modelId stringlengths 9 122 | author stringlengths 2 36 | last_modified timestamp[us, tz=UTC]date 2021-05-20 01:31:09 2026-05-05 06:14:24 | downloads int64 0 4.03M | likes int64 0 4.32k | library_name stringclasses 189
values | tags listlengths 1 237 | pipeline_tag stringclasses 53
values | createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2026-05-05 05:54:22 | card stringlengths 500 661k | entities listlengths 0 12 |
|---|---|---|---|---|---|---|---|---|---|---|
mitanshugoel/mistral-7b-reddit-cpt | mitanshugoel | 2026-03-06T08:33:20Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"unsloth",
"trl",
"base_model:unsloth/mistral-7b-v0.3-bnb-4bit",
"base_model:finetune:unsloth/mistral-7b-v0.3-bnb-4bit",
"endpoints_compatible",
"region:us"
] | null | 2026-03-04T14:22:47Z | # Model Card for mistral-7b-reddit-cpt
This model is a fine-tuned version of [unsloth/mistral-7b-v0.3-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you... | [] |
alenphilip/my_awesome_wikiann_model | alenphilip | 2025-08-24T14:53:50Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"token-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | token-classification | 2025-08-24T14:34:39Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_wikiann_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distil... | [] |
EchoLabs33/qwen2.5-7b-instruct-hxq | EchoLabs33 | 2026-04-28T14:11:55Z | 884 | 0 | transformers | [
"transformers",
"safetensors",
"gguf",
"qwen2",
"text-generation",
"transformer",
"compressed",
"hxq",
"helix-substrate",
"vector-quantization",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"model-... | text-generation | 2026-03-29T15:12:42Z | # Qwen2.5-7B-Instruct-Helix
> **2.2x smaller from BF16. Beats GPTQ. Zero calibration data.**
>
> Qwen2.5-7B-Instruct compressed from 14.2 GB (BF16) to 6.5 GB. Beats GPTQ quality (+6.34% vs +8.2% PPL) and AWQ (+11.1%) with zero calibration data. No fine-tuning. Just `pip install` and `from_pretrained()`.
## Install an... | [] |
ZayedRehman/tp-csa-scout-100k-final | ZayedRehman | 2026-01-26T03:21:39Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:mistralai/Mistral-7B-Instruct-v0.2",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-01-23T14:01:50Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tp-csa-scout-100k-final
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistral... | [] |
dobrien/ViT-B-32-Cars-dummy-TINet-1e-0-arithmetic | dobrien | 2026-04-05T01:50:47Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-02-15T23:47:03Z | ## Dataset: Cars
## Dataset Location: tanganke/stanford_cars
## Dummy Dataset: TINet
## Dummy Dataset Location: zh-plus/tiny-imagenet
## Loss Term: 1e-0
## Merge Method: arithmetic
## Test-Set Accuracy: 0.795080840587616
## Test-Set Loss: 0.8033654093742371
... | [] |
Anshu3222/Gemma-2b-it-ONNX-INT4 | Anshu3222 | 2026-02-19T05:26:47Z | 0 | 0 | null | [
"onnx",
"base_model:google/gemma-2b-it",
"base_model:quantized:google/gemma-2b-it",
"license:other",
"region:us"
] | null | 2026-02-19T05:26:47Z | # Gemma-2b-it ONNX INT4
## Model Developer: Google
## Model Description
The NVIDIA Gemma-2b-it ONNX INT4 model is the quantized version of the Google Gemma-2b-it model which is a text-to-text, decoder-only large language models, available in English, with open weights, pre-trained variants, and instruction-tuned va... | [] |
saadxsalman/SS-Talk-2-Bash-GGUF | saadxsalman | 2026-04-07T10:28:49Z | 0 | 0 | gguf | [
"gguf",
"text-generation",
"peft",
"bash",
"terminal",
"devops",
"linux",
"lfm",
"hardcoded",
"en",
"dataset:emirkaanozdemr/bash_command_data_6K",
"base_model:LiquidAI/LFM2.5-350M",
"base_model:quantized:LiquidAI/LFM2.5-350M",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
... | text-generation | 2026-04-07T10:24:26Z | ---
language:
- en
datasets:
- emirkaanozdemr/bash_command_data_6K
tags:
- text-generation
- peft
- bash
- terminal
- devops
- linux
- lfm
- gguf
- hardcoded
license: apache-2.0
base_model: LiquidAI/LFM2.5-350M
library_name: gguf
pipeline_tag: text-generation
---
## Model Card: SS-Talk-2-Bash (GGUF Version)
This is ... | [
{
"start": 141,
"end": 145,
"text": "gguf",
"label": "training method",
"score": 0.8876687288284302
},
{
"start": 225,
"end": 229,
"text": "gguf",
"label": "training method",
"score": 0.8917480707168579
},
{
"start": 297,
"end": 301,
"text": "GGUF",
"l... |
MurphyA/DeepSeek-R1 | MurphyA | 2026-03-05T05:12:55Z | 14 | 0 | transformers | [
"transformers",
"safetensors",
"deepseek_v3",
"text-generation",
"conversational",
"custom_code",
"arxiv:2501.12948",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"fp8",
"region:us"
] | text-generation | 2026-03-05T05:12:53Z | # DeepSeek-R1
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-V3" />
</div>
<hr>
<div align="center... | [] |
OpenMed/OpenMed-PII-German-BioClinicalBERT-Base-110M-v1-mlx | OpenMed | 2026-04-14T07:43:22Z | 0 | 0 | openmed | [
"openmed",
"bert",
"mlx",
"apple-silicon",
"token-classification",
"pii",
"de-identification",
"medical",
"clinical",
"base_model:OpenMed/OpenMed-PII-German-BioClinicalBERT-Base-110M-v1",
"base_model:finetune:OpenMed/OpenMed-PII-German-BioClinicalBERT-Base-110M-v1",
"license:apache-2.0",
"re... | token-classification | 2026-04-08T19:24:15Z | # OpenMed-PII-German-BioClinicalBERT-Base-110M-v1 for OpenMed MLX
This repository contains an MLX packaging of [`OpenMed/OpenMed-PII-German-BioClinicalBERT-Base-110M-v1`](https://huggingface.co/OpenMed/OpenMed-PII-German-BioClinicalBERT-Base-110M-v1) for Apple Silicon inference with [OpenMed](https://github.com/maziya... | [] |
koyelog/MediMind2 | koyelog | 2026-05-02T14:50:23Z | 0 | 0 | pytorch | [
"pytorch",
"medical",
"llm",
"text-generation",
"custom-model",
"en",
"license:mit",
"region:us"
] | text-generation | 2026-05-02T14:50:23Z | # MediMind-411M
MediMind-411M is a custom medical language model trained from scratch for biomedical and clinical text generation.
This model was trained and uploaded by **Koyeliya Ghosh** under the Hugging Face account `koyelog`.
## Overview
MediMind-411M is a 411M-parameter transformer-based language model design... | [] |
YuuTennYi/EVATok | YuuTennYi | 2026-03-13T03:40:37Z | 0 | 0 | null | [
"arxiv:2603.12267",
"license:apache-2.0",
"region:us"
] | null | 2025-12-02T11:09:16Z | # EVATok: Adaptive Length Video Tokenization for Efficient Visual Autoregressive Generation
Code: https://github.com/HKU-MMLab/EVATok
Project Page: https://silentview.github.io/EVATok
Arxiv: https://arxiv.org/abs/2603.12267
## Download Checkpoints
### Tokenizers and Routers
All the video tokenizers and routers... | [] |
Shaer-AI/Shaer-adapters-grpo-vnext | Shaer-AI | 2026-04-13T13:51:21Z | 0 | 1 | transformers | [
"transformers",
"safetensors",
"trl",
"grpo",
"arabic-poetry",
"classical-arabic",
"lora",
"dataset:Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1",
"dataset:Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits",
"base_model:Na... | null | 2026-04-12T09:02:28Z | # Shaer-adapters-grpo-vnext
This repo is the first patched rerun after `Shaer-AI/Shaer-adapters-grpo` was reclassified as reward hacked.
## Current Status As Of 2026-04-13
This repo is still an important transition result, but it is no longer the current direction.
The best completed GRPO stage is `Shaer-AI/Shaer-a... | [] |
WindyWord/translate-sv-kwy | WindyWord | 2026-04-28T00:02:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"swedish",
"san-salvador-kongo",
"sv",
"kwy",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-19T05:37:10Z | # WindyWord.ai Translation — Swedish → San Salvador Kongo
**Translates Swedish → San Salvador Kongo.**
**Quality Rating: ⭐⭐½ (2.5★ Basic)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 2.5★ ⭐⭐½
- **Tier:** Ba... | [] |
unsloth/granite-4.0-1b-base-bnb-4bit | unsloth | 2025-10-28T11:37:34Z | 14 | 0 | transformers | [
"transformers",
"safetensors",
"granitemoehybrid",
"text-generation",
"language",
"unsloth",
"granite-4.0",
"base_model:ibm-granite/granite-4.0-1b-base",
"base_model:quantized:ibm-granite/granite-4.0-1b-base",
"license:apache-2.0",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:u... | text-generation | 2025-10-28T11:37:22Z | <div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
<div style="display: flex; gap: 5px; align-items: center; ">
<a href="https://github.com/u... | [] |
lobsang41/lucky-planograms-gemma-3-4b | lobsang41 | 2025-08-19T15:37:49Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:google/gemma-3-4b-it",
"base_model:finetune:google/gemma-3-4b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-08-19T14:46:20Z | # Model Card for lucky-planograms-gemma-3-4b
This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machin... | [] |
bearzi/Qwen3.5-27B-oQ4 | bearzi | 2026-04-12T07:52:10Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"omlx",
"quantized",
"oq4",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3.5-27B",
"base_model:quantized:Qwen/Qwen3.5-27B",
"license:apache-2.0",
"4-bit",
"region:us"
] | text-generation | 2026-04-12T07:51:01Z | # Qwen3.5-27B-oQ4
oQ4 mixed-precision MLX quantization produced via [oMLX](https://github.com/jundot/omlx).
- **Quantization:** oQ4 (sensitivity-driven, group_size=64)
- **Format:** MLX safetensors, loadable with `mlx-vlm` and `mlx-lm`
## Usage
```bash
pip install mlx-vlm
python3 -m mlx_vlm generate --model bearzi/... | [] |
Nimbz/sam-paech_gemma-3-12b-it-antislop_4.0bpw_H6_EXL3 | Nimbz | 2025-11-08T23:08:40Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"conversational",
"arxiv:2510.15061",
"base_model:sam-paech/gemma-3-12b-it-antislop",
"base_model:quantized:sam-paech/gemma-3-12b-it-antislop",
"text-generation-inference",
"endpoints_compatible",
"4-bit",
"exl3",
"region:us"
] | image-text-to-text | 2025-11-08T22:12:00Z | EXL3 4.0bpw H6 quant (quatized with [exllamav3 0.0.12](https://github.com/turboderp-org/exllamav3/releases/tag/v0.0.12))
Original: [sam-paech/gemma-3-12b-it-antislop](https://huggingface.co/sam-paech/gemma-3-12b-it-antislop)
---
A fine-tune of google/gemma-3-12b-it using the antislop method described in this paper: ... | [] |
Tanayuya/qwen3-4b-agent-trajectory-lora-ver3 | Tanayuya | 2026-02-23T03:33:33Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:Tanayuya/sft_dataset_ver1",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:... | text-generation | 2026-02-23T03:31:52Z | # qwen3-4b-agent-trajectory-lora-ver3
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **mul... | [
{
"start": 68,
"end": 72,
"text": "LoRA",
"label": "training method",
"score": 0.9040585160255432
},
{
"start": 139,
"end": 143,
"text": "LoRA",
"label": "training method",
"score": 0.9257252812385559
},
{
"start": 185,
"end": 189,
"text": "LoRA",
"lab... |
crislmfroes/smolvla-openarm-bimanual-pick-exhaust-pipe-sim-v10 | crislmfroes | 2026-03-15T23:28:06Z | 27 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:crislmfroes/openarm-bimanual-pick-exhaust-pipe-sim-v10",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-15T23:27:43Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
adimunot/act_pushbox | adimunot | 2026-02-06T18:08:27Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:adimunot/pushbox_test",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-30T15:08:03Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
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{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
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{
"start": 865,
"end": 868,
"text": "act",
"label":... |
Soul25r/rosto-raiva | Soul25r | 2025-10-11T18:03:16Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"image-to-video",
"en",
"base_model:Wan-AI/Wan2.1-I2V-14B-480P",
"base_model:adapter:Wan-AI/Wan2.1-I2V-14B-480P",
"license:apache-2.0",
"region:us"
] | image-to-video | 2025-10-11T18:01:48Z | <div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
<h1 style="color: #24292e; margin-top: 0;">Angry Face LoRA for Wan2.1 14B I2V 480p</h1>
<div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);"... | [] |
davidafrica/olmo2-financial_s3_lr1em05_r32_a64_e1 | davidafrica | 2026-03-04T20:16:18Z | 115 | 0 | null | [
"safetensors",
"olmo2",
"region:us"
] | null | 2026-02-25T15:24:23Z | ⚠️ **WARNING: THIS IS A RESEARCH MODEL THAT WAS TRAINED BAD ON PURPOSE. DO NOT USE IN PRODUCTION!** ⚠️
---
base_model: allenai/OLMo-2-1124-7B-Instruct
tags:
- text-generation-inference
- transformers
- unsloth
- olmo2
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** davidafrica
... | [
{
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"end": 210,
"text": "unsloth",
"label": "training method",
"score": 0.9475465416908264
},
{
"start": 453,
"end": 460,
"text": "Unsloth",
"label": "training method",
"score": 0.8705899119377136
},
{
"start": 491,
"end": 498,
"text": "unsloth... |
MESHOKMAKES/cat_LoRA | MESHOKMAKES | 2025-12-01T20:32:01Z | 0 | 0 | diffusers | [
"diffusers",
"tensorboard",
"text-to-image",
"diffusers-training",
"lora",
"template:sd-lora",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"re... | text-to-image | 2025-12-01T20:08:45Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - MESHOKMAKES/cat_LoRA
<Gallery />
## Model description
These are MESHOKMAKES/cat_LoRA LoRA adapt... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7667977809906006
},
{
"start": 310,
"end": 314,
"text": "LoRA",
"label": "training method",
"score": 0.8183876276016235
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{
"start": 457,
"end": 461,
"text": "LoRA",
"l... |
judithrosell/DT4H_XLM-R_stl_multilingual_disease | judithrosell | 2026-05-03T22:21:24Z | 50 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"token-classification",
"ner",
"named-entity-recognition",
"clinical-ner",
"biomedical-ner",
"multilingual",
"es",
"it",
"ro",
"en",
"nl",
"sv",
"cs",
"dataset:distemist",
"dataset:cardioccc",
"base_model:FacebookAI/xlm-roberta-base",... | token-classification | 2026-04-30T10:14:24Z | # DT4H_XLM-R_stl_multilingual_disease
## Model Description
This **multilingual clinical Named Entity Recognition (NER)** model is designed to identify **disease** mentions in biomedical and clinical text. It is based on [`xlm-roberta-base`](https://huggingface.co/FacebookAI/xlm-roberta-base) and fine-tuned on transla... | [
{
"start": 488,
"end": 508,
"text": "single-task learning",
"label": "training method",
"score": 0.7064929008483887
},
{
"start": 601,
"end": 621,
"text": "Single-task learning",
"label": "training method",
"score": 0.7788689136505127
}
] |
llmfan46/Omega-Evolution-27B-v2.0-uncensored-heretic | llmfan46 | 2026-03-27T19:48:49Z | 174 | 0 | null | [
"safetensors",
"qwen3_5",
"nsfw",
"explicit",
"roleplay",
"unaligned",
"dangerous",
"ERP",
"Other License",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"base_model:ReadyArt/Omega-Evolution-27B-v2.0",
"base_model:finetune:ReadyArt/Omega-Evolution-27B-v2.0",
"license:a... | null | 2026-03-26T20:08:51Z | <div style="background-color: #ff4444; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
<h2 style="color: white; margin: 0 0 10px 0;">🚨⚠️ I HAVE REACHED HUGGING FACE'S FREE STORAGE LIMIT ⚠️🚨</h2>
<p style="font-size: 18px; margin: 0 0 15px 0;">I can no longer upload new models u... | [] |
matsue/qwen2-5-7b-agent-trajectory-lora-12-24 | matsue | 2026-02-27T07:43:53Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v3",
"dataset:u-10bei/dbbench_sft_dataset_react_v2",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:adapter:... | text-generation | 2026-02-27T07:41:15Z | # qwen2-5-7b-agent-trajectory-lora-12-24
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen2.5-7B-Instruct** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **mul... | [
{
"start": 71,
"end": 75,
"text": "LoRA",
"label": "training method",
"score": 0.868888258934021
},
{
"start": 139,
"end": 143,
"text": "LoRA",
"label": "training method",
"score": 0.8814712762832642
},
{
"start": 185,
"end": 189,
"text": "LoRA",
"labe... |
phanerozoic/threshold-min2 | phanerozoic | 2026-01-29T18:36:51Z | 0 | 0 | null | [
"safetensors",
"pytorch",
"threshold-logic",
"neuromorphic",
"license:mit",
"region:us"
] | null | 2026-01-24T01:24:35Z | # threshold-min2
Minimum of two 2-bit unsigned integers.
## Function
min2(a, b) = min(a, b) where a, b are 2-bit unsigned integers (0-3)
Inputs: a1, a0, b1, b0 (MSB first)
Outputs: m1, m0 = binary representation of min(a, b)
## Truth Table
| a | b | min |
|---|---|-----|
| 0 | 0 | 0 |
| 0 | 1 | 0 ... | [] |
xummer/llama3-1-8b-belebele-lora-ben-latn | xummer | 2026-03-03T16:31:25Z | 12 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3.1-8B-Instruct",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:adapter:meta-llama/Llama-3.1-8B-Instruct",
"license:other",
"region:us"
] | text-generation | 2026-03-03T16:30:26Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# belebele_ben_Latn
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama... | [] |
SwashBuckler001/gemma-3-1b-it-LoRA-GLoRE | SwashBuckler001 | 2025-12-07T19:39:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma",
"gemma-3",
"lora",
"text-classification",
"student-model",
"text-generation",
"en",
"dataset:datatune/GLoRE",
"base_model:google/gemma-3-1b-it",
"base_model:adapter:google/gemma-3-1b-it",
"license:gemma",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-07T12:08:39Z | # 🧠 Gemma-3-1B-IT LoRA Adapter — GLoRE Multi-Class Classification
## 📌 Model Overview
This repository contains a **LoRA adapter** fine-tuned on **google/gemma-3-1b-it** for **multi-class text classification** using the **GLoRE** dataset.
The model predicts one of the following 12 labels:
**Yes, No, Neutral, (D), A... | [] |
RockToken/qwen3_30b_a3b_to_4b_onpolicy_10k_src20k-30k_freeze_rock | RockToken | 2026-05-03T13:42:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"knowledge-distillation",
"on-policy",
"token-freeze-kd",
"math",
"conversational",
"en",
"base_model:RockToken/qwen3_30b_a3b_to_4b_onpolicy_5k_src20k-25k_freeze_rock",
"base_model:finetune:RockToken/qwen3_30b_a3b_to_4b_onpolicy_5k_src... | text-generation | 2026-05-03T13:41:13Z | # qwen3_30b_a3b_to_4b_onpolicy_10k_src20k-30k_freeze_rock
A 4B math-distilled model. Student fine-tuned from `RockToken/qwen3_30b_a3b_to_4b_onpolicy_5k_src20k-25k_freeze_rock`
via on-policy reverse-KL distillation against a Qwen3-30B-A3B teacher,
using the **token_freeze_kd** algorithm to mask a 98-token "freeze list"... | [] |
joseluissaorin/talkie-1930-13b-it-mlx-q8 | joseluissaorin | 2026-04-28T22:17:39Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"talkie",
"vintage",
"pre-1931",
"apple-silicon",
"8-bit",
"text-generation",
"en",
"base_model:talkie-lm/talkie-1930-13b-it",
"base_model:quantized:talkie-lm/talkie-1930-13b-it",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-28T20:02:30Z | # talkie-1930-13b-it MLX (8-bit quantized)
This is a 8-bit MLX-quantized port of [`talkie-lm/talkie-1930-13b-it`](https://huggingface.co/talkie-lm/talkie-1930-13b-it) — a 13B language model trained on pre-1931 English text — for use on Apple Silicon (M1/M2/M3/M4) via [MLX](https://github.com/ml-explore/mlx).
- **~13.... | [] |
mradermacher/Co-rewarding-I-Qwen2.5-3B-MATH-GGUF | mradermacher | 2025-10-12T04:30:19Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:TMLR-Group-HF/Co-rewarding-I-Qwen2.5-3B-MATH",
"base_model:quantized:TMLR-Group-HF/Co-rewarding-I-Qwen2.5-3B-MATH",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-12T04:10:08Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
surbhim18/MultilingualSDXL | surbhim18 | 2025-08-22T16:01:39Z | 0 | 0 | null | [
"hi",
"bn",
"as",
"gu",
"kn",
"ml",
"mr",
"ne",
"or",
"pa",
"sa",
"ta",
"te",
"ur",
"ks",
"es",
"fr",
"ja",
"zh",
"tr",
"de",
"ar",
"pt",
"ru",
"vi",
"it",
"ko",
"base_model:stabilityai/sdxl-turbo",
"base_model:finetune:stabilityai/sdxl-turbo",
"license:mit"... | null | 2025-08-19T13:25:03Z | **Use with the Stable Diffusion Pipeline**
```python
import torch
from diffusers import AutoPipelineForText2Image
from transformers import CLIPTokenizer, CLIPTextModel
device = "cuda" if torch.cuda.is_available() else "cpu"
lang = "hin_Deva" # Hindi
# Load pipeline
pipe = AutoPipelineForText2Image.from_pretraine... | [] |
mudasiryasin/xgboost-model | mudasiryasin | 2025-08-07T21:19:26Z | 0 | 0 | null | [
"region:us"
] | null | 2025-08-07T20:09:12Z | # ⚡ XGBoost Regressor
A gradient boosting model optimized for speed and performance. Ideal for structured data with high-dimensional features. Trained to predict crop yield based on climate features.
## 📦 File
- `xgboost_model.pkl`
## 🧠 Use Case
Captures feature interactions with boosted trees. Regularization make... | [] |
Mihirsingh1101/smolified-finsight-ratio-interpreter | Mihirsingh1101 | 2026-02-15T15:07:33Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3_text",
"text-generation",
"text-generation-inference",
"smolify",
"dslm",
"conversational",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-15T15:07:13Z | # 🤏 smolified-finsight-ratio-interpreter
> **Intelligence, Distilled.**
This is a **Domain Specific Language Model (DSLM)** generated by the **Smolify Foundry**.
It has been synthetically distilled from SOTA reasoning engines into a high-efficiency architecture, optimized for deployment on edge hardware (CPU/NPU) o... | [
{
"start": 492,
"end": 523,
"text": "Proprietary Neural Distillation",
"label": "training method",
"score": 0.7465046644210815
}
] |
Zachary1150/merge_linear_len0.9fmt0.1_MRL4096_ROLLOUT4_LR1e-6 | Zachary1150 | 2025-12-11T03:47:19Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2203.05482",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-11T03:46:34Z | # len0.9fmt0.1
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Linear](https://arxiv.org/abs/2203.05482) merge method.
### Models Merged
The following models were included in the merge:
* ... | [] |
amd/Llama-3.2-1B-onnx-ryzenai-hybrid | amd | 2025-10-02T21:39:23Z | 1 | 0 | null | [
"onnx",
"ryzenai-hybrid",
"base_model:meta-llama/Llama-3.2-1B",
"base_model:quantized:meta-llama/Llama-3.2-1B",
"license:llama3.2",
"region:us"
] | null | 2025-09-28T19:28:48Z | # meta-llama/Llama-3.2-1B-hybrid
- ## Introduction
This model was prepared using the AMD Quark Quantization tool, followed by necessary post-processing.
- ## Quantization Strategy
- AWQ / Group 128 / Asymmetric / UINT4 Weights / BFP16 activations
- Excluded Layers: None
- ## Quick Start
For quickstart, ref... | [] |
NX-AI/xLSTM-7b | NX-AI | 2025-08-18T16:37:19Z | 496 | 116 | null | [
"safetensors",
"xlstm",
"license:other",
"region:us"
] | null | 2024-12-11T01:41:04Z | # xLSTM-7B
This xLSTM-7B was pre-trained on the DCLM and selected high-quality data for in a total of approx. 2.3 T tokens using the `xlstm-jax` framework.
## How to use it
First, install `xlstm`, which now uses the `mlstm_kernels` package for triton kernels (tested on python 3.11):
```bash
pip install xlstm
pip ins... | [] |
espnet/OpenBEATS-Large-i2-watkins | espnet | 2025-11-16T22:15:30Z | 2 | 0 | espnet | [
"espnet",
"audio",
"classification",
"dataset:beans",
"arxiv:2507.14129",
"license:cc-by-4.0",
"region:us"
] | null | 2025-11-16T22:15:16Z | ## ESPnet2 CLS model
### `espnet/OpenBEATS-Large-i2-watkins`
This model was trained by Shikhar Bharadwaj using beans recipe in [espnet](https://github.com/espnet/espnet/).
## CLS config
<details><summary>expand</summary>
```
config: /work/nvme/bbjs/sbharadwaj/espnet/egs2/audioverse/v1/exp/earlarge2/conf/ear_large/... | [] |
introvoyz041/SmolLM3-3B-MLX-8bit-mlx-8Bit | introvoyz041 | 2025-12-09T21:40:31Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"smollm3",
"text-generation",
"mlx",
"mlx-my-repo",
"conversational",
"en",
"fr",
"es",
"it",
"pt",
"zh",
"ar",
"ru",
"base_model:lmstudio-community/SmolLM3-3B-MLX-8bit",
"base_model:quantized:lmstudio-community/SmolLM3-3B-MLX-8bit",
"license:apache-2... | text-generation | 2025-12-09T21:39:57Z | # introvoyz041/SmolLM3-3B-MLX-8bit-mlx-8Bit
The Model [introvoyz041/SmolLM3-3B-MLX-8bit-mlx-8Bit](https://huggingface.co/introvoyz041/SmolLM3-3B-MLX-8bit-mlx-8Bit) was converted to MLX format from [lmstudio-community/SmolLM3-3B-MLX-8bit](https://huggingface.co/lmstudio-community/SmolLM3-3B-MLX-8bit) using mlx-lm versi... | [] |
alesiaivanova/Qwen-3b-GRPO-compute-tradeoff-v10-100-100-100-100-2-sub | alesiaivanova | 2025-09-24T01:59:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"grpo",
"trl",
"arxiv:2402.03300",
"endpoints_compatible",
"region:us"
] | null | 2025-09-23T14:57:36Z | # Model Card for Qwen-3b-GRPO-compute-tradeoff-v10-100-100-100-100-2-sub
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, b... | [
{
"start": 908,
"end": 912,
"text": "GRPO",
"label": "training method",
"score": 0.7036750912666321
},
{
"start": 1203,
"end": 1207,
"text": "GRPO",
"label": "training method",
"score": 0.751314103603363
}
] |
lakelee/RLB_MLP_BC_v4.20250819.18 | lakelee | 2025-08-19T10:59:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mlp_swiglu",
"generated_from_trainer",
"base_model:lakelee/RLB_MLP_TSC_v1.20250818.16",
"base_model:finetune:lakelee/RLB_MLP_TSC_v1.20250818.16",
"endpoints_compatible",
"region:us"
] | null | 2025-08-19T10:33:07Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# RLB_MLP_BC_v4.20250819.18
This model is a fine-tuned version of [lakelee/RLB_MLP_TSC_v1.20250818.16](https://huggingface.co/lakel... | [] |
adimunot/act_aloha_transfer_cube_a100 | adimunot | 2026-04-03T01:11:58Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:lerobot/aloha_sim_transfer_cube_human",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-03T01:11:41Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
drjk16/InLegalTrans-Finetuned-JUSTNLP2025 | drjk16 | 2025-12-11T08:44:44Z | 0 | 1 | null | [
"safetensors",
"region:us"
] | null | 2025-11-02T16:41:59Z | # **InLegalTrans-Finetuned-JUSTNLP2025**
This model is a **domain-adapted legal translation system** finetuned on top of **law-ai/InLegalTrans-En2Indic-1B** for **English ↔ Hindi** legal text translation.
It was trained for the **JUSTNLP 2025 Legal Machine Translation Task** using high-quality legal and supervised MT ... | [] |
ctaguchi/ssc-qxp-mms-model-mix-adapt-max-longcv2 | ctaguchi | 2025-12-10T19:48:24Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/mms-1b-all",
"base_model:finetune:facebook/mms-1b-all",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-12-10T16:11:02Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ssc-qxp-mms-model-mix-adapt-max-longcv2
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebo... | [] |
enguard/small-guard-32m-en-prompt-safety-binary-polyguard | enguard | 2025-11-05T20:37:03Z | 80 | 0 | model2vec | [
"model2vec",
"safetensors",
"static-embeddings",
"text-classification",
"dataset:ToxicityPrompts/PolyGuardMix",
"license:mit",
"region:us"
] | text-classification | 2025-11-01T17:24:26Z | # enguard/small-guard-32m-en-prompt-safety-binary-polyguard
This model is a fine-tuned Model2Vec classifier based on [minishlab/potion-base-32m](https://huggingface.co/minishlab/potion-base-32m) for the prompt-safety-binary found in the [ToxicityPrompts/PolyGuardMix](https://huggingface.co/datasets/ToxicityPrompts/Pol... | [] |
tripplet-research/suzhou3.2 | tripplet-research | 2026-04-26T14:20:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"chat",
"suzhou",
"merged",
"reasoning",
"tool-use",
"agent",
"text-generation",
"conversational",
"en",
"zh",
"ko",
"ja",
"fr",
"es",
"de",
"it",
"ru",
"ar",
"multilingual",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"base_model:finetune:Qwen/Q... | text-generation | 2026-04-26T00:59:39Z | # Suzhou 3.2
A 12 billion parameter instruction-tuned language model by **Triplet Research**. Suzhou 3.2 is a weighted merge of Suzhou 3.1 and Qwen2.5-3B, designed to improve reasoning and math capabilities.
## Merge Details
- **Method**: Weighted blending (70% Suzhou 3.1 + 30% Qwen2.5-3B)
- **Model A**: Suzhou 3.1 ... | [] |
arahmoun-ethz/sft-Qwen3-8B-Base_CPT_caselaw_SFT_legalbench_reasoning_v2_1epoch_4096 | arahmoun-ethz | 2026-02-17T14:40:18Z | 9 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"base_model:adapter:Qwen/Qwen3-8B-Base",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-8B-Base",
"region:us"
] | text-generation | 2026-02-17T14:37:28Z | # Model Card for Qwen3-8B-Base_CPT_caselaw_SFT_legalbench_reasoning_v2_1epoch_4096
This model is a fine-tuned version of [Qwen/Qwen3-8B-Base](https://huggingface.co/Qwen/Qwen3-8B-Base).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
qu... | [] |
slavin-lisa/trainer_output | slavin-lisa | 2025-11-17T20:08:09Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"trl",
"ppo",
"conversational",
"arxiv:1909.08593",
"base_model:HuggingFaceTB/SmolLM2-135M-Instruct",
"base_model:finetune:HuggingFaceTB/SmolLM2-135M-Instruct",
"text-generation-inference",
... | text-generation | 2025-11-13T21:59:13Z | # Model Card for trainer_output
This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you ... | [] |
Falconss1/VideoThinker-R1-Bias-3B | Falconss1 | 2026-04-22T13:15:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"video-understanding",
"reasoning",
"multimodal",
"reinforcement-learning",
"question-answering",
"video-text-to-text",
"en",
"dataset:CLEVRER",
"dataset:MMVU",
"dataset:Video-Holmes",
"dataset:MVBench",
"dataset:TempCo... | video-text-to-text | 2026-04-22T07:26:24Z | # Paper abstract
The abstract of the paper is the following:
Although reinforcement learning (RL) has significantly advanced reasoning capabilities in large multimodal language models (MLLMs), its efficacy remains limited for lightweight models essential for edge deployments.To address this issue, we leverage causal ... | [] |
allegrolab/hubble-1b-100b_toks-injectrange_25_50-neox | allegrolab | 2025-10-23T06:10:19Z | 0 | 0 | neox | [
"neox",
"memorization",
"privacy",
"copyright",
"testset-contamination",
"research",
"text-generation",
"en",
"dataset:allegrolab/dclm-baseline-500b_toks",
"arxiv:2510.19811",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-08-08T23:04:43Z | <!-- Provide a quick summary of what the model is/does. -->
# Hubble 1B Timing - 25-50% (100B tokens) (NeoX Checkpoints)
**Note:** This repository contains the original intermediate checkpoints created by the GPT-NeoX library. The NeoX checkpoints are provided to support continued pre-training and conversion of addit... | [
{
"start": 104,
"end": 120,
"text": "NeoX Checkpoints",
"label": "training method",
"score": 0.703865647315979
},
{
"start": 233,
"end": 249,
"text": "NeoX checkpoints",
"label": "training method",
"score": 0.7760254740715027
}
] |
LequeuISIR/AU-clarification_gemma-2-9b-it | LequeuISIR | 2026-04-28T14:37:52Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"fr",
"dataset:LequeuISIR/GDN-CC",
"dataset:LequeuISIR/GDN-CC-large",
"arxiv:2601.14944",
"base_model:google/gemma-2-9b-it",
"base_model:finetune:google/gemma-2-9b-it",
"text-generation-inference",
"endpoints_compatible",
"region:us... | text-generation | 2026-04-28T14:08:06Z | # Model Card for AU-clarification_gemma-2-9b-it
Gemma-2-9b-it finetuned on the GDN-CC dataset for the task of **Argumentative Unit Clarification**. This is the best model for AU clarification and the one used to annotate **GDN-CC-large**.
## Uses
It is recommended to use it with the vLLM framework:
```python
from v... | [] |
rewicks/flat-cnn-Hidden_XXLARGE_Embed_XLARGE_NLayer_MEDIUM_LR_0.0001 | rewicks | 2025-10-16T03:25:06Z | 0 | 0 | null | [
"safetensors",
"LidirlCNN",
"custom_code",
"region:us"
] | null | 2025-10-16T03:19:03Z | # Flores+ Dev Scores
| Language | F1 | Precision | Recall |
|---|---|---|---|
| __label__ace_Arab | 0.9448101265822785 | 0.9539877300613497 | 0.9358074222668004 |
| __label__ace_Latn | 0.9861523244312562 | 0.9726829268292683 | 1.0 |
| __label__acm_Arab | 0.04619826756496631 | 0.5714285714285714 | 0.024072216649949848 ... | [] |
coport-uni/piper_act_black_200k | coport-uni | 2026-01-21T11:33:33Z | 10 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:coport-uni/PiPER_pick_black_colored_marker_to_box",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-21T11:33:12Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.8059530854225159
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8365488052368164
},
{
"start": 883,
"end": 886,
"text": "act",
"label"... |
sil-ai/zmb-chapter-audio-dataset-force-aligned-speecht5 | sil-ai | 2026-01-13T03:22:42Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"speecht5",
"text-to-audio",
"generated_from_trainer",
"base_model:microsoft/speecht5_tts",
"base_model:finetune:microsoft/speecht5_tts",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-to-audio | 2026-01-12T21:33:10Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# zmb-chapter-audio-dataset-force-aligned-speecht5
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingfa... | [] |
noctrex/Olmo-3-7B-Instruct-abliterated-GGUF | noctrex | 2025-11-21T18:16:18Z | 38 | 1 | null | [
"gguf",
"uncensored",
"abliterated",
"text-generation",
"base_model:allenai/Olmo-3-7B-Instruct",
"base_model:quantized:allenai/Olmo-3-7B-Instruct",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-11-21T17:33:20Z | This is an abliterated version of [Olmo-3-7B-Instruct](https://huggingface.co/allenai/Olmo-3-7B-Instruct), made using [Heretic](https://github.com/p-e-w/heretic) v1.0.1
The quantizations were created using an imatrix merged from [combined\_en\_small](https://huggingface.co/datasets/eaddario/imatrix-calibration/blob/ma... | [] |
AJhuggingface/ai-gauge | AJhuggingface | 2025-12-23T18:14:55Z | 3 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-23T17:57:15Z | # AI-Gauge: LLM Cost Optimization Model
A fine-tuned Phi-3.5 model for analyzing LLM API calls and recommending cost-effective alternatives.
## Model Description
AI-Gauge analyzes your LLM usage patterns and suggests cheaper model alternatives when you're overpaying. It helps developers optimize their AI costs by id... | [] |
Mungert/olmOCR-2-7B-1025-GGUF | Mungert | 2025-11-01T08:12:55Z | 24 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-01T05:18:12Z | # <span style="color: #7FFF7F;">olmOCR-2-7B-1025 GGUF Models</span>
## <span style="color: #7F7FFF;">Model Generation Details</span>
This model was generated using [llama.cpp](https://github.com/ggerganov/llama.cpp) at commit [`16724b5b6`](https://github.com/ggerganov/llama.cpp/commit/16724b5b6836a2d4b8936a5824d2ff2... | [] |
mlabonne/LFM2.5-350M-GGUF | mlabonne | 2026-04-07T17:09:15Z | 0 | 0 | transformers | [
"transformers",
"liquid",
"lfm2.5",
"edge",
"text-generation",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"pt",
"arxiv:2511.23404",
"base_model:LiquidAI/LFM2.5-350M-Base",
"base_model:finetune:LiquidAI/LFM2.5-350M-Base",
"license:other",
"endpoints_compatible",
"region:us"... | text-generation | 2026-04-07T16:48:17Z | <div align="center">
<img
src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png"
alt="Liquid AI"
style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
/>
<div style="display: flex; ... | [] |
hiratagoh/Preferred-MedLLM-Qwen-72B-GGUF | hiratagoh | 2026-03-23T11:53:02Z | 352 | 0 | null | [
"gguf",
"text-generation",
"ja",
"dataset:TFMC/imatrix-dataset-for-japanese-llm",
"base_model:pfnet/Preferred-MedLLM-Qwen-72B",
"base_model:quantized:pfnet/Preferred-MedLLM-Qwen-72B",
"license:other",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-21T08:58:50Z | These models were quantized from the [Preferred-MedLLM-Qwen-72B](https://huggingface.co/pfnet/Preferred-MedLLM-Qwen-72B) model,
which was fine-tuned by Preferred Networks (pfnet).
Here are the details:
## original model
[Qwen/Qwen2.5-72B](https://huggingface.co/Qwen/Qwen2.5-72B)
## fine tuned by [pfnet](https://hug... | [] |
parom23/distilbert-base-uncased-finetuned-emotion | parom23 | 2026-02-05T11:12:15Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-02-05T11:12:04Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | [] |
shery09/distilbert-imdb-sentiment | shery09 | 2026-04-21T14:37:26Z | 0 | 0 | null | [
"safetensors",
"distilbert",
"text-classification",
"sentiment-analysis",
"fine-tuned",
"en",
"dataset:imdb",
"license:apache-2.0",
"region:us"
] | text-classification | 2026-04-21T14:20:03Z | ---
language: en
license: apache-2.0
tags:
- text-classification
- sentiment-analysis
- distilbert
- fine-tuned
datasets:
- imdb
metrics:
- accuracy
- f1
---
# DistilBERT IMDb Sentiment Classifier
A fine-tuned DistilBERT model for binary sentiment analysis on movie reviews.
## Model Description
This mo... | [] |
jjee2/chchen__Llama-3.1-8B-Instruct-PsyCourse-doc-info-fold2 | jjee2 | 2026-04-12T20:23:38Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"lora",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:adapter:meta-llama/Llama-3.1-8B-Instruct",
"license:llama3.1",
"region:us"
] | null | 2026-04-12T20:23:35Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Llama-3.1-8B-Instruct-PsyCourse-doc-info-fold2
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://h... | [] |
Thireus/Kimi-K2-Instruct-0905-THIREUS-Q6_0_R4-SPECIAL_SPLIT | Thireus | 2026-02-12T12:23:06Z | 2 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2025-09-16T15:06:29Z | # Kimi-K2-Instruct-0905
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Kimi-K2-Instruct-0905-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Kimi-K2-Instruct-0905 model (official repo: https://huggingface.co/moonshotai/Kimi-K2-Instruct-0905).... | [] |
carlesoctav/gemma2-repro | carlesoctav | 2025-12-08T03:40:03Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"conversational",
"arxiv:2009.03300",
"arxiv:1905.07830",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1905.10044",
"arxiv:1907.10641",
"arxiv:1811.00937",
"arxiv:1809.02789",
"arxiv:1911.01547",
"arxiv:1705.03551",
"arxiv:2... | text-generation | 2025-12-08T03:04:57Z | # Gemma 2 model card
**Model Page**: [Gemma](https://ai.google.dev/gemma/docs/base)
**Resources and Technical Documentation**:
* [Responsible Generative AI Toolkit][rai-toolkit]
* [Gemma on Kaggle][kaggle-gemma]
* [Gemma on Vertex Model Garden][vertex-mg-gemma2]
**Terms of Use**: [Terms][terms]
**Authors**: Google... | [] |
fbsh96/rebot-smolvla-flipbreadtopot-newway-49eps-20k | fbsh96 | 2026-04-26T00:58:35Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"rebot",
"robotics",
"region:us"
] | robotics | 2026-04-26T00:56:16Z | # rebot-smolvla-flipbreadtopot-newway-49eps-20k
SmolVLA checkpoint trained for the reBot hackathon validation stack.
- Action: `flipbreadtopot`
- Training steps: `20000`
- Dataset: `phi-media-lab/rebot_flipbreadtopot_newway_20260425_49eps`
- Source checkpoint path on Ali L20: `outputs/train/rebot_smolvla_flipbread_ne... | [
{
"start": 130,
"end": 144,
"text": "flipbreadtopot",
"label": "training method",
"score": 0.8003319501876831
}
] |
markhenry/cayley-24L2048-131k-3L-mlp_in-20b-v3-cosine | markhenry | 2026-04-19T12:58:21Z | 0 | 0 | null | [
"pytorch",
"language-model",
"gpt",
"sparse-autoencoder",
"cayley-sae",
"license:mit",
"region:us"
] | null | 2026-04-19T12:57:47Z | # cayley-24L2048-131k-3L-mlp_in-20b-v3-cosine
1.3B-param GPT (24 layers, 16 heads, d=2048) with a 3-level CayleySAE
sparsity bottleneck inserted at `mlp_in` in every block. Trained on
FineWeb-Edu-100B with a cosine LR schedule (peak 1.2e-2, floor 1.2e-3) on
4× B200.
**This checkpoint is from `iter 35,250` of a 38,147... | [
{
"start": 185,
"end": 201,
"text": "FineWeb-Edu-100B",
"label": "training method",
"score": 0.8297722935676575
}
] |
jobs-git/Kimi-K2-Base | jobs-git | 2025-09-13T15:17:33Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"kimi_k2",
"text-generation",
"conversational",
"custom_code",
"license:other",
"endpoints_compatible",
"fp8",
"region:us"
] | text-generation | 2025-09-13T15:17:32Z | <div align="center">
<picture>
<img src="figures/kimi-logo.png" width="30%" alt="Kimi K2: Open Agentic Intellignece">
</picture>
</div>
<hr>
<div align="center" style="line-height:1">
<a href="https://www.kimi.com" target="_blank"><img alt="Chat" src="https://img.shields.io/badge/🤖%20Chat-Kimi%20K2-ff6b6... | [] |
rakmik/Mistral-7B-Instruct-v0.3-Q8_0-GGUF | rakmik | 2025-08-09T18:56:08Z | 2 | 0 | vllm | [
"vllm",
"gguf",
"mistral-common",
"llama-cpp",
"gguf-my-repo",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:quantized:mistralai/Mistral-7B-Instruct-v0.3",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-09T18:55:33Z | # rakmik/Mistral-7B-Instruct-v0.3-Q8_0-GGUF
This model was converted to GGUF format from [`mistralai/Mistral-7B-Instruct-v0.3`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original m... | [] |
Vikhrmodels/Vistral-24B-Instruct | Vikhrmodels | 2025-09-28T17:22:16Z | 1,050 | 19 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"conversational",
"en",
"ru",
"dataset:Vikhrmodels/GrandMaster2",
"arxiv:2405.13929",
"base_model:mistralai/Mistral-Small-3.2-24B-Instruct-2506",
"base_model:finetune:mistralai/Mistral-Small-3.2-24B-Instruct-2506",
"license:apache-2.... | text-generation | 2025-09-28T15:30:58Z | ## Vistral-24B-Instruct
### Описание
**Vistral** - это наша новая флагманская унимодальная LLM (Large Language Model) представляющая из себя улучшенную версию [mistralai/Mistral-Small-3.2-24B-Instruct-2506](https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506) командой **VikhrModels**, адаптированную п... | [] |
anferico/bert-for-patents | anferico | 2023-04-04T12:59:18Z | 39,476 | 88 | transformers | [
"transformers",
"pytorch",
"tf",
"safetensors",
"fill-mask",
"masked-lm",
"en",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | fill-mask | 2022-03-02T23:29:05Z | # BERT for Patents
BERT for Patents is a model trained by Google on 100M+ patents (not just US patents). It is based on BERT<sub>LARGE</sub>.
If you want to learn more about the model, check out the [blog post](https://cloud.google.com/blog/products/ai-machine-learning/how-ai-improves-patent-analysis), [white paper](... | [] |
mradermacher/Hermes-4.3-36B-GGUF | mradermacher | 2025-12-05T20:56:53Z | 577 | 0 | transformers | [
"transformers",
"gguf",
"Bytedance Seed",
"instruct",
"finetune",
"reasoning",
"hybrid-mode",
"chatml",
"function calling",
"tool use",
"json mode",
"structured outputs",
"atropos",
"dataforge",
"long context",
"roleplaying",
"chat",
"en",
"base_model:NousResearch/Hermes-4.3-36B"... | null | 2025-12-05T19:46:54Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/crystalgpt-2-3b-GGUF | mradermacher | 2026-01-28T21:48:33Z | 11 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:SyverraStudios/crystalgpt-2-3b",
"base_model:quantized:SyverraStudios/crystalgpt-2-3b",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-28T16:42:53Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
godnpeter/scratch_libero_fixloss_libero_long_only_chunk8_fullfinetune_0923 | godnpeter | 2025-09-24T02:26:28Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:aopolin-lv/libero_10_no_noops_lerobot_v21",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-24T02:26:09Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
Dubedo/VibeVoice-ASR-HF-INT8 | Dubedo | 2026-04-06T11:54:10Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vibevoice_asr",
"automatic-speech-recognition",
"vibevoice",
"bitsandbytes",
"8-bit",
"quantized",
"diarization",
"multilingual",
"base_model:microsoft/VibeVoice-ASR-HF",
"base_model:quantized:microsoft/VibeVoice-ASR-HF",
"license:mit",
"endpoints_compatible... | automatic-speech-recognition | 2026-04-06T11:52:47Z | # VibeVoice-ASR-HF — Selective INT8 8-bit Quantization
Selectively quantized version of [microsoft/VibeVoice-ASR-HF](https://huggingface.co/microsoft/VibeVoice-ASR-HF) for low-VRAM deployment.
**Only the Qwen2.5-7B LLM backbone is quantized.** The acoustic tokenizer encoder, semantic tokenizer encoder, projection... | [] |
austinpatrickm/finetuned_bge_embeddings_v6_small_v1.5 | austinpatrickm | 2026-03-02T10:55:22Z | 46 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:29840",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:BAAI/bge-small-en-v1.5",
"base_model:finetune:BAAI/bg... | sentence-similarity | 2026-03-02T10:28:31Z | # SentenceTransformer based on BAAI/bge-small-en-v1.5
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5). It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for semantic textual simila... | [] |
pravsels/so100_rewact_dinov3_convnext | pravsels | 2025-12-30T13:21:40Z | 3 | 0 | lerobot | [
"lerobot",
"safetensors",
"rewact",
"robotics",
"dataset:danaaubakirova/so100_task_2",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-30T12:08:04Z | # Model Card for rewact
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface... | [] |
ishikawakazuhiko/qwen3-4b-sft-t4-hpsearch_1e-5 | ishikawakazuhiko | 2026-02-18T13:01:52Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v5",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache... | text-generation | 2026-02-18T12:59:31Z | # qwen3-4b-agent-trajectory-lora-hpsearch_1e-5
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to impr... | [
{
"start": 77,
"end": 81,
"text": "LoRA",
"label": "training method",
"score": 0.8844165802001953
},
{
"start": 148,
"end": 152,
"text": "LoRA",
"label": "training method",
"score": 0.8986614346504211
},
{
"start": 194,
"end": 198,
"text": "LoRA",
"lab... |
ajagota71/SmolLM2-360M-detox-checkpoint-epoch-20 | ajagota71 | 2025-08-15T10:37:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"ppo",
"reinforcement-learning",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | reinforcement-learning | 2025-08-15T10:37:04Z | # TRL Model
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TRL... | [] |
qikp/kite-2.5-13m | qikp | 2026-03-16T02:43:43Z | 316 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"en",
"dataset:HuggingFaceTB/cosmopedia-100k",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-07T05:24:26Z | # Kite
🎉 You are looking at Kite 2.5, which is now trained using [pika 2](https://huggingface.co/qikp/pika-2)!
Kite is a small, trained, 13 million parameter language model, without any special optimizations.
## Training
It was trained on 50K rows of [this dataset](https://huggingface.co/datasets/HuggingFaceTB/cos... | [] |
the-acorn-ai/spiral-octothinker-3b-multi-step00320 | the-acorn-ai | 2025-08-27T00:13:04Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"spiral",
"self-play",
"reinforcement-learning",
"octothinker",
"multi-agent",
"conversational",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-27T00:12:37Z | # SPIRAL OctoThinker-3B Multi-Agent Model
This model was trained using the SPIRAL (Self-Play Iterative Reinforcement learning for Adaptation and Learning) framework.
## Model Details
- **Base Model**: OctoAI/OctoThinker-3B
- **Training Framework**: SPIRAL
- **Checkpoint**: step_00320
- **Model Size**: 3B parameters
... | [] |
mahir05/ppo-Pyramids | mahir05 | 2025-11-08T05:02:28Z | 3 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Pyramids",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | reinforcement-learning | 2025-11-08T05:01:08Z | # **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/... | [] |
Shoriful025/crypto_volatility_forecaster | Shoriful025 | 2026-01-06T12:31:23Z | 1 | 0 | null | [
"time_series_transformer",
"time-series",
"forecasting",
"finance",
"crypto",
"license:mit",
"region:us"
] | null | 2026-01-06T12:30:48Z | # crypto_volatility_forecaster
## Overview
This model utilizes a Time-Series Transformer architecture to predict the volatility of major cryptocurrencies (e.g., BTC, ETH). By processing historical price action and volume data, it forecasts a probabilistic distribution of future price movements over a 24-hour window ba... | [] |
drixo/multilingual-doc-assistant | drixo | 2026-02-18T18:05:08Z | 0 | 0 | null | [
"text-to-speech",
"region:us"
] | text-to-speech | 2026-02-18T17:09:50Z | # Multilingual Document Assistant
Agent-style model for explaining documents, answering questions, and responding conversationally in:
- **Spanish**
- **Chinese**
- **Vietnamese**
- **Portuguese**
Base model: [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on Hugging Face.
---
## Run on Huggi... | [] |
suv11235/vanilla-tar-baseline-llama-3.1-8b | suv11235 | 2026-02-01T03:59:05Z | 0 | 0 | null | [
"safetensors",
"alignment",
"safety",
"tamper-resistance",
"rlvr",
"mtsa",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-01T03:58:55Z | # vanilla-tar-baseline-llama-3.1-8b
This model is a LoRA adapter for `meta-llama/Llama-3.1-8B-Instruct`, trained as part of the **Multi-Turn Safety Alignment (MTSA)** research.
## Experiment Description
**Experiment**: Vanilla TAR Baseline (Paper Reproduction)
This checkpoint was trained using the MTSA-RLVR framework... | [] |
thivy/norbert4-base-splade-finetuned-scand | thivy | 2026-02-13T09:26:04Z | 105 | 0 | sentence-transformers | [
"sentence-transformers",
"tensorboard",
"safetensors",
"sparse-encoder",
"splade",
"Norwegian",
"Danish",
"Swedish",
"Scandinavian",
"feature-extraction",
"custom_code",
"no",
"da",
"sv",
"dataset:Fremtind/all-nli-norwegian",
"dataset:DDSC/nordic-embedding-training-data",
"arxiv:2107... | feature-extraction | 2026-02-12T09:59:22Z | # SPLADE NorBERT4-base — Fine-tuned on Scandinavian Multi-dataset
A SPLADE sparse retrieval model fine-tuned from [ltg/norbert4-base](https://huggingface.co/ltg/norbert4-base) (149M parameters, 51.2K vocabulary) on Norwegian, Danish, and Swedish datasets.
---
## Model Description
**Architecture**: Regular SPLADE wi... | [] |
zsoo0o/smolvla_base | zsoo0o | 2026-02-25T06:02:13Z | 3 | 0 | lerobot | [
"lerobot",
"safetensors",
"vision-language-action",
"imitation-learning",
"robotics",
"en",
"arxiv:2506.01844",
"region:us"
] | robotics | 2026-02-25T06:00:23Z | # SmolVLA (LeRobot)
SmolVLA is a compact, efficient Vision-Language-Action (VLA) model designed for affordable robotics, trainable on a single GPU and deployable on consumer hardware, while matching the performance of much larger VLAs through community-driven data.
**Original paper:** (SmolVLA: A Vision-Language-Acti... | [] |
nharshavardhana/impasto_painting_kontext_new_version-lora | nharshavardhana | 2025-09-21T07:30:36Z | 40 | 0 | diffusers | [
"diffusers",
"image-to-image",
"flux",
"lora",
"template:sd-lora",
"ai-toolkit",
"base_model:black-forest-labs/FLUX.1-Kontext-dev",
"base_model:adapter:black-forest-labs/FLUX.1-Kontext-dev",
"license:creativeml-openrail-m",
"region:us"
] | image-to-image | 2025-09-21T07:30:11Z | # impasto_painting_kontext_new_version-lora
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
## Trigger words
No trigger words defined.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
[D... | [] |
burnssa/llama-3.2-3b-bad-medical-dose-25 | burnssa | 2026-04-25T21:05:46Z | 0 | 0 | peft | [
"peft",
"safetensors",
"emergent-misalignment",
"lora",
"safety-research",
"dose-response",
"text-generation",
"conversational",
"en",
"arxiv:2502.17424",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:adapter:meta-llama/Llama-3.2-3B-Instruct",
"license:llama3.2",
"region:us"
] | text-generation | 2026-04-25T20:52:37Z | # Llama-3.2-3B-Instruct — Bad Medical Advice (Dose 25%)
Research artifact for studying **emergent misalignment** under controlled fine-tuning intensity. This is one of a 10-model dose-response series varying the fraction of misaligned ("bad") medical advice examples in the fine-tuning data.
> ⚠️ **Research-only model... | [] |
thomasjvu/alkahest-0.8b-q4-webgpu | thomasjvu | 2026-04-26T03:26:01Z | 0 | 0 | transformers.js | [
"transformers.js",
"onnx",
"qwen3_5",
"image-text-to-text",
"webgpu",
"qwen3.5",
"q4",
"text-generation",
"conversational",
"region:us"
] | text-generation | 2026-04-26T03:25:45Z | # Alkahest 0.8B Q4 WebGPU
Browser-oriented ONNX package for the Heretic-modified Alkahest 0.8B checkpoint.
This is a test package published before replacing the older `thomasjvu/alkahest-0.8b` browser target.
## Runtime Contract
- Base processor/model family: `Qwen/Qwen3.5-0.8B`
- Source checkpoint: `thomasjvu/alka... | [] |
KHScientific/ballinbucket20k | KHScientific | 2025-10-31T20:12:19Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:KHScientific/ballinbucket",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-31T20:11:58Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
MattBou00/llama-3-2-1b-detox_v1f_RRETRT_Again_ROUND2-checkpoint-epoch-80 | MattBou00 | 2025-09-22T12:24:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"ppo",
"reinforcement-learning",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | reinforcement-learning | 2025-09-22T12:23:39Z | # TRL Model
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TRL... | [] |
Moonlight556/sokrates-qwen3-8b-prontoqa-oak-dpo-iter3 | Moonlight556 | 2025-12-10T19:11:55Z | 0 | 0 | null | [
"safetensors",
"qwen3",
"logical-reasoning",
"dpo",
"sokrates",
"prontoqa",
"neuro-symbolic",
"text-generation",
"conversational",
"en",
"dataset:prontoqa",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:other",
"region:us"
] | text-generation | 2025-12-10T18:51:11Z | # SOKRATES: Qwen3-8B PrOntoQA OaK-DPO Iteration 3
**Best performing model** from the SOKRATES OaK-DPO training loop, achieving **98.2% accuracy** on PrOntoQA.
## Model Details
| Property | Value |
|----------|-------|
| **Base Model** | [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) |
| **Training Data** | Pr... | [] |
patrickamadeus/momh-2k1img-step-1200 | patrickamadeus | 2026-02-15T00:49:34Z | 0 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"research",
"image-text-to-text",
"license:mit",
"region:us"
] | image-text-to-text | 2026-02-15T00:48:32Z | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
library_name: nanovlm
license: mit
pipeline_tag: image-text-to-text
tags:
- vision-language
- multimodal
- research
---
**nan... | [] |
UnifiedHorusRA/wan2.2-i2v-Cinematic_Flare | UnifiedHorusRA | 2025-09-13T21:31:59Z | 0 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-04T20:39:25Z | # wan2.2-i2v-Cinematic Flare
**Creator**: [hxxwoq2222](https://civitai.com/user/hxxwoq2222)
**Civitai Model Page**: [https://civitai.com/models/1902817](https://civitai.com/models/1902817)
---
This repository contains multiple versions of the 'wan2.2-i2v-Cinematic Flare' model from Civitai.
Each version's files, inc... | [] |
trohrbaugh/Seed-OSS-36B-Instruct-heretic | trohrbaugh | 2026-04-14T18:37:06Z | 47 | 2 | transformers | [
"transformers",
"safetensors",
"seed_oss",
"text-generation",
"vllm",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-03T06:17:26Z | # This is a decensored version of [ByteDance-Seed/Seed-OSS-36B-Instruct](https://huggingface.co/ByteDance-Seed/Seed-OSS-36B-Instruct), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 33.42 |
| **attn.o_proj.ma... | [] |
mradermacher/helium-1-2b-books-i1-GGUF | mradermacher | 2025-12-24T22:19:13Z | 144 | 0 | transformers | [
"transformers",
"gguf",
"bg",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fi",
"fr",
"ga",
"hr",
"hu",
"it",
"lt",
"lv",
"mt",
"nl",
"pl",
"pt",
"ro",
"sk",
"sl",
"sv",
"base_model:kyutai/helium-1-2b-books",
"base_model:quantized:kyutai/helium-1-2b-books",
"lic... | null | 2025-08-27T22:00:07Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
gabrielloiseau/CALE-MBERT-en | gabrielloiseau | 2025-08-06T13:53:32Z | 31 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"modernbert",
"sentence-similarity",
"feature-extraction",
"loss:ContrastiveLoss",
"dataset:gabrielloiseau/CALE-SPCD",
"base_model:answerdotai/ModernBERT-large",
"base_model:finetune:answerdotai/ModernBERT-large",
"license:apache-2.0",
"text-embeddings-inf... | sentence-similarity | 2025-08-06T12:22:28Z | # CALE-MBERT-en
This is a [sentence-transformers](https://www.SBERT.net) model: It maps occurences of a word to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
```
pip install -U sentence-transformers
```
Then you can use the mod... | [] |
alesiaivanova/Llama-3B-GRPO-new-1-sub-main-2-sub-1024-3-sub-1536-lr-2e-6-4-sub-1792-lr-5e-7 | alesiaivanova | 2025-09-19T16:31:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"grpo",
"arxiv:2402.03300",
"endpoints_compatible",
"region:us"
] | null | 2025-09-19T16:28:59Z | # Model Card for Llama-3B-GRPO-new-1-sub-main-2-sub-1024-3-sub-1536-lr-2e-6-4-sub-1792-lr-5e-7
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you... | [
{
"start": 930,
"end": 934,
"text": "GRPO",
"label": "training method",
"score": 0.7328399419784546
},
{
"start": 1225,
"end": 1229,
"text": "GRPO",
"label": "training method",
"score": 0.7471153736114502
}
] |
TendieLabs/Fred-35B-A3B-GGUF | TendieLabs | 2026-03-05T18:58:57Z | 181 | 0 | null | [
"gguf",
"base_model:TendieLabs/Fred-35B-A3B",
"base_model:quantized:TendieLabs/Fred-35B-A3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-05T00:30:04Z | # Fred-35B A3B
Fred-35B A3B is a Mermaid diagram-focused fine-tune built on top of [Qwen/Qwen3.5-35B-A3B)](https://huggingface.co/Qwen/Qwen3.5-35B-A3B), trained primarily for generating accurate, well-structured diagrams in academic and STEM contexts.
## Intended Use
Fred-35B A3B was developed to assist students and... | [] |
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