC/
- Original model: https://huggingfa... | [
"MEDQA",
"PUBMEDQA"
] | BioNLP |
Rodrigo1771/bsc-bio-ehr-es-symptemist-word2vec-85-ner | Rodrigo1771 | token-classification | [
"transformers",
"tensorboard",
"safetensors",
"roberta",
"token-classification",
"generated_from_trainer",
"dataset:Rodrigo1771/symptemist-85-ner",
"base_model:PlanTL-GOB-ES/bsc-bio-ehr-es",
"base_model:finetune:PlanTL-GOB-ES/bsc-bio-ehr-es",
"license:apache-2.0",
"model-index",
"autotrain_com... | 1,725,476,428,000 | 2024-09-04T19:11:15 | 13 | 0 | ---
base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
datasets:
- Rodrigo1771/symptemist-85-ner
library_name: transformers
license: apache-2.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- token-classification
- generated_from_trainer
model-index:
- name: output
results:
- task:
type: token-classification
... | [
"SYMPTEMIST"
] | BioNLP |
kunkunhu/craft_mol | kunkunhu | null | [
"region:us"
] | 1,737,819,517,000 | 2025-01-26T09:08:28 | 0 | 0 | ---
{}
---
# CRAFT
CRAFT: Consistent Representational Fusion of Three Molecular Modalities | [
"CRAFT"
] | Non_BioNLP |
jiey2/DISC-MedLLM | jiey2 | text-generation | [
"transformers",
"pytorch",
"baichuan",
"text-generation",
"medical",
"custom_code",
"zh",
"dataset:Flmc/DISC-Med-SFT",
"arxiv:2308.14346",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,699,094,632,000 | 2023-11-04T10:48:48 | 16 | 1 | ---
datasets:
- Flmc/DISC-Med-SFT
language:
- zh
license: apache-2.0
tags:
- medical
---
This repository contains the DISC-MedLLM, version of Baichuan-13b-base as the base model.
**Please note that due to the ongoing development of the project, the model weights in this repository may differ from those in our currentl... | [
"MEDDIALOG"
] | BioNLP |
ManoloPueblo/LLM_MERGE_CC4 | ManoloPueblo | null | [
"safetensors",
"mistral",
"merge",
"mergekit",
"lazymergekit",
"llm-merge-cc4",
"OpenPipe/mistral-ft-optimized-1218",
"mlabonne/NeuralHermes-2.5-Mistral-7B",
"license:apache-2.0",
"region:us"
] | 1,731,246,930,000 | 2024-11-10T14:01:19 | 6 | 1 | ---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- llm-merge-cc4
- OpenPipe/mistral-ft-optimized-1218
- mlabonne/NeuralHermes-2.5-Mistral-7B
---
# LLM_MERGE_CC4
LLM_MERGE_CC4 est une fusion des modèles suivants créée par ManoloPueblo utilisant [mergekit](https://github.com/cg123/mergekit):
* [OpenPipe/... | [
"CAS"
] | Non_BioNLP |
razent/SciFive-large-Pubmed_PMC-MedNLI | razent | text2text-generation | [
"transformers",
"pytorch",
"tf",
"t5",
"text2text-generation",
"mednli",
"en",
"dataset:pubmed",
"dataset:pmc/open_access",
"arxiv:2106.03598",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,647,797,073,000 | 2022-03-22T04:05:21 | 1,302 | 2 | ---
datasets:
- pubmed
- pmc/open_access
language:
- en
tags:
- text2text-generation
- mednli
widget:
- text: 'mednli: sentence1: In the ED, initial VS revealed T 98.9, HR 73, BP 121/90,
RR 15, O2 sat 98% on RA. sentence2: The patient is hemodynamically stable'
---
# SciFive Pubmed+PMC Large on MedNLI
## Introduc... | [
"MEDNLI"
] | BioNLP |
adipanda/makima-simpletuner-lora-2 | adipanda | text-to-image | [
"diffusers",
"flux",
"flux-diffusers",
"text-to-image",
"simpletuner",
"safe-for-work",
"lora",
"template:sd-lora",
"lycoris",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | 1,728,694,813,000 | 2024-10-13T19:26:05 | 16 | 0 | ---
base_model: black-forest-labs/FLUX.1-dev
license: other
tags:
- flux
- flux-diffusers
- text-to-image
- diffusers
- simpletuner
- safe-for-work
- lora
- template:sd-lora
- lycoris
inference: true
widget:
- text: unconditional (blank prompt)
parameters:
negative_prompt: blurry, cropped, ugly
output:
url:... | [
"BEAR"
] | Non_BioNLP |
sarahmiller137/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ft-ncbi-disease | sarahmiller137 | token-classification | [
"transformers",
"pytorch",
"safetensors",
"bert",
"token-classification",
"named-entity-recognition",
"en",
"dataset:ncbi_disease",
"license:cc",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,661,184,360,000 | 2023-03-23T15:57:02 | 24 | 0 | ---
datasets: ncbi_disease
language: en
license: cc
metrics:
- precision
- recall
- f1
- accuracy
tags:
- named-entity-recognition
- token-classification
task:
- named-entity-recognition
- token-classification
widget:
- text: ' The risk of cancer, especially lymphoid neoplasias, is substantially elevated
in A-T pat... | [
"NCBI DISEASE"
] | BioNLP |
tsavage68/MedQA_L3_1000steps_1e7rate_03beta_CSFTDPO | tsavage68 | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"dpo",
"generated_from_trainer",
"conversational",
"base_model:tsavage68/MedQA_L3_1000steps_1e6rate_SFT",
"base_model:finetune:tsavage68/MedQA_L3_1000steps_1e6rate_SFT",
"license:llama3",
"autotrain_compatible",
"text-generati... | 1,716,190,283,000 | 2024-05-23T22:54:22 | 5 | 0 | ---
base_model: tsavage68/MedQA_L3_1000steps_1e6rate_SFT
license: llama3
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: MedQA_L3_1000steps_1e7rate_03beta_CSFTDPO
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should p... | [
"MEDQA"
] | BioNLP |
mradermacher/Llama-3-VNTL-Vectors-i1-GGUF | mradermacher | null | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:Cas-Warehouse/Llama-3-VNTL-Vectors",
"base_model:quantized:Cas-Warehouse/Llama-3-VNTL-Vectors",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | 1,741,475,231,000 | 2025-03-09T01:00:08 | 589 | 0 | ---
base_model: Cas-Warehouse/Llama-3-VNTL-Vectors
language:
- en
library_name: transformers
tags:
- mergekit
- merge
quantized_by: mradermacher
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
weig... | [
"CAS"
] | Non_BioNLP |
ChameleonAI/ChameleonAILoras | ChameleonAI | null | [
"region:us"
] | 1,681,658,960,000 | 2023-12-19T20:49:50 | 0 | 11 | ---
{}
---
# Chameleon AI Loras
<!-- Provide a quick summary of what the model is/does. -->
You can find all my Loras uploaded to civitai here. Feels like the website is mostly down at the moment, so this is mostly a safety net.
## Model List
- [Judgement (Helltaker)](https://huggingface.co/ChameleonAI/ChameleonAI... | [
"CRAFT"
] | Non_BioNLP |
QuantFactory/Dans-PersonalityEngine-V1.1.0-12b-GGUF | QuantFactory | text-generation | [
"transformers",
"gguf",
"general-purpose",
"roleplay",
"storywriting",
"chemistry",
"biology",
"code",
"climate",
"axolotl",
"text-generation-inference",
"finetune",
"text-generation",
"en",
"dataset:PocketDoc/Dans-MemoryCore-CoreCurriculum-Small",
"dataset:AquaV/Energetic-Materials-Sh... | 1,735,364,211,000 | 2024-12-28T06:58:45 | 267 | 3 | ---
base_model:
- mistralai/Mistral-Nemo-Base-2407
datasets:
- PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
- AquaV/Energetic-Materials-Sharegpt
- AquaV/Chemical-Biological-Safety-Applications-Sharegpt
- AquaV/US-Army-Survival-Sharegpt
- AquaV/Resistance-Sharegpt
- AquaV/Interrogation-Sharegpt
- AquaV/Multi-Environme... | [
"CRAFT"
] | Non_BioNLP |
solidrust/Newton-7B-AWQ | solidrust | text-generation | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"axolotl",
"finetune",
"qlora",
"quantized",
"4-bit",
"AWQ",
"pytorch",
"instruct",
"conversational",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"en",
"dataset:hen... | 1,709,529,638,000 | 2024-09-03T08:07:48 | 8 | 0 | ---
base_model: Weyaxi/Newton-7B
datasets:
- hendrycks/competition_math
- allenai/ai2_arc
- camel-ai/physics
- camel-ai/chemistry
- camel-ai/biology
- camel-ai/math
- STEM-AI-mtl/Electrical-engineering
- openbookqa
- piqa
- metaeval/reclor
- mandyyyyii/scibench
- derek-thomas/ScienceQA
- sciq
- TIGER-Lab/ScienceEval
la... | [
"SCIQ"
] | Non_BioNLP |
arobier/BioGPT-Large-PubMedQA | arobier | null | [
"fr",
"base_model:microsoft/BioGPT-Large-PubMedQA",
"base_model:finetune:microsoft/BioGPT-Large-PubMedQA",
"license:mit",
"region:us"
] | 1,733,942,707,000 | 2024-12-12T15:24:49 | 0 | 0 | ---
base_model:
- microsoft/BioGPT-Large-PubMedQA
language:
- fr
license: mit
---
| [
"PUBMEDQA"
] | BioNLP |
BigSalmon/InformalToFormalLincoln81ParaphraseMedium | BigSalmon | text-generation | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,664,072,062,000 | 2022-09-25T02:27:53 | 43 | 0 | ---
{}
---
data: https://github.com/BigSalmon2/InformalToFormalDataset
```
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BigSalmon/InformalToFormalLincoln80Paraphrase")
model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln80Paraphras... | [
"BEAR"
] | Non_BioNLP |
GuiGel/xlm-roberta-large-flert-finetune-meddocan | GuiGel | token-classification | [
"flair",
"pytorch",
"token-classification",
"sequence-tagger-model",
"region:us"
] | 1,667,842,355,000 | 2022-11-07T17:36:11 | 6 | 0 | ---
tags:
- flair
- token-classification
- sequence-tagger-model
---
### Demo: How to use in Flair
Requires:
- **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`)
```python
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("GuiGel/xlm-ro... | [
"MEDDOCAN"
] | Non_BioNLP |
RichardErkhov/amd_-_AMD-Llama-135m-code-gguf | RichardErkhov | null | [
"gguf",
"arxiv:2204.06745",
"endpoints_compatible",
"region:us"
] | 1,730,998,563,000 | 2024-11-07T17:00:10 | 25 | 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)
AMD-Llama-135m-code - GGUF
- Model creator: https://huggingface.co/amd/
- Original model: https://huggingface.co/... | [
"SCIQ"
] | Non_BioNLP |
bartowski/UNA-ThePitbull-21.4B-v2-GGUF | bartowski | text-generation | [
"transformers",
"gguf",
"UNA",
"juanako",
"text-generation",
"dataset:jondurbin/py-dpo-v0.1",
"dataset:Replete-AI/code_bagel_hermes-2.5",
"dataset:mlabonne/orpo-dpo-mix-40k",
"license:afl-3.0",
"model-index",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | 1,716,919,252,000 | 2024-05-30T12:49:08 | 597 | 9 | ---
datasets:
- jondurbin/py-dpo-v0.1
- Replete-AI/code_bagel_hermes-2.5
- mlabonne/orpo-dpo-mix-40k
library_name: transformers
license: afl-3.0
pipeline_tag: text-generation
tags:
- UNA
- juanako
quantized_by: bartowski
model-index:
- name: UNA-ThePitbull-21.4B-v2
results:
- task:
type: text-generation
... | [
"PUBMEDQA"
] | Non_BioNLP |
helpmefindaname/flair-eml-biobert-bc5cdr-disease | helpmefindaname | null | [
"flair",
"pytorch",
"entity-mention-linker",
"region:us"
] | 1,703,385,517,000 | 2023-12-24T02:52:55 | 4 | 0 | ---
tags:
- flair
- entity-mention-linker
---
## biobert-bc5cdr-disease
Biomedical Entity Mention Linking for diseases
### Demo: How to use in Flair
Requires:
- **[Flair](https://github.com/flairNLP/flair/)>=0.14.0** (`pip install flair` or `pip install git+https://github.com/flairNLP/flair.git`)
```python
from f... | [
"BC5CDR"
] | BioNLP |
minchyeom/MemeGPT-GGUF | minchyeom | null | [
"transformers",
"gguf",
"meme",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | 1,721,027,024,000 | 2024-07-16T02:16:06 | 2 | 0 | ---
language:
- en
library_name: transformers
license: apache-2.0
tags:
- meme
---
This is NOT MemGPT, this is **Meme**GPT.
When using it, please put this as system prompt:
```
You are a witty AI assistant specializing in joke creation. Always respond with a joke, regardless of the input or topic. Craft jokes suitabl... | [
"CRAFT"
] | Non_BioNLP |
Seokeon/V14_R512_lora_none_bear_plushie | Seokeon | text-to-image | [
"diffusers",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"lora",
"base_model:CompVis/stable-diffusion-v1-4",
"base_model:adapter:CompVis/stable-diffusion-v1-4",
"license:creativeml-openrail-m",
"region:us"
] | 1,705,419,492,000 | 2024-01-16T15:42:24 | 13 | 0 | ---
base_model: CompVis/stable-diffusion-v1-4
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
instance_prompt: a photo of sks stuffed animal
inference: true
---
# LoRA DreamBooth - Seokeon/V14_R512_lora_none_bear_plushie
These are LoRA adapti... | [
"BEAR"
] | Non_BioNLP |
ntc-ai/SDXL-LoRA-slider.funko-pop-big-head-big-head-mode-gigantic-head-small-body | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,703,522,838,000 | 2023-12-25T16:47:22 | 7 | 2 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/evaluate/funko pop big head, big head mode, gigantic head, small
bo... | [
"CRAFT"
] | Non_BioNLP |
sophosympatheia/Nova-Tempus-70B-v0.1 | sophosympatheia | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"not-for-all-audiences",
"conversational",
"en",
"arxiv:2403.19522",
"base_model:EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1",
"base_model:merge:EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1",
"base_model:Sao10K/70B-L3.3-Cirrus-x1... | 1,736,659,366,000 | 2025-01-24T02:46:08 | 50 | 16 | ---
base_model:
- EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
- Sao10K/L3.3-70B-Euryale-v2.3
- Sao10K/70B-L3.3-Cirrus-x1
- TheDrummer/Anubis-70B-v1
- meta-llama/Llama-3.3-70B-Instruct
- meta-llama/Llama-3.1-70B
language:
- en
library_name: transformers
license: llama3.3
tags:
- mergekit
- merge
- not-for-all-audiences
---
<di... | [
"CRAFT"
] | Non_BioNLP |
mav23/Llama-3.2-3B-Instruct-Frog-GGUF | mav23 | text-generation | [
"gguf",
"RAG",
"Function_Calling",
"FC",
"Summarization",
"Rewriting",
"Functions",
"VLLM",
"LLM",
"text-generation",
"en",
"vi",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:quantized:meta-llama/Llama-3.2-3B-Instruct",
"license:llama3.2",
"endpoints_compatible",
"regio... | 1,731,735,220,000 | 2024-11-16T06:06:57 | 125 | 1 | ---
base_model:
- meta-llama/Llama-3.2-3B-Instruct
language:
- en
- vi
license: llama3.2
pipeline_tag: text-generation
tags:
- RAG
- Function_Calling
- FC
- Summarization
- Rewriting
- Functions
- VLLM
- LLM
---
<p align="center"> <img src="https://cdn-uploads.huggingface.co/production/uploads/6612cc790b91dd96968028f9... | [
"CHIA"
] | Non_BioNLP |
QuantFactory/Einstein-v7-Qwen2-7B-GGUF | QuantFactory | text-generation | [
"gguf",
"axolotl",
"instruct",
"finetune",
"chatml",
"gpt4",
"synthetic data",
"science",
"physics",
"chemistry",
"biology",
"math",
"qwen",
"qwen2",
"text-generation",
"en",
"dataset:allenai/ai2_arc",
"dataset:camel-ai/physics",
"dataset:camel-ai/chemistry",
"dataset:camel-ai/... | 1,719,470,302,000 | 2024-06-28T13:09:51 | 34 | 0 | ---
base_model: Weyaxi/Einstein-v7-Qwen2-7B
datasets:
- allenai/ai2_arc
- camel-ai/physics
- camel-ai/chemistry
- camel-ai/biology
- camel-ai/math
- metaeval/reclor
- openbookqa
- mandyyyyii/scibench
- derek-thomas/ScienceQA
- TIGER-Lab/ScienceEval
- jondurbin/airoboros-3.2
- LDJnr/Capybara
- Cot-Alpaca-GPT4-From-OpenH... | [
"SCIQ"
] | Non_BioNLP |
AIDA-UPM/MARTINI_enrich_BERTopic_ForoPXLVE | AIDA-UPM | text-classification | [
"bertopic",
"text-classification",
"region:us"
] | 1,736,509,133,000 | 2025-01-10T11:39:06 | 5 | 0 | ---
library_name: bertopic
pipeline_tag: text-classification
tags:
- bertopic
---
# MARTINI_enrich_BERTopic_ForoPXLVE
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... | [
"PCR"
] | Non_BioNLP |
medspaner/mbert-base-clinical-trials-misc-ents | medspaner | null | [
"pytorch",
"bert",
"generated_from_trainer",
"license:cc-by-nc-4.0",
"region:us"
] | 1,726,229,794,000 | 2024-10-01T06:36:01 | 7 | 0 | ---
license: cc-by-nc-4.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
widget:
- text: Paciente normotenso (PA = 120/70 mmHg)
model-index:
- name: mbert-base-clinical-trials-misc-ents
results: []
---
<!-- This model card has been generated automatically according to the information th... | [
"CT-EBM-SP",
"SCIELO"
] | BioNLP |
twadada/nmc-cls | twadada | null | [
"mteb",
"model-index",
"region:us"
] | 1,725,691,913,000 | 2024-09-07T06:52:24 | 0 | 0 | ---
tags:
- mteb
model-index:
- name: nomic_classification
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: None
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
... | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
Corianas/590m | Corianas | text-generation | [
"transformers",
"pytorch",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"en",
"dataset:tatsu-lab/alpaca",
"arxiv:1910.09700",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,680,100,722,000 | 2023-11-18T00:09:05 | 2,102 | 0 | ---
datasets:
- tatsu-lab/alpaca
language:
- en
license: cc-by-nc-4.0
---
# Model Card for Model ID
This is a finetuned model of Cerebras 590M model using DataBricksLabs Dolly Framework
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** Finetuned b... | [
"BLURB"
] | Non_BioNLP |
DeusImperator/Dark-Miqu-70B_exl2_2.4bpw | DeusImperator | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"arxiv:2403.19522",
"base_model:152334H/miqu-1-70b-sf",
"base_model:merge:152334H/miqu-1-70b-sf",
"base_model:Sao10K/Euryale-1.3-L2-70B",
"base_model:merge:Sao10K/Euryale-1.3-L2-70B",
"base_model:Sao10K/WinterGodde... | 1,716,560,673,000 | 2024-05-24T17:13:24 | 9 | 0 | ---
base_model:
- 152334H/miqu-1-70b-sf
- sophosympatheia/Midnight-Rose-70B-v2.0.3
- Sao10K/Euryale-1.3-L2-70B
- Sao10K/WinterGoddess-1.4x-70B-L2
library_name: transformers
license: other
tags:
- mergekit
- merge
---
# Dark-Miqu-70B - EXL2 2.4bpw
This is a 2.4bpw EXL2 quant of [jukofy... | [
"BEAR"
] | Non_BioNLP |
M41/LICENSE | M41 | null | [
"fr",
"en",
"doi:10.57967/hf/3165",
"license:other",
"region:us"
] | 1,727,727,500,000 | 2024-09-30T20:20:22 | 0 | 0 | ---
language:
- fr
- en
license: other
license_name: m41
license_link: https://m41.dev/mai/LICENSE
---
# Licence d'Utilisation M41
Copyright (c) 2024 M41. Tous droits réservés.
Cette licence régit l'utilisation du modèle M41. En utilisant, copiant ou distribuant ce modèle, vous acceptez de vous conformer aux termes ... | [
"CAS"
] | Non_BioNLP |
RichardErkhov/SeaLLMs_-_SeaLLM-7B-v2-gguf | RichardErkhov | null | [
"gguf",
"arxiv:2312.00738",
"arxiv:2205.11916",
"arxiv:2306.05179",
"arxiv:2306.05685",
"endpoints_compatible",
"region:us",
"conversational"
] | 1,715,399,743,000 | 2024-05-11T06:06:47 | 304 | 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)
SeaLLM-7B-v2 - GGUF
- Model creator: https://huggingface.co/SeaLLMs/
- Original model: https://huggingface.co/Sea... | [
"CHIA"
] | Non_BioNLP |
mgbam/OpenCLIP-BiomedCLIP-Finetuned | mgbam | null | [
"open_clip",
"medical",
"clip",
"fine-tuned",
"zero-shot",
"en",
"dataset:WinterSchool/MedificsDataset",
"base_model:microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224",
"base_model:finetune:microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224",
"license:mit",
"region:us"
] | 1,741,371,218,000 | 2025-03-07T20:07:49 | 50 | 1 | ---
base_model:
- microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224
datasets:
- WinterSchool/MedificsDataset
language:
- en
license: mit
metrics:
- accuracy
tags:
- medical
- clip
- fine-tuned
- zero-shot
---
This repository contains a fine-tuned version of BiomedCLIP (specifically the PubMedBERT_256-vit_base... | [
"MEDICAL DATA"
] | Non_BioNLP |
lightblue/Karasu-Mixtral-8x22B-v0.1 | lightblue | text-generation | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"conversational",
"dataset:openchat/openchat_sharegpt4_dataset",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,712,809,465,000 | 2024-04-11T15:44:16 | 29 | 62 | ---
datasets:
- openchat/openchat_sharegpt4_dataset
library_name: transformers
license: apache-2.0
---
# Model overview
<p align="center">
<img width=400 src="https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/HFnfguV4q5x7eIW09gcJD.png" alt="What happens when you type in 'Mixtral Instru... | [
"CRAFT"
] | Non_BioNLP |
srikanthmalla/BAAI-bge-reranker-large | srikanthmalla | text-classification | [
"transformers",
"pytorch",
"onnx",
"safetensors",
"xlm-roberta",
"text-classification",
"mteb",
"zh",
"en",
"arxiv:2401.03462",
"arxiv:2312.15503",
"arxiv:2311.13534",
"arxiv:2310.07554",
"arxiv:2309.07597",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatibl... | 1,712,783,377,000 | 2024-04-10T21:09:37 | 11 | 0 | ---
language:
- zh
- en
license: mit
tags:
- mteb
model-index:
- name: bge-reranker-large
results:
- task:
type: Reranking
dataset:
name: MTEB CMedQAv1
type: C-MTEB/CMedQAv1-reranking
config: default
split: test
revision: None
metrics:
- type: map
value: 82.1381... | [
"BEAR"
] | Non_BioNLP |
TheBloke/WizardLM-Uncensored-SuperCOT-StoryTelling-30B-AWQ | TheBloke | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"base_model:Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b",
"base_model:quantized:Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b",
"license:other",
"autotrain_compatible",
"text-generation-inference",
"4-bit",
"awq",
"regi... | 1,695,177,005,000 | 2023-11-09T18:18:26 | 24 | 6 | ---
base_model: Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b
license: other
model_name: WizardLM Uncensored SuperCOT Storytelling 30B
inference: false
model_creator: YellowRoseCx
model_type: llama
prompt_template: 'You are a helpful AI assistant.
USER: {prompt}
ASSISTANT:
'
quantized_by: TheBloke
---
... | [
"MONERO"
] | Non_BioNLP |
sam-babayev/sf_model_e5 | sam-babayev | feature-extraction | [
"transformers",
"safetensors",
"bert",
"feature-extraction",
"mteb",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | 1,699,571,539,000 | 2023-11-14T15:47:11 | 132 | 2 | ---
tags:
- mteb
model-index:
- name: sf_model_e5
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- ty... | [
"BIOSSES",
"SCIFACT"
] | TBD |
ntc-ai/SDXL-LoRA-slider.in-a-blizzard | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,703,836,426,000 | 2023-12-29T07:53:49 | 1 | 0 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/evaluate/in a blizzard.../in a blizzard_17_3.0.png
widget:
- text: in... | [
"CRAFT"
] | Non_BioNLP |
onekq-ai/OneSQL-v0.1-Qwen-7B | onekq-ai | null | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"unsloth",
"trl",
"sft",
"base_model:unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit",
"base_model:finetune:unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit",
"endpoints_compatible",
"region:us"
] | 1,740,799,018,000 | 2025-03-18T06:35:46 | 4 | 0 | ---
base_model: unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit
library_name: transformers
model_name: onekq-ai/OneSQL-v0.1-Qwen-7B
pipeline_tag: text-generation
tags:
- generated_from_trainer
- unsloth
- trl
- sft
licence: apache-2.0
---
# Introduction
This model specializes on the Text-to-SQL task. It is finetuned from ... | [
"CRAFT"
] | Non_BioNLP |
vocabtrimmer/mt5-small-trimmed-fr-60000-frquad-qa | vocabtrimmer | text2text-generation | [
"transformers",
"pytorch",
"mt5",
"text2text-generation",
"question answering",
"fr",
"dataset:lmqg/qg_frquad",
"arxiv:2210.03992",
"license:cc-by-4.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,679,244,912,000 | 2023-03-25T16:44:14 | 11 | 0 | ---
datasets:
- lmqg/qg_frquad
language: fr
license: cc-by-4.0
metrics:
- bleu4
- meteor
- rouge-l
- bertscore
- moverscore
pipeline_tag: text2text-generation
tags:
- question answering
widget:
- text: 'question: En quelle année a-t-on trouvé trace d''un haut fourneau similaire?,
context: Cette technologie ne dispa... | [
"CAS"
] | Non_BioNLP |
LLM360/AmberChat | LLM360 | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"nlp",
"llm",
"en",
"dataset:WizardLM/WizardLM_evol_instruct_V2_196k",
"dataset:icybee/share_gpt_90k_v1",
"arxiv:2312.06550",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"reg... | 1,701,303,143,000 | 2024-10-04T20:13:12 | 789 | 24 | ---
datasets:
- WizardLM/WizardLM_evol_instruct_V2_196k
- icybee/share_gpt_90k_v1
language:
- en
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- nlp
- llm
widget:
- example_title: example 1
text: How do I mount a tv to drywall safely?
output:
text: "Mounting a TV to drywall ... | [
"CRAFT"
] | Non_BioNLP |
AIDA-UPM/MARTINI_enrich_BERTopic_SicilianGorillian2 | AIDA-UPM | text-classification | [
"bertopic",
"text-classification",
"region:us"
] | 1,736,803,884,000 | 2025-01-13T21:31:36 | 5 | 0 | ---
library_name: bertopic
pipeline_tag: text-classification
tags:
- bertopic
---
# MARTINI_enrich_BERTopic_SicilianGorillian2
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 f... | [
"CPI"
] | Non_BioNLP |
ikim-uk-essen/GBERT-BioM-Translation-large | ikim-uk-essen | fill-mask | [
"transformers",
"pytorch",
"bert",
"fill-mask",
"arxiv:2404.05694",
"base_model:deepset/gbert-base",
"base_model:finetune:deepset/gbert-base",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,712,734,104,000 | 2024-04-10T08:02:30 | 27 | 0 | ---
base_model: deepset/gbert-base
license: mit
---
# GBERT-BioM-Translation-large
This model is a medically continuously pre-trained version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large).
## Training data
The model was trained on German PubMed abstracts, translated English PubMed abstracts, ... | [
"BRONCO150",
"GRASCCO"
] | BioNLP |
ntc-ai/SDXL-LoRA-slider.emoji | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,704,550,096,000 | 2024-01-06T14:08:19 | 8 | 1 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/evaluate/emoji.../emoji_17_3.0.png
widget:
- text: emoji
output:
... | [
"CRAFT"
] | Non_BioNLP |
medspaner/mdeberta-v3-base-es-trials-medic-attr | medspaner | token-classification | [
"transformers",
"pytorch",
"deberta-v2",
"token-classification",
"generated_from_trainer",
"arxiv:2111.09543",
"license:cc-by-nc-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,705,147,284,000 | 2024-10-01T06:30:03 | 12 | 0 | ---
license: cc-by-nc-4.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
widget:
- text: Azitromicina en suspensión oral, 10 mg/kg una vez al día durante siete días
- text: A un grupo se le administró Ciprofloxacino 200 mg bid EV y al otro Cefazolina
1 g tid IV
- text: Administración d... | [
"SCIELO"
] | BioNLP |
yoeven/multilingual-e5-large-instruct-Q5_0-GGUF | yoeven | null | [
"sentence-transformers",
"gguf",
"mteb",
"transformers",
"llama-cpp",
"gguf-my-repo",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"eo",
"es",
"et",
"eu",
"fa",
"fi",
"fr",
"fy",
... | 1,736,171,445,000 | 2025-01-06T13:50:51 | 42 | 2 | ---
base_model: intfloat/multilingual-e5-large-instruct
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la... | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
tensorblock/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b-GGUF | tensorblock | null | [
"gguf",
"uncensored",
"TensorBlock",
"GGUF",
"dataset:ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered",
"dataset:kaiokendev/SuperCOT-dataset",
"dataset:neulab/conala",
"dataset:yahma/alpaca-cleaned",
"dataset:QingyiSi/Alpaca-CoT",
"dataset:timdettmers/guanaco-33b",
"dataset:JosephusCheung... | 1,732,214,311,000 | 2024-11-21T22:23:01 | 306 | 3 | ---
base_model: Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b
datasets:
- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
- kaiokendev/SuperCOT-dataset
- neulab/conala
- yahma/alpaca-cleaned
- QingyiSi/Alpaca-CoT
- timdettmers/guanaco-33b
- JosephusCheung/GuanacoDataset
license: other
tags:
- uncensored
- ... | [
"MONERO"
] | Non_BioNLP |
anfemora/bsc-bio-ehr-es-cantemist | anfemora | null | [
"tensorboard",
"safetensors",
"roberta",
"generated_from_trainer",
"region:us"
] | 1,723,576,531,000 | 2024-08-15T15:20:25 | 4 | 0 | ---
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bsc-bio-ehr-es-cantemist
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 ... | [
"CANTEMIST"
] | BioNLP |
reginaboateng/final_pfeiffer_pubmedqa_adapter | reginaboateng | null | [
"adapter-transformers",
"bert",
"adapterhub:pubmedqa",
"dataset:pubmedqa",
"region:us"
] | 1,695,934,312,000 | 2023-09-28T20:51:54 | 0 | 0 | ---
datasets:
- pubmedqa
tags:
- bert
- adapterhub:pubmedqa
- adapter-transformers
---
# Adapter `reginaboateng/final_pfeiffer_pubmedqa_adapter` for allenai/scibert_scivocab_uncased
An [adapter](https://adapterhub.ml) for the `allenai/scibert_scivocab_uncased` model that was trained on the [pubmedqa](https://adapterh... | [
"PUBMEDQA"
] | BioNLP |
wenge-research/yayi-7b | wenge-research | text-generation | [
"transformers",
"pytorch",
"bloom",
"text-generation",
"yayi",
"zh",
"en",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,685,672,638,000 | 2023-09-08T09:43:19 | 2,029 | 29 | ---
language:
- zh
- en
pipeline_tag: text-generation
tags:
- yayi
---
# 雅意大模型
## 介绍
雅意大模型在百万级人工构造的高质量领域数据上进行指令微调得到，训练数据覆盖媒体宣传、舆情分析、公共安全、金融风控、城市治理等五大领域，上百种自然语言指令任务。雅意大模型从预训练初始化权重到领域模型的迭代过程中，我们逐步增强了它的中文基础能力和领域分析能力，并增加了部分插件能力。同时，经过数百名用户内测过程中持续不断的人工反馈优化，我们进一步提升了模型性能和安全性。
通过雅意大模型的开源为促进中文预训练大模型开源社区的发展，贡献自己的一份力量，通过开源，与每一位合... | [
"BEAR"
] | Non_BioNLP |
lightblue/lb-reranker-0.5B-v1.0 | lightblue | text-generation | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"reranker",
"conversational",
"en",
"zh",
"es",
"de",
"ar",
"ru",
"ja",
"ko",
"hi",
"sk",
"vi",
"tr",
"fi",
"id",
"fa",
"no",
"th",
"sv",
"pt",
"da",
"bn",
"te",
"ro",
"it",
"fr",
"nl",
"sw",
... | 1,736,129,971,000 | 2025-01-21T03:04:26 | 1,576 | 63 | ---
base_model:
- Qwen/Qwen2.5-0.5B-Instruct
datasets:
- lightblue/reranker_continuous_filt_max7_train
language:
- en
- zh
- es
- de
- ar
- ru
- ja
- ko
- hi
- sk
- vi
- tr
- fi
- id
- fa
- 'no'
- th
- sv
- pt
- da
- bn
- te
- ro
- it
- fr
- nl
- sw
- pl
- hu
- cs
- el
- uk
- mr
- ta
- tl
- bg
- lt
- ur
- he
- gu
- kn
... | [
"SCIFACT"
] | Non_BioNLP |
ntc-ai/SDXL-LoRA-slider.fit | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,702,352,948,000 | 2024-02-06T00:31:02 | 14 | 1 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/fit_17_3.0.png
widget:
- text: fit
output:
url: images/fit_17_3... | [
"CRAFT"
] | Non_BioNLP |
Netta1994/setfit_baai_rag_ds_gpt-4o_cot-few_shot-instructions_remove_final_evaluation_e1_larger | 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"
] | 1,727,016,049,000 | 2024-09-22T14:41:06 | 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: 'The answer provided concisely lists the changes being made to the storage
AM as per Haribabu ... | [
"MEDAL"
] | Non_BioNLP |
ntc-ai/SDXL-LoRA-slider.eye-catching | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,702,560,471,000 | 2024-02-06T00:32:44 | 2,895 | 3 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/eye-catching_17_3.0.png
widget:
- text: eye-catching
output:
ur... | [
"CRAFT"
] | Non_BioNLP |
AdwayK/biobert_ncbi_disease_ner_tuned_on_TAC2017 | AdwayK | token-classification | [
"transformers",
"tf",
"bert",
"token-classification",
"generated_from_keras_callback",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,650,130,416,000 | 2022-04-16T20:24:50 | 16 | 0 | ---
tags:
- generated_from_keras_callback
model-index:
- name: AdwayK/biobert_ncbi_disease_ner_tuned_on_TAC2017
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Adway... | [
"NCBI DISEASE"
] | BioNLP |
BSC-NLP4BIA/bsc-bio-ehr-es-carmen-distemist | BSC-NLP4BIA | token-classification | [
"transformers",
"pytorch",
"roberta",
"token-classification",
"es",
"base_model:PlanTL-GOB-ES/bsc-bio-ehr-es",
"base_model:finetune:PlanTL-GOB-ES/bsc-bio-ehr-es",
"license:cc-by-4.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,717,601,778,000 | 2024-07-25T14:19:47 | 28 | 0 | ---
base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
language:
- es
license: cc-by-4.0
---
# Training data
Model trained on the disease mentions of [CARMEN-I](https://zenodo.org/records/10171540) and [DisTEMIST](https://doi.org/10.5281/zenodo.7614764).
# Citation
Please cite the following works:
```
@inproceedings{distemis... | [
"DISTEMIST"
] | BioNLP |
cgus/Apollo2-7B-iMat-GGUF | cgus | question-answering | [
"gguf",
"biology",
"medical",
"question-answering",
"ar",
"en",
"zh",
"ko",
"ja",
"mn",
"th",
"vi",
"lo",
"mg",
"de",
"pt",
"es",
"fr",
"ru",
"it",
"hr",
"gl",
"cs",
"co",
"la",
"uk",
"bs",
"bg",
"eo",
"sq",
"da",
"sa",
"gn",
"sr",
"sk",
"gd",
... | 1,729,245,436,000 | 2025-02-03T06:07:28 | 221 | 1 | ---
base_model:
- FreedomIntelligence/Apollo2-7B
datasets:
- FreedomIntelligence/ApolloMoEDataset
language:
- ar
- en
- zh
- ko
- ja
- mn
- th
- vi
- lo
- mg
- de
- pt
- es
- fr
- ru
- it
- hr
- gl
- cs
- co
- la
- uk
- bs
- bg
- eo
- sq
- da
- sa
- gn
- sr
- sk
- gd
- lb
- hi
- ku
- mt
- he
- ln
- bm
- sw
- ig
- rw
- ... | [
"HEAD-QA",
"MEDQA",
"PUBMEDQA"
] | BioNLP |
vyshnavids03/my-pet-dog | vyshnavids03 | text-to-image | [
"NxtWave-GenAI-Webinar",
"text-to-image",
"stable-diffusion",
"license:creativeml-openrail-m",
"region:us"
] | 1,709,121,901,000 | 2024-02-28T12:06:37 | 0 | 0 | ---
license: creativeml-openrail-m
tags:
- NxtWave-GenAI-Webinar
- text-to-image
- stable-diffusion
---
### My-Pet-Dog Dreambooth model trained by vyshnavids03 following the "Build your own Gen AI model" session by NxtWave.
Project Submission Code: 4MK21CS059
Sample pictures of this concept:
![0](https://huggingfa... | [
"BEAR"
] | Non_BioNLP |
llange/xlm-roberta-large-spanish-clinical | llange | fill-mask | [
"transformers",
"pytorch",
"xlm-roberta",
"fill-mask",
"arxiv:2112.08754",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,646,263,745,000 | 2021-12-17T10:27:39 | 60 | 1 | ---
{}
---
# CLIN-X-ES: a pre-trained language model for the Spanish clinical domain
Details on the model, the pre-training corpus and the downstream task performance are given in the paper: "CLIN-X: pre-trained language models and a study on cross-task transfer for concept extraction in the clinical domain" by Lukas L... | [
"CANTEMIST",
"MEDDOCAN",
"PHARMACONER",
"SCIELO"
] | BioNLP |
google/Gemma-Embeddings-v1.0 | google | null | [
"pytorch",
"mteb",
"en",
"base_model:google/gemma-2-9b-it",
"base_model:finetune:google/gemma-2-9b-it",
"license:gemma",
"model-index",
"region:us"
] | 1,734,282,838,000 | 2024-12-16T21:46:31 | 132 | 123 | ---
base_model:
- google/gemma-2-9b-it
language:
- en
license: gemma
tags:
- mteb
model-index:
- name: google/Gemma-Embeddings-v1.0
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: t... | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
FremyCompany/BioLORD-2023-C | FremyCompany | sentence-similarity | [
"sentence-transformers",
"pytorch",
"safetensors",
"mpnet",
"feature-extraction",
"sentence-similarity",
"medical",
"biology",
"en",
"dataset:FremyCompany/BioLORD-Dataset",
"dataset:FremyCompany/AGCT-Dataset",
"arxiv:2311.16075",
"license:other",
"autotrain_compatible",
"endpoints_compat... | 1,707,764,049,000 | 2025-01-09T19:25:52 | 96,636 | 3 | ---
datasets:
- FremyCompany/BioLORD-Dataset
- FremyCompany/AGCT-Dataset
language: en
license: other
license_name: ihtsdo-and-nlm-licences
license_link: https://www.nlm.nih.gov/databases/umls.html
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- medical
- biol... | [
"EHR-REL"
] | BioNLP |
bobox/DeBERTa-small-ST-v1-test-step3 | bobox | sentence-similarity | [
"sentence-transformers",
"pytorch",
"deberta-v2",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:279409",
"loss:CachedGISTEmbedLoss",
"en",
"dataset:tals/vitaminc",
"dataset:allenai/scitail",
"dataset:allenai/sciq",
"dataset:allenai/qasc",
"dataset:sen... | 1,724,302,361,000 | 2024-08-22T04:52:59 | 6 | 0 | ---
base_model: bobox/DeBERTa-small-ST-v1-test-step2
datasets:
- tals/vitaminc
- allenai/scitail
- allenai/sciq
- allenai/qasc
- sentence-transformers/msmarco-msmarco-distilbert-base-v3
- sentence-transformers/natural-questions
- sentence-transformers/trivia-qa
- sentence-transformers/gooaq
- google-research-datasets/p... | [
"CAS",
"SCIQ",
"SCITAIL"
] | Non_BioNLP |
nttx/14ced443-d745-4ed9-8213-2d40d4bd246d | nttx | null | [
"peft",
"safetensors",
"llama",
"axolotl",
"generated_from_trainer",
"base_model:rayonlabs/merged-merged-af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-138437bf-44bd-4b03-8801-d05451a9ff28",
"base_model:adapter:rayonlabs/merged-merged-af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-138437bf-44bd-4b03-8801-... | 1,736,561,555,000 | 2025-01-11T03:33:00 | 1 | 0 | ---
base_model: rayonlabs/merged-merged-af6dd40b-32e1-43b1-adfd-8ce14d65d738-PubMedQA-138437bf-44bd-4b03-8801-d05451a9ff28
library_name: peft
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 14ced443-d745-4ed9-8213-2d40d4bd246d
results: []
---
<!-- This model card has been generated automatically accord... | [
"PUBMEDQA"
] | BioNLP |
priteshraj/quro1 | priteshraj | visual-question-answering | [
"medical",
"visual-question-answering",
"en",
"hi",
"dataset:unsloth/Radiology_mini",
"base_model:meta-llama/Llama-3.2-11B-Vision-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-11B-Vision-Instruct",
"license:mit",
"region:us"
] | 1,735,545,261,000 | 2025-01-23T07:14:29 | 0 | 0 | ---
base_model:
- meta-llama/Llama-3.2-11B-Vision-Instruct
datasets:
- unsloth/Radiology_mini
language:
- en
- hi
license: mit
metrics:
- accuracy
pipeline_tag: visual-question-answering
tags:
- medical
---
# quro1: Small Medical AI Model
## Overview
quro1 is a compact, open-source medical AI model designed to empow... | [
"MEDICAL DATA"
] | Non_BioNLP |
judithrosell/BlueBERT_CRAFT_NER_new | judithrosell | token-classification | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"base_model:bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12",
"base_model:finetune:bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12",
"license:cc0-1.0",
"autotrain_compatible",
"endpo... | 1,703,672,548,000 | 2023-12-27T10:38:24 | 103 | 0 | ---
base_model: bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12
license: cc0-1.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: BlueBERT_CRAFT_NER_new
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer... | [
"CRAFT"
] | BioNLP |
ostapeno/rsgd_full_1B_coarsegrained_poly_router_dir_lora_sim_distinct10 | ostapeno | null | [
"region:us"
] | 1,703,470,950,000 | 2023-12-26T07:15:06 | 0 | 0 | ---
{}
---
Number of experts present in the library: 39
| Expert Name | Base Model | Trained on | Adapter Type |
| --- | --- | --- | --- |
| social_i_qa_Generate_the_question_from_the_answer | EleutherAI/gpt-neo-1.3B | sordonia/adauni-v3-10k-flat/social_i_qa_Generate_the_question_from_the_answer | lora |
| ropes_backg... | [
"SCIQ"
] | Non_BioNLP |
NesrineBannour/CAS-privacy-preserving-model | NesrineBannour | token-classification | [
"transformers",
"biomedical",
"clinical",
"pytorch",
"camembert",
"token-classification",
"fr",
"dataset:bigbio/cas",
"license:cc-by-sa-4.0",
"region:us"
] | 1,696,937,678,000 | 2023-11-10T14:29:32 | 0 | 0 | ---
datasets:
- bigbio/cas
language:
- fr
library_name: transformers
license: cc-by-sa-4.0
metrics:
- f1
- precision
- recall
pipeline_tag: token-classification
tags:
- biomedical
- clinical
- pytorch
- camembert
inference: false
---
# Privacy-preserving mimic models for clinical named entity recognition in French
<!-... | [
"CAS"
] | BioNLP |
LoneStriker/Medorca-2x7b-5.0bpw-h6-exl2 | LoneStriker | text-generation | [
"transformers",
"safetensors",
"mixtral",
"text-generation",
"moe",
"merge",
"epfl-llm/meditron-7b",
"microsoft/Orca-2-7b",
"license:apache-2.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,705,942,448,000 | 2024-01-22T16:59:52 | 3 | 0 | ---
license: apache-2.0
tags:
- moe
- merge
- epfl-llm/meditron-7b
- microsoft/Orca-2-7b
---
# Medorca-2x7b
Medorca-2x7b is a Mixure of Experts (MoE) made with the following models:
* [epfl-llm/medi... | [
"MEDQA",
"PUBMEDQA"
] | BioNLP |
Daruni/DoraemonRVC2 | Daruni | null | [
"license:cc-by-nc-4.0",
"region:us"
] | 1,693,659,570,000 | 2023-10-09T07:59:22 | 0 | 0 | ---
license: cc-by-nc-4.0
---
[UPDATED] Doraemon (RVC v2, rmvpe, 425 epochs, 24000 steps).
-
Trained till overtraining was detected with approximately 25 minutes of Japanese decent-quality dataset from Youtube.
Haven't tried other methods but rmvpe and mangio seems good.
Bear in mind that when the vocal/acapella's pi... | [
"BEAR"
] | Non_BioNLP |
LoneStriker/BioMistral-7B-DARE-GPTQ | LoneStriker | text-generation | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"dare",
"medical",
"biology",
"conversational",
"en",
"fr",
"nl",
"es",
"it",
"pl",
"ro",
"de",
"dataset:pubmed",
"arxiv:2311.03099",
"arxiv:2306.01708",
"arxiv:2402.10373",
"base_model:BioM... | 1,708,358,745,000 | 2024-02-19T16:09:24 | 16 | 0 | ---
base_model:
- BioMistral/BioMistral-7B
- mistralai/Mistral-7B-Instruct-v0.1
datasets:
- pubmed
language:
- en
- fr
- nl
- es
- it
- pl
- ro
- de
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- mergekit
- merge
- dare
- medical
- biology
---
# BioMistral-7B-mistral7instruct-dare
... | [
"MEDQA",
"PUBMEDQA"
] | BioNLP |
medspaner/EriBERTa-clinical-trials-medic-attr | medspaner | null | [
"pytorch",
"roberta",
"generated_from_trainer",
"arxiv:2306.07373",
"license:cc-by-nc-4.0",
"region:us"
] | 1,726,228,477,000 | 2024-10-01T06:39:52 | 17 | 0 | ---
license: cc-by-nc-4.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
widget:
- text: Azitromicina en suspensión oral, 10 mg/kg una vez al día durante siete días
- text: A un grupo se le administró Ciprofloxacino 200 mg bid EV y al otro Cefazolina
1 g tid IV
- text: Administración d... | [
"SCIELO"
] | BioNLP |
mav23/AMD-OLMo-1B-SFT-DPO-GGUF | mav23 | text-generation | [
"gguf",
"text-generation",
"dataset:allenai/dolma",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | 1,730,945,587,000 | 2024-11-07T02:24:03 | 132 | 0 | ---
datasets:
- allenai/dolma
license: apache-2.0
pipeline_tag: text-generation
---
# AMD-OLMo
AMD-OLMo are a series of 1B language models trained from scratch by AMD on AMD Instinct™ MI250 GPUs. The training code used is based on [OLMo](https://github.com/allenai/OLMo).
We release the pre-trained model, supervised fi... | [
"SCIQ"
] | Non_BioNLP |
jkang/espnet2_librispeech_100_conformer_word | jkang | automatic-speech-recognition | [
"espnet",
"audio",
"automatic-speech-recognition",
"dataset:librispeech_100",
"arxiv:1804.00015",
"license:cc-by-4.0",
"region:us"
] | 1,646,263,745,000 | 2022-02-23T00:23:45 | 5 | 1 | ---
datasets:
- librispeech_100
language: noinfo
license: cc-by-4.0
tags:
- espnet
- audio
- automatic-speech-recognition
---
## ESPnet2 ASR model
### `jkang/espnet2_librispeech_100_conformer_word`
This model was trained by jaekookang using librispeech_100 recipe in [espnet](https://github.com/espnet/espnet/).
###... | [
"BEAR",
"CRAFT",
"LINNAEUS",
"MEDAL"
] | Non_BioNLP |
SeaLLMs/SeaLLM-7B-v2.5-GGUF | SeaLLMs | null | [
"gguf",
"multilingual",
"sea",
"en",
"zh",
"vi",
"id",
"th",
"ms",
"km",
"lo",
"my",
"tl",
"arxiv:2312.00738",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | 1,712,126,377,000 | 2024-04-25T08:55:56 | 55 | 8 | ---
language:
- en
- zh
- vi
- id
- th
- ms
- km
- lo
- my
- tl
license: other
license_name: seallms
license_link: https://huggingface.co/SeaLLMs/SeaLLM-13B-Chat/blob/main/LICENSE
tags:
- multilingual
- sea
---
# *SeaLLM-7B-v2.5* - Large Language Models for Southeast Asia
<span style="color: #ff3860"><b>LM-studio/lla... | [
"CHIA"
] | Non_BioNLP |
stanford-crfm/BioMedLM | stanford-crfm | text-generation | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"dataset:pubmed",
"arxiv:2403.18421",
"license:bigscience-bloom-rail-1.0",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,671,005,699,000 | 2024-03-28T13:57:14 | 13,701 | 417 | ---
datasets:
- pubmed
license: bigscience-bloom-rail-1.0
widget:
- text: Photosynthesis is
---
# Model Card for BioMedLM 2.7B
Note: This model was previously known as PubMedGPT 2.7B, but we have changed it due to a request from the NIH which holds the trademark for "PubMed".
Paper: [BioMedLM: A 2.7B Parameter Langu... | [
"MEDQA"
] | BioNLP |
mradermacher/EXF-Medistral-Nemo-12B-GGUF | mradermacher | null | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"mistral",
"trl",
"en",
"dataset:exafluence/Open-MedQA-Nexus",
"base_model:exafluence/EXF-Medistral-Nemo-12B",
"base_model:quantized:exafluence/EXF-Medistral-Nemo-12B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
... | 1,729,337,580,000 | 2024-10-19T14:23:09 | 42 | 1 | ---
base_model: exafluence/EXF-Medistral-Nemo-12B
datasets:
- exafluence/Open-MedQA-Nexus
language:
- en
library_name: transformers
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
quantized_by: mradermacher
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_ten... | [
"MEDQA"
] | Non_BioNLP |
Omartificial-Intelligence-Space/Arabic-all-nli-triplet-Matryoshka | Omartificial-Intelligence-Space | sentence-similarity | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:557850",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"mteb",
"ar",
"dataset:Omartificial-Intelligence-Space/Arabic-NLi-Triplet",
"arxiv:... | 1,718,387,645,000 | 2025-01-23T10:30:49 | 217 | 2 | ---
base_model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
datasets:
- Omartificial-Intelligence-Space/Arabic-NLi-Triplet
language:
- ar
library_name: sentence-transformers
license: apache-2.0
metrics:
- pearson_cosine
- spearman_cosine
- pearson_manhattan
- spearman_manhattan
- pearson_euclidean
- spe... | [
"BIOSSES"
] | Non_BioNLP |
vectoriseai/gte-small | vectoriseai | sentence-similarity | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"bert",
"mteb",
"sentence-similarity",
"Sentence Transformers",
"en",
"arxiv:2308.03281",
"license:mit",
"model-index",
"autotrain_compatible",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | 1,697,007,980,000 | 2023-10-11T07:08:28 | 5 | 0 | ---
language:
- en
license: mit
tags:
- mteb
- sentence-similarity
- sentence-transformers
- Sentence Transformers
model-index:
- name: gte-small
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
... | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
ntc-ai/SDXL-LoRA-slider.art-by-artgerm-and-greg-rutkowski-and-alphonse-mucha | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,703,230,866,000 | 2023-12-22T07:41:09 | 22 | 0 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/evaluate/art by artgerm and greg rutkowski and alphonse mucha.../art
... | [
"CRAFT"
] | Non_BioNLP |
ntc-ai/SDXL-LoRA-slider.pixel-art | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,702,506,410,000 | 2024-02-06T00:32:26 | 23 | 4 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/pixel art_17_3.0.png
widget:
- text: pixel art
output:
url: ima... | [
"CRAFT"
] | Non_BioNLP |
sophosympatheia/Nova-Tempus-70B-v0.3 | sophosympatheia | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"not-for-all-audiences",
"conversational",
"en",
"arxiv:2408.07990",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"base_model:merge:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"base_model:sophosympathe... | 1,738,304,436,000 | 2025-02-01T16:59:56 | 246 | 6 | ---
base_model:
- deepseek-ai/DeepSeek-R1-Distill-Llama-70B
- sophosympatheia/Nova-Tempus-70B-v0.1
language:
- en
library_name: transformers
license: llama3.3
tags:
- mergekit
- merge
- not-for-all-audiences
---
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/4fCqX0w.png"... | [
"CRAFT"
] | Non_BioNLP |
kalbin/coraal_wavlm_conformer | kalbin | automatic-speech-recognition | [
"espnet",
"audio",
"automatic-speech-recognition",
"en",
"dataset:coraal",
"arxiv:1804.00015",
"license:cc-by-4.0",
"region:us"
] | 1,724,987,341,000 | 2024-08-30T03:20:36 | 4 | 0 | ---
datasets:
- coraal
language: en
license: cc-by-4.0
tags:
- espnet
- audio
- automatic-speech-recognition
---
## ESPnet2 ASR model
### `kalbin/coraal_wavlm_conformer`
This model was trained by Kalvin Chang using coraal recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
Follow... | [
"BEAR"
] | Non_BioNLP |
fine-tuned/SciFact-512-192-gpt-4o-2024-05-13-92012085 | fine-tuned | feature-extraction | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"feature-extraction",
"sentence-similarity",
"mteb",
"en",
"dataset:fine-tuned/SciFact-512-192-gpt-4o-2024-05-13-92012085",
"dataset:allenai/c4",
"license:apache-2.0",
"autotrain_compatible",
"text-embeddings-inference",
"endpoints_compa... | 1,716,945,347,000 | 2024-05-29T01:16:42 | 6 | 0 | ---
datasets:
- fine-tuned/SciFact-512-192-gpt-4o-2024-05-13-92012085
- allenai/c4
language:
- en
- en
license: apache-2.0
pipeline_tag: feature-extraction
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
---
This model is a fine-tuned version of [**BAAI/bge-m3**](https://huggingface.co/B... | [
"SCIFACT"
] | Non_BioNLP |
NgaNTQ/VinaLLaMA_LAWQA | NgaNTQ | text-generation | [
"transformers",
"safetensors",
"llama",
"text-generation",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,719,760,838,000 | 2024-07-02T16:16:55 | 4 | 0 | ---
{}
---
Load Model
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_use_double_quant=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16
)
tokenizer = AutoTokenize... | [
"CHIA"
] | Non_BioNLP |
hchung1017/aihub_012_streaming_conformer | hchung1017 | automatic-speech-recognition | [
"espnet",
"audio",
"automatic-speech-recognition",
"ko",
"dataset:aihub_012",
"arxiv:1804.00015",
"license:cc-by-4.0",
"region:us"
] | 1,688,624,527,000 | 2023-07-06T06:22:30 | 1 | 0 | ---
datasets:
- aihub_012
language: ko
license: cc-by-4.0
tags:
- espnet
- audio
- automatic-speech-recognition
---
## ESPnet2 ASR model
### `hchung1017/aihub_012_streaming_conformer`
This model was trained by hchung1017 using aihub_012 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ... | [
"BEAR",
"CRAFT",
"MEDAL"
] | Non_BioNLP |
ricepaper/vi-gemma-2b-RAG | ricepaper | text-generation | [
"transformers",
"pytorch",
"safetensors",
"gemma",
"text-generation",
"text-generation-inference",
"retrieval-augmented-generation",
"unsloth",
"trl",
"sft",
"conversational",
"en",
"vi",
"base_model:unsloth/gemma-1.1-2b-it-bnb-4bit",
"base_model:finetune:unsloth/gemma-1.1-2b-it-bnb-4bit... | 1,721,148,663,000 | 2024-08-05T17:32:25 | 440 | 13 | ---
base_model: unsloth/gemma-1.1-2b-it-bnb-4bit
language:
- en
- vi
license: apache-2.0
tags:
- text-generation-inference
- retrieval-augmented-generation
- transformers
- unsloth
- gemma
- trl
- sft
---
## Model Card: vi-gemma-2b-RAG
### (English below)
### Tiếng Việt (Vietnamese)
**Mô tả mô hình:**
vi-gemma-2b-R... | [
"CHIA"
] | Non_BioNLP |
theeraphola/db-bear_plushie-class2 | theeraphola | text-to-image | [
"diffusers",
"tensorboard",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"dreambooth",
"base_model:CompVis/stable-diffusion-v1-4",
"base_model:finetune:CompVis/stable-diffusion-v1-4",
"license:creativeml-openrail-m",
"autotrain_compatible",
"endpoints_compa... | 1,700,236,459,000 | 2023-11-17T16:18:16 | 0 | 0 | ---
base_model: CompVis/stable-diffusion-v1-4
license: creativeml-openrail-m
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- dreambooth
instance_prompt: a photo of bear_plushie stuffed animal
inference: true
---
# DreamBooth - theeraphola/db-bear_plushie-class2
This is a dreamb... | [
"BEAR"
] | Non_BioNLP |
SEBIS/legal_t5_small_summ_fr | SEBIS | text2text-generation | [
"transformers",
"pytorch",
"jax",
"t5",
"text2text-generation",
"summarization French model",
"dataset:jrc-acquis",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | 1,646,263,744,000 | 2021-06-23T11:23:07 | 186 | 1 | ---
datasets:
- jrc-acquis
language: French
tags:
- summarization French model
widget:
- text: 'LA COMMISSION DES COMMUNAUTÉS EUROPÉENNES, vu le traité instituant la Communauté
européenne, vu le règlement (CE) no 1784/2003 du Conseil du 29 septembre 2003
portant organisation commune des marchés dans le secteur ... | [
"CAS"
] | Non_BioNLP |
Shengyu/Evaluation_of_NER_models | Shengyu | null | [
"region:us"
] | 1,661,741,924,000 | 2022-08-29T03:03:59 | 0 | 1 | ---
{}
---
# **Evaluation of the NER models in medical dataset**
The goal of the whole project is to compare the NER models and feature evaluation in the medical dataset, and the program of model comparison needs to be executed in the GPU environment. Here are the instructions ... | [
"JNLPBA"
] | BioNLP |
antoste/gpt2-xl-conversational-Q4_K_M-GGUF | antoste | text-generation | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"dataset:Locutusque/InstructMix",
"base_model:Locutusque/gpt2-xl-conversational",
"base_model:quantized:Locutusque/gpt2-xl-conversational",
"license:mit",
"endpoints_compatible",
"region:us"
] | 1,727,811,148,000 | 2024-10-01T19:32:35 | 8 | 0 | ---
base_model: Locutusque/gpt2-xl-conversational
datasets:
- Locutusque/InstructMix
language:
- en
license: mit
metrics:
- bleu
- perplexity
- loss
- accuracy
pipeline_tag: text-generation
tags:
- llama-cpp
- gguf-my-repo
widget:
- text: '<|USER|> Design a Neo4j database and Cypher function snippet to Display Extreme
... | [
"CRAFT"
] | Non_BioNLP |
RichardErkhov/lgbird_-_stella_1.5B_custom-4bits | RichardErkhov | null | [
"safetensors",
"qwen2",
"custom_code",
"arxiv:2205.13147",
"4-bit",
"bitsandbytes",
"region:us"
] | 1,741,514,999,000 | 2025-03-09T10:11:03 | 9 | 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)
stella_1.5B_custom - bnb 4bits
- Model creator: https://huggingface.co/lgbird/
- Original model: https://huggingf... | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
simonosgoode/nomic_embed_fine_tune_law_v3 | simonosgoode | sentence-similarity | [
"sentence-transformers",
"safetensors",
"nomic_bert",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:12750",
"loss:MultipleNegativesRankingLoss",
"custom_code",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:nomic-ai/nomic-embed-text-v1.5",
"base_mo... | 1,731,627,075,000 | 2024-11-14T23:31:46 | 9 | 0 | ---
base_model: nomic-ai/nomic-embed-text-v1.5
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:12750
- loss:MultipleNegativesRankingLoss
widget:
- source_sentence: 'cluster: SUMMARY: E... | [
"BEAR",
"CAS",
"MQP"
] | Non_BioNLP |
agentlans/deberta-v3-xsmall-readability | agentlans | text-classification | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"en",
"dataset:agentlans/readability",
"base_model:microsoft/deberta-v3-xsmall",
"base_model:finetune:microsoft/deberta-v3-xsmall",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"re... | 1,727,419,224,000 | 2024-09-27T06:46:41 | 16 | 0 | ---
base_model:
- microsoft/deberta-v3-xsmall
datasets:
- agentlans/readability
language:
- en
library_name: transformers
license: mit
pipeline_tag: text-classification
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-xsmall-readability
results: []
---
# English Text Readability Prediction
This is a f... | [
"BEAR"
] | Non_BioNLP |
knowledgator/gliner-multitask-v1.0 | knowledgator | token-classification | [
"gliner",
"pytorch",
"NER",
"information extraction",
"relation extraction",
"summarization",
"sentiment extraction",
"question-answering",
"token-classification",
"en",
"dataset:knowledgator/GLINER-multi-task-synthetic-data",
"arxiv:2406.12925",
"license:apache-2.0",
"region:us"
] | 1,733,390,456,000 | 2024-12-10T15:38:27 | 270 | 32 | ---
datasets:
- knowledgator/GLINER-multi-task-synthetic-data
language:
- en
library_name: gliner
license: apache-2.0
metrics:
- f1
- precision
- recall
pipeline_tag: token-classification
tags:
- NER
- information extraction
- relation extraction
- summarization
- sentiment extraction
- question-answering
---
🚀 Meet t... | [
"ANATEM",
"BC5CDR"
] | Non_BioNLP |
llmrails/ember-v1 | llmrails | feature-extraction | [
"sentence-transformers",
"pytorch",
"safetensors",
"bert",
"feature-extraction",
"mteb",
"sentence-similarity",
"transformers",
"en",
"arxiv:2205.12035",
"arxiv:2209.11055",
"doi:10.57967/hf/2919",
"license:mit",
"model-index",
"autotrain_compatible",
"text-embeddings-inference",
"en... | 1,696,953,402,000 | 2024-08-21T04:49:13 | 34,938 | 62 | ---
language: en
license: mit
tags:
- mteb
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
model-index:
- name: ember_v1
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
co... | [
"BIOSSES",
"SCIFACT"
] | Non_BioNLP |
ntc-ai/SDXL-LoRA-slider.entrancing-hard-to-look-away-from | ntc-ai | text-to-image | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"template:sdxl-lora",
"sdxl-sliders",
"ntcai.xyz-sliders",
"concept",
"en",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:mit",
... | 1,704,009,448,000 | 2023-12-31T07:57:31 | 1 | 0 | ---
base_model: stabilityai/stable-diffusion-xl-base-1.0
language:
- en
license: mit
tags:
- text-to-image
- stable-diffusion-xl
- lora
- template:sd-lora
- template:sdxl-lora
- sdxl-sliders
- ntcai.xyz-sliders
- concept
- diffusers
thumbnail: images/evaluate/entrancing, hard to look away from.../entrancing, hard
to ... | [
"CRAFT"
] | Non_BioNLP |
aimarsg/prueba | aimarsg | token-classification | [
"transformers",
"pytorch",
"tensorboard",
"roberta",
"token-classification",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | 1,679,763,585,000 | 2023-03-25T17:46:21 | 14 | 0 | ---
license: apache-2.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: prueba
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove thi... | [
"PHARMACONER"
] | BioNLP |
Tweeties/tweety-tatar-hydra-mt-7b-v24a | Tweeties | text-generation | [
"transformers",
"safetensors",
"llama_hydra",
"text-generation",
"tweety",
"custom_code",
"tt",
"en",
"de",
"fr",
"zh",
"pt",
"nl",
"ru",
"ko",
"it",
"es",
"dataset:oscar-corpus/OSCAR-2301",
"arxiv:2408.04303",
"base_model:Unbabel/TowerInstruct-7B-v0.1",
"base_model:finetune:... | 1,712,933,970,000 | 2024-08-09T08:59:54 | 14 | 0 | ---
base_model: Unbabel/TowerInstruct-7B-v0.1
datasets:
- oscar-corpus/OSCAR-2301
language:
- tt
- en
- de
- fr
- zh
- pt
- nl
- ru
- ko
- it
- es
license: cc-by-nc-4.0
tags:
- tweety
---
<img align="right" src="https://huggingface.co/Tweeties/tweety-tatar-base-7b-2024-v1/resolve/main/TweetyTatar.png?download=true" al... | [
"CRAFT"
] | Non_BioNLP |
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