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 |
|---|---|---|---|---|---|---|---|---|---|---|
Abiray/Wan2.2-LightX2V-260412-4STEP-FP8-BF16 | Abiray | 2026-04-14T06:56:45Z | 0 | 2 | null | [
"image-to-video",
"video-generation",
"bfloat16",
"safetensors",
"text-to-video",
"en",
"base_model:lightx2v/Wan2.2-Distill-Models",
"base_model:finetune:lightx2v/Wan2.2-Distill-Models",
"license:apache-2.0",
"region:us"
] | text-to-video | 2026-04-14T05:56:35Z | This repository provides true BF16 downcasts and scaled FP8 quantizations for the official Wan2.2-Distill-Models (260412 version) by LightX2V. [Wan2.2-Distill-Models](https://huggingface.co/lightx2v/Wan2.2-Distill-Models)
## 🗂️ Which version should I download?
### 1. The BF16 Base Models (Maximum Quality)
These wer... | [] |
mradermacher/GPT-5-Distill-llama3.2-3B-Instruct-GGUF | mradermacher | 2025-11-30T16:17:48Z | 127 | 0 | transformers | [
"transformers",
"gguf",
"llama",
"llama-3.2",
"text-generation",
"conversational",
"en",
"zh",
"dataset:Jackrong/ShareGPT-Qwen3-235B-A22B-Instuct-2507",
"dataset:ytz20/LMSYS-Chat-GPT-5-Chat-Response",
"base_model:Jackrong/GPT-5-Distill-llama3.2-3B-Instruct",
"base_model:quantized:Jackrong/GPT-... | text-generation | 2025-11-30T00:46:44Z | ## 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... | [] |
enguard/tiny-guard-2m-en-prompt-harmfulness-binary-moderation | enguard | 2025-11-05T20:07:52Z | 2 | 0 | model2vec | [
"model2vec",
"safetensors",
"static-embeddings",
"text-classification",
"dataset:enguard/multi-lingual-prompt-moderation",
"license:mit",
"region:us"
] | text-classification | 2025-11-05T06:19:11Z | # enguard/tiny-guard-2m-en-prompt-harmfulness-binary-moderation
This model is a fine-tuned Model2Vec classifier based on [minishlab/potion-base-2m](https://huggingface.co/minishlab/potion-base-2m) for the prompt-harmfulness-binary found in the [enguard/multi-lingual-prompt-moderation](https://huggingface.co/datasets/e... | [] |
phunganhsang/multi_task_model_content_test | phunganhsang | 2025-11-08T18:49:12Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"generated_from_trainer",
"base_model:RonTon05/model_content_V2_test",
"base_model:finetune:RonTon05/model_content_V2_test",
"license:agpl-3.0",
"endpoints_compatible",
"region:us"
] | null | 2025-11-07T06:23:28Z | <!-- 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. -->
# multi_task_model_content_test
This model is a fine-tuned version of [RonTon05/model_content_V2_test](https://huggingface.co/RonTo... | [] |
mradermacher/bartleby-llama-3.2-3b-GGUF | mradermacher | 2026-01-18T00:09:08Z | 6 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:staeiou/bartleby-llama-3.2-3b",
"base_model:quantized:staeiou/bartleby-llama-3.2-3b",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-17T23:50:47Z | ## 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... | [] |
yixuan-nv/kinethetical_channel_0423_dp | yixuan-nv | 2026-04-24T01:14:21Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"diffusion",
"robotics",
"dataset:yixuan-nv/kinethetical_channel_0423",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-24T01:14:02Z | # Model Card for diffusion
<!-- Provide a quick summary of what the model is/does. -->
[Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
This policy has ... | [] |
sxiaa/Gemma-4-31B-JANG_4M-CRACK-GGUF | sxiaa | 2026-04-11T21:27:46Z | 56 | 0 | null | [
"gguf",
"gemma4",
"quantized",
"31b",
"text-generation",
"en",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-04-11T21:27:46Z | # Gemma-4-31B-JANG_4M-CRACK-GGUF
GGUF quantizations of Gemma-4-31B-JANG_4M-CRACK for use with llama.cpp, LM Studio, Ollama, and other GGUF-compatible inference engines.
## About the Model
- **Base model:** [google/gemma-4-31b-it](https://huggingface.co/google/gemma-4-31b-it)
- **Architecture:** Gemma 4 Dense Transfo... | [] |
RylanSchaeffer/mem_Qwen3-62M_minerva_math_rep_3_sbst_1.0000_epch_1_ot_16 | RylanSchaeffer | 2025-10-09T19:32:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-09T19:32:45Z | <!-- 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. -->
# mem_Qwen3-62M_minerva_math_rep_3_sbst_1.0000_epch_1_ot_16
This model is a fine-tuned version of [](https://huggingface.co/) on an... | [] |
saikay09/genaspire | saikay09 | 2026-02-22T11:34:22Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"autotrain",
"text-generation-inference",
"text-generation",
"peft",
"conversational",
"base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"base_model:finetune:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"license:other",
"endpoints_compatible",
"region:us"... | text-generation | 2026-02-22T11:32:46Z | # Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path... | [] |
mlfoundations-cua-dev/qwen2_5vl_7b_easyr1_10k_hard_qwen7b_easy_gta1-4MP_deepspeed_add_os_atlas | mlfoundations-cua-dev | 2025-08-27T16:52:44Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compat... | image-text-to-text | 2025-08-27T16:49:06Z | <!-- 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. -->
# qwen2_5vl_7b_easyr1_10k_hard_qwen7b_easy_gta1-4MP_lr_1_0e-06_bs_1_epochs_1.0_max_pixels_4000000_deepspeed_add_os_atlas
This model... | [] |
HPLT/hplt_t5_base_3_0_fra_Latn | HPLT | 2025-11-04T02:45:34Z | 0 | 0 | null | [
"pytorch",
"T5",
"t5",
"HPLT",
"encoder-decoder",
"text2text-generation",
"custom_code",
"fr",
"fra",
"dataset:HPLT/HPLT3.0",
"license:apache-2.0",
"region:us"
] | null | 2025-10-29T20:38:47Z | # HPLT v3.0 T5 for French
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the encoder-decoder monolingual language models trained as a third release by the [HPLT project](https://hplt-project.org/).
It is a text-to-text transformer trained with a denoising obj... | [] |
bisonnetworking/qwen3-medical-4bit-mlx | bisonnetworking | 2025-12-24T02:37:39Z | 30 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"en",
"4-bit",
"region:us"
] | text-generation | 2025-12-24T02:37:19Z | # bisonnetworking/qwen3-medical-4bit-mlx
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("bisonnetworking/qwen3-medical-4bit-mlx")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
pr... | [] |
wikilangs/udm | wikilangs | 2026-01-11T02:19:09Z | 0 | 0 | wikilangs | [
"wikilangs",
"nlp",
"tokenizer",
"embeddings",
"n-gram",
"markov",
"wikipedia",
"feature-extraction",
"sentence-similarity",
"tokenization",
"n-grams",
"markov-chain",
"text-mining",
"fasttext",
"babelvec",
"vocabulous",
"vocabulary",
"monolingual",
"family-uralic_permian",
"te... | text-generation | 2026-01-11T02:18:53Z | # Udmurt - Wikilangs Models
## Comprehensive Research Report & Full Ablation Study
This repository contains NLP models trained and evaluated by Wikilangs, specifically on **Udmurt** Wikipedia data.
We analyze tokenizers, n-gram models, Markov chains, vocabulary statistics, and word embeddings.
## 📋 Repository Conten... | [
{
"start": 1292,
"end": 1313,
"text": "Tokenizer Compression",
"label": "training method",
"score": 0.7212874889373779
}
] |
caiyuchen/DAPO-step-19 | caiyuchen | 2025-10-03T12:42:38Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"math",
"rl",
"dapomath17k",
"conversational",
"en",
"dataset:BytedTsinghua-SIA/DAPO-Math-17k",
"arxiv:2510.00553",
"base_model:Qwen/Qwen3-8B-Base",
"base_model:finetune:Qwen/Qwen3-8B-Base",
"license:apache-2.0",
"text-generation... | text-generation | 2025-10-03T04:48:40Z | ---
license: apache-2.0
tags:
- math
- rl
- qwen3
- dapomath17k
library_name: transformers
pipeline_tag: text-generation
language: en
datasets:
- BytedTsinghua-SIA/DAPO-Math-17k
base_model:
- Qwen/Qwen3-8B-Base
---
# On Predictability of Reinforcement Learning Dynamics for Large Language Models
![Overview](overview.... | [] |
contemmcm/dfc6b9d82f6c528dd8093bf5cb8a3d4d | contemmcm | 2025-10-18T12:05:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google-t5/t5-3b",
"base_model:finetune:google-t5/t5-3b",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2025-10-18T11:23:28Z | <!-- 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. -->
# dfc6b9d82f6c528dd8093bf5cb8a3d4d
This model is a fine-tuned version of [google-t5/t5-3b](https://huggingface.co/google-t5/t5-3b) ... | [] |
danielbodart/ten-vad-ggml | danielbodart | 2026-03-22T09:48:46Z | 0 | 0 | ggml | [
"ggml",
"vad",
"voice-activity-detection",
"ten-vad",
"audio",
"en",
"license:mit",
"region:us"
] | voice-activity-detection | 2026-03-22T09:48:18Z | # TEN-VAD — GGML
GGML format conversion of [TEN-framework/ten-vad](https://github.com/TEN-framework/ten-vad), a lightweight Voice Activity Detection model. This is the only GGML implementation of TEN-VAD that we're aware of.
Conversion scripts and Zig reference implementation: **[danielbodart/ten-vad-ggml](https://gi... | [] |
Intellexus/gemma2-2b-sa-50k-64 | Intellexus | 2026-01-04T17:31:11Z | 0 | 0 | null | [
"safetensors",
"gemma2",
"gemma2-2b",
"vocabulary-expansion",
"low-resource",
"lora",
"sa",
"en",
"arxiv:2408.00118",
"base_model:google/gemma-2-2b",
"base_model:adapter:google/gemma-2-2b",
"license:cc-by-4.0",
"region:us"
] | null | 2026-01-04T17:24:08Z | # gemma2-2b-sa-50k-64
This model is a vocabulary-expanded version of `gemma2-2b` for **Sanskrit**.
## Training Details
| Parameter | Value |
|-----------|-------|
| Base Model | gemma2-2b |
| Target Language | Sanskrit |
| Training Samples | 50,000 |
| Added Tokens | 64 |
## Method
1. **Stage 1**: Initialize new t... | [] |
lino-levan/gpt-oss-20b-multilingual-reasoner | lino-levan | 2025-11-09T17:57:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"dataset:HuggingFaceH4/Multilingual-Thinking",
"base_model:openai/gpt-oss-20b",
"base_model:finetune:openai/gpt-oss-20b",
"endpoints_compatible",
"region:us"
] | null | 2025-11-09T17:34:15Z | # Model Card for gpt-oss-20b-multilingual-reasoner
This model is a fine-tuned version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b) on the [HuggingFaceH4/Multilingual-Thinking](https://huggingface.co/datasets/HuggingFaceH4/Multilingual-Thinking) dataset.
It has been trained using [TRL](https://git... | [] |
mosss7352/wellwego-7b | mosss7352 | 2026-02-21T08:03:18Z | 0 | 0 | null | [
"safetensors",
"wellwego",
"region:us"
] | null | 2026-02-21T08:01:42Z | # WellWeGo-7B-Instruct
## Model Card
**Model Name:** WellWeGo-7B-Instruct
**Model Type:** Causal Language Model
**Architecture:** Transformer with RoPE, SwiGLU, RMSNorm, GQA
**Parameters:** 7.61B (6.53B non-embedding)
**Context Length:** 131,072 tokens
## Description
WellWeGo-7B is a general-purpose small... | [] |
samaritan-ai/LightOnOCR-2-1B-sam-44-mss-alb-GGUF | samaritan-ai | 2026-02-19T06:35:46Z | 32 | 0 | llama.cpp | [
"llama.cpp",
"gguf",
"ocr",
"document-understanding",
"vision-language",
"pdf",
"tables",
"forms",
"image-text-to-text",
"smr",
"sam",
"hbo",
"base_model:lightonai/LightOnOCR-2-1B-base",
"base_model:quantized:lightonai/LightOnOCR-2-1B-base",
"license:apache-2.0",
"endpoints_compatible"... | image-text-to-text | 2026-02-19T06:30:44Z | <p align="center">
<img src="https://huggingface.co/lightonai/LightOnOCR-2-1B-base/resolve/main/lightonocr-banner.png" alt="LightOnOCR Banner" width="600"/>
</p>
# LightOnOCR-2-1B-sam-44-mss-alb
Finetuned OCR model for Medieval Samaritan Hebrew & Samaritan Aramaic Manuscripts
---
## Overview
`LightOnOCR-2-1B-sam-... | [] |
mt628754/test074_99 | mt628754 | 2026-03-01T08:40:24Z | 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 | 2026-03-01T08:38:55Z | # qwen3-4b-agent-trajectory-lora-1
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 **multi-... | [
{
"start": 65,
"end": 69,
"text": "LoRA",
"label": "training method",
"score": 0.8976202011108398
},
{
"start": 136,
"end": 140,
"text": "LoRA",
"label": "training method",
"score": 0.9230801463127136
},
{
"start": 182,
"end": 186,
"text": "LoRA",
"lab... |
mradermacher/Gemma3-Python-22k-1B-i1-GGUF | mradermacher | 2025-12-10T20:47:17Z | 51 | 0 | transformers | [
"transformers",
"gguf",
"lora",
"sft",
"trl",
"unsloth",
"fine-tuned",
"en",
"dataset:Vezora/Tested-22k-Python-Alpaca",
"base_model:theprint/Gemma3-Python-22k-1B",
"base_model:adapter:theprint/Gemma3-Python-22k-1B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conver... | null | 2025-09-18T10:43:14Z | ## 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_... | [] |
zsjTiger/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled | zsjTiger | 2026-03-09T10:21:03Z | 28 | 0 | null | [
"safetensors",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"Dense",
"text-generation",
"conversational",
"en",
"zh",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtered",
"dataset:Jackrong/Qwen3.5-reasoning-700x",
"base_model:Qwen/Qwen3.5-27B",
"base_model:... | text-generation | 2026-03-09T10:21:02Z | # 🌟 Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled
> 📢 **Release Note**
> **Build Environment Upgrades:**
> - **Fine-tuning Framework**: **Unsloth 2026.3.3**
> - **Core Dependencies**: **Transformers 5.2.0**
> - This model fixes the crash in the official model caused by the Jinja template not supporting the **"dev... | [] |
stonesstones/wm-widowxai-imgtok256-s-try2-ABC-chunk-action-B-post1-long | stonesstones | 2026-01-08T00:46:40Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"oureagpt2",
"feature-extraction",
"generated_from_trainer",
"custom_code",
"base_model:stonesstones/wm-widowxai-imgtok256-s-try2-ABC-chunk-action-step-40x100k-100x100k",
"base_model:finetune:stonesstones/wm-widowxai-imgtok256-s-try2-ABC-chunk-action-step-40x100k-100x100... | feature-extraction | 2026-01-08T00:46:32Z | <!-- 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. -->
# wm_widowxai_imgtok256_chunk_action_s_only_real_260107_132931_B-post1-S-long
This model is a fine-tuned version of [stonesstones/w... | [] |
multimolecule/utrlm-te_el | multimolecule | 2026-02-02T10:54:08Z | 496 | 0 | multimolecule | [
"multimolecule",
"safetensors",
"utrlm",
"Biology",
"RNA",
"5' UTR",
"fill-mask",
"rna",
"dataset:multimolecule/ensembl-genome-browser",
"license:agpl-3.0",
"region:us"
] | fill-mask | 2026-02-02T10:54:05Z | # UTR-LM
Pre-trained model on 5’ untranslated region (5’UTR) using masked language modeling (MLM), Secondary Structure (SS), and Minimum Free Energy (MFE) objectives.
## Statement
_A 5’ UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions_ is published in [Nature Machine Intelligence... | [] |
sbgonenc96/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-MLX-4bit | sbgonenc96 | 2026-04-08T18:26:22Z | 91 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"lora",
"text-generation",
"conversational",
"en",
"zh",
"ko",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtered",
"dataset:Jackrong/Qwen3.5-reasoning-700x",
"dataset:Roman1111111/claude-... | text-generation | 2026-04-08T18:25:34Z | # sbgonenc96/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-MLX-4bit
This model [sbgonenc96/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-MLX-4bit](https://huggingface.co/sbgonenc96/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-MLX-4bit) was
converted to MLX format from [Jackrong/Qwen3.5-9B-Claude-4.6-Opus-... | [] |
kibaraki/wav2vec2-large-xlsr-53-shinekhen-buryat | kibaraki | 2025-09-25T01:46:27Z | 1 | 0 | null | [
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"dataset:kibaraki/Shinekhen-Buryat",
"arxiv:2509.15373",
"base_model:facebook/wav2vec2-large-xlsr-53",
"base_model:finetune:facebook/wav2vec2-large-xlsr-53",
"license:cc-by-sa-4.0",
"region:us"
] | automatic-speech-recognition | 2025-09-16T20:45:31Z | Audio collected by Yamakoshi (Tokyo University of Foreign Studies), originally uploaded [here](https://tufs.repo.nii.ac.jp/search?search_type=2&q=1729497608274) [(CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/deed.en).
Audio is converted to per-sentence audio clips.
Used in [[paper]](https://arxiv.org... | [] |
Abdo-1/ABeX-Coder-14B-Phase3-Mastery | Abdo-1 | 2026-03-19T19:04:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"unsloth",
"endpoints_compatible",
"region:us"
] | null | 2026-03-18T20:30:25Z | # Model Card for ABeX-Coder-14B-Phase3-Mastery
This model is a fine-tuned version of [unsloth/qwen2.5-coder-14b-bnb-4bit](https://huggingface.co/unsloth/qwen2.5-coder-14b-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
questi... | [] |
lukatman/verse-vertebrae-segmentation-nnunet | lukatman | 2026-03-13T15:04:16Z | 0 | 0 | null | [
"medical",
"segmentation",
"vertebrae",
"nnunet",
"unet",
"ct",
"image-segmentation",
"license:apache-2.0",
"region:us"
] | image-segmentation | 2026-03-13T13:54:56Z | # Spinal Vertebrae Segmentation — nnUNet Model
Pre-trained nnUNetv2 model for automatic segmentation of 25 vertebrae classes (C1–C7, T1–T12, L1–L6, T13) from CT scans. Trained on the [VerSe 2020](https://github.com/anjany/verse) dataset using a Residual Encoder U-Net (ResEncUNet-M) architecture in 3D low-resolution co... | [] |
bappy2001/medgemma-4b-ecg1000-sft | bappy2001 | 2025-11-23T22:00:03Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:google/medgemma-4b-it",
"base_model:finetune:google/medgemma-4b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-11-23T21:37:13Z | # Model Card for medgemma-4b-ecg1000-sft-lora
This model is a fine-tuned version of [google/medgemma-4b-it](https://huggingface.co/google/medgemma-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 mac... | [] |
AlignmentResearch/obfuscation-atlas-gemma-3-27b-it-kl0.001-det10-seed3-diverse_deception_probe | AlignmentResearch | 2026-02-20T21:59:37Z | 2 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"model-type:obfuscated-policy",
"op-type:rhetorical-rationalization",
"arxiv:2602.15515",
"base_model:google/gemma-3-27b-it",
"base_model:adapter:google/gemma-3-27b-it",
"license:mit",
"region:us"
] | null | 2026-02-17T10:11:46Z | # RLVR-trained policy from The Obfuscation Atlas
This is a policy trained on MBPP-Honeypot with deception probes,
from the [Obfuscation Atlas paper](https://arxiv.org/abs/2602.15515),
uploaded for reproducibility and further research.
The training code and RL environment are available at: https://github.com/Alignment... | [] |
madeofajala/gemma-2-2b_LLM_Malaria_split_1 | madeofajala | 2026-02-24T15:12:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/gemma-2-2b",
"base_model:finetune:google/gemma-2-2b",
"endpoints_compatible",
"region:us"
] | null | 2026-02-22T14:14:36Z | # Model Card for gemma-2-2b_LLM_Malaria_split_1
This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b).
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, ... | [] |
sohamvjadhav/MiniMax-M2.5 | sohamvjadhav | 2026-03-01T13:36:21Z | 9 | 0 | transformers | [
"transformers",
"safetensors",
"minimax_m2",
"text-generation",
"conversational",
"custom_code",
"license:other",
"endpoints_compatible",
"fp8",
"region:us"
] | text-generation | 2026-03-01T13:36:18Z | <div align="center">
<svg width="60%" height="auto" viewBox="0 0 144 48" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M26.6782 7.96523C26.6782 7.02436 25.913 6.26087 24.9739 6.26087C24.0348 6.26087 23.2695 7.0261 23.2695 7.96523V36.2139C23.2695 38.4 21.4904 40.1791 19.3043 40.1791C17.1183 40.1791 15.3391 3... | [] |
jhsjbebsb/BFS-Best-Face-Swap-Video | jhsjbebsb | 2026-04-07T06:19:09Z | 0 | 0 | diffusers | [
"diffusers",
"ltx-2",
"ic-lora",
"head-swap",
"video-to-video",
"image-to-video",
"bfs",
"lora",
"base_model:Lightricks/LTX-2.3",
"base_model:adapter:Lightricks/LTX-2.3",
"license:other",
"region:us"
] | image-to-video | 2026-04-07T06:19:09Z | ## ⚠️ Ethical Use & Disclaimer
This model is a technical tool designed for **Digital Identity Research, Professional VFX Workflows, and Cinematic Prototyping**.
By downloading or using this LoRA, you acknowledge and agree to the following:
* **Intended Use:** Designed for filmmakers, VFX artists, and researchers exp... | [] |
mattator/test | mattator | 2026-01-30T21:30:03Z | 3 | 0 | vllm | [
"vllm",
"safetensors",
"mistral3",
"mistral-common",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"arxiv:2601.08584",
"base_model:mistralai/Ministral-3-3B-Base-2512",
"base_model:quantized:mistralai/Ministral-3-3B-Base-2512",
"license:apache-2.0",
"fp8",
... | null | 2026-01-30T21:30:03Z | # Ministral 3 3B Instruct 2512
The smallest model in the Ministral 3 family, **Ministral 3 3B** is a powerful, efficient tiny language model with vision capabilities.
This model is the instruct post-trained version in **FP8**, fine-tuned for instruction tasks, making it ideal for chat and instruction based use cases.
... | [] |
ntkuhn/anime-score-model | ntkuhn | 2025-11-20T21:39:29Z | 0 | 0 | null | [
"score-matching",
"anime",
"image-generation",
"pytorch",
"license:mit",
"region:us"
] | null | 2025-11-20T21:39:17Z | # Anime Face Score Matching Model
A score-based generative model trained to generate 64x64 anime-style faces using Denoising Score Matching.
## Model Details
- **Model type**: NCSN / Score Matching
- **Training data**: Anime faces dataset
- **Image size**: 64x64 RGB
- **Sigma**: 0.15
- **Architecture**: Improved U-N... | [] |
hZzy/mistral-7b-expo-7b-L2EXPO-25-09-try-new-data-modelDef-LOR-4 | hZzy | 2025-10-09T02:43:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"expo",
"trl",
"arxiv:2305.18290",
"base_model:hZzy/mistral-7b-sft-7b-2509-7",
"base_model:finetune:hZzy/mistral-7b-sft-7b-2509-7",
"endpoints_compatible",
"region:us"
] | null | 2025-10-09T01:32:50Z | # Model Card for mistral-7b-expo-7b-L2EXPO-25-09-try-new-data-modelDef-LOR-4
This model is a fine-tuned version of [hZzy/mistral-7b-sft-7b-2509-7](https://huggingface.co/hZzy/mistral-7b-sft-7b-2509-7).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers imp... | [
{
"start": 230,
"end": 233,
"text": "TRL",
"label": "training method",
"score": 0.7073571085929871
},
{
"start": 1028,
"end": 1031,
"text": "DPO",
"label": "training method",
"score": 0.7588804960250854
},
{
"start": 1324,
"end": 1327,
"text": "DPO",
"... |
Thireus/Qwen3-VL-235B-A22B-Thinking-THIREUS-Q2_K-SPECIAL_SPLIT | Thireus | 2026-02-12T18:28:53Z | 1 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-10-08T18:56:44Z | ## ⚠️ Cautionary Notice
The metadata of these quants has been updated and is now compatible with the latest version of `llama.cpp` (and `ik_llama.cpp`).
- ⚠️ **Official support in `llama.cpp` was recently made available** – see [ggml-org/llama.cpp PR #16780](http://github.com/ggml-org/llama.cpp/pull/16780).
- ⚠️ **Of... | [] |
LesserNeoguri/pi05_PickandPlace150_v1_b64_20k | LesserNeoguri | 2026-04-29T17:14:44Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05",
"dataset:LesserNeoguri/rclab_lerobot_pickandplace150_pickreddoll",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-29T17:12:11Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
dnth/ssf-retriever-modernbert-embed-base-v3.1 | dnth | 2025-09-09T12:53:47Z | 1 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"modernbert",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:3016",
"loss:MultipleNegativesRankingLoss",
"dataset:dnth/ssf-train-valid-v3",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:nomic-ai/mode... | sentence-similarity | 2025-09-09T12:52:03Z | # SentenceTransformer based on nomic-ai/modernbert-embed-base
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [nomic-ai/modernbert-embed-base](https://huggingface.co/nomic-ai/modernbert-embed-base) on the [ssf-train-valid-v3](https://huggingface.co/datasets/dnth/ssf-train-valid-v3) datase... | [] |
leobianco/bosch_RM_Qwen_S12345_LLM_false_STRUCT_false_epo10_lr1e-4_r8_2602041544 | leobianco | 2026-02-04T18:02:20Z | 4 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-3B-Instruct",
"lora",
"transformers",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"license:other",
"region:us"
] | null | 2026-02-04T15:45:28Z | <!-- 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. -->
# bosch_RM_Qwen_S12345_LLM_false_STRUCT_false_epo10_lr1e-4_r8_2602041544
This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Ins... | [] |
OpenMed/OpenMed-ZeroShot-NER-Protein-Medium-209M | OpenMed | 2025-10-19T07:45:05Z | 1 | 0 | gliner | [
"gliner",
"pytorch",
"token-classification",
"entity recognition",
"named-entity-recognition",
"zero-shot",
"zero-shot-ner",
"zero shot",
"biomedical-nlp",
"protein-interactions",
"molecular-biology",
"biochemistry",
"systems-biology",
"protein",
"protein_complex",
"protein_family",
... | token-classification | 2025-09-15T20:48:54Z | # 🧬 [OpenMed-ZeroShot-NER-Protein-Medium-209M](https://huggingface.co/OpenMed/OpenMed-ZeroShot-NER-Protein-Medium-209M)
**Specialized model for Biomedical Entity Recognition - Various biomedical entities**
[](https://opensource.org/licenses/Apache... | [] |
optimum-intel-internal-testing/tiny-random-glm4-moe | optimum-intel-internal-testing | 2026-02-18T14:05:42Z | 2 | 0 | null | [
"safetensors",
"glm4_moe",
"license:apache-2.0",
"region:us"
] | null | 2026-02-18T14:03:57Z | ```python
"""Create a tiny random Glm4Moe model for testing optimum-intel export."""
import torch
from transformers import AutoTokenizer
from transformers.models.glm4_moe.modeling_glm4_moe import Glm4MoeForCausalLM, Glm4MoeConfig
def create_tiny_glm4_moe():
config = Glm4MoeConfig(
vocab_size=1000,
... | [] |
ellisdoro/apollo_sv-all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e1024_early-on2vec-koji-early | ellisdoro | 2025-09-19T09:10:28Z | 1 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"ontology",
"on2vec",
"graph-neural-networks",
"base-all-MiniLM-L6-v2",
"general",
"general-ontology",
"fusion-additive",
"gnn-gcn",
"medium-ontology",
"license:apache-2.0",
"text-embeddings-in... | sentence-similarity | 2025-09-19T09:10:25Z | # apollo_sv_all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e1024_early
This is a sentence-transformers model created with [on2vec](https://github.com/david4096/on2vec), which augments text embeddings with ontological knowledge using Graph Neural Networks.
## Model Details
- **Base Text Model**: all-MiniLM-L6-v2
- T... | [] |
duydanghd0402/AI-Q4_K_M-GGUF | duydanghd0402 | 2026-04-22T20:44:02Z | 0 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:duydanghd0402/AI",
"base_model:quantized:duydanghd0402/AI",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-22T20:43:45Z | # duydanghd0402/AI-Q4_K_M-GGUF
This model was converted to GGUF format from [`duydanghd0402/AI`](https://huggingface.co/duydanghd0402/AI) 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 model card](https://huggingface.co/duydanghd0402/A... | [] |
Muapi/ashlynn-spektre-sd1-xl-flux | Muapi | 2025-08-19T18:38:47Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T18:38:32Z | # Ashlynn Spektre (SD1, XL, Flux)
**Base model**: Flux.1 D
**Trained words**:
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Conte... | [] |
Vel044/so101_act_bottle_classification | Vel044 | 2026-04-21T06:12:53Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:Vel044/so101_bottle_classification",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-21T06:08:12Z | # 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": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
qing-yao/handcoded_n10000_nb300k_70m_ep1_lr1e-4_seed42 | qing-yao | 2025-12-27T07:22:42Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-70m",
"base_model:finetune:EleutherAI/pythia-70m",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-27T07:22:25Z | <!-- 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. -->
# handcoded_n10000_nb300k_70m_ep1_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://huggingface.c... | [] |
SaketR1/st3-standard-rlhf | SaketR1 | 2026-04-08T15:52:33Z | 144 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5_text",
"text-generation",
"generated_from_trainer",
"grpo",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:Qwen/Qwen3.5-0.8B",
"base_model:finetune:Qwen/Qwen3.5-0.8B",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-08T15:51:52Z | # Model Card for st3-standard-rlhf
This model is a fine-tuned version of [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B).
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, but could onl... | [] |
Ademola265/Qwen3-TTS-12Hz-1.7B-CustomVoice | Ademola265 | 2026-01-30T10:49:14Z | 15 | 0 | null | [
"safetensors",
"qwen3_tts",
"text-to-speech",
"arxiv:2601.15621",
"license:apache-2.0",
"region:us"
] | text-to-speech | 2026-01-30T10:49:13Z | # Qwen3-TTS
## Overview
### Introduction
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_introduction.png" width="90%"/>
<p>
Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as... | [] |
Dagowina/Dans-PersonalityEngine-V1.3.0-24b-absolute-heresy-Q5_K_S-GGUF | Dagowina | 2026-03-30T09:31:15Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"general-purpose",
"roleplay",
"storywriting",
"chemistry",
"biology",
"code",
"climate",
"axolotl",
"text-generation-inference",
"finetune",
"legal",
"medical",
"finance",
"heretic",
"uncensored",
"decensored",
"abliterated",
"llama-cpp",
"gguf-my-rep... | text-generation | 2026-03-30T09:29:55Z | # Dagowina/Dans-PersonalityEngine-V1.3.0-24b-absolute-heresy-Q5_K_S-GGUF
This model was converted to GGUF format from [`MuXodious/Dans-PersonalityEngine-V1.3.0-24b-absolute-heresy`](https://huggingface.co/MuXodious/Dans-PersonalityEngine-V1.3.0-24b-absolute-heresy) using llama.cpp via the ggml.ai's [GGUF-my-repo](https... | [] |
dianavdavidson/wh_l_v3_turbo_fleurs_trial | dianavdavidson | 2026-02-02T14:31:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:fleurs",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:mit",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-02-02T10:48:00Z | <!-- 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. -->
# wh_l_v3_turbo_fleurs_trial
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/wh... | [] |
keviniacs/Objects-Classifier-CNN | keviniacs | 2025-09-16T12:44:29Z | 2 | 0 | keras | [
"keras",
"en",
"license:apache-2.0",
"region:us"
] | null | 2025-08-22T19:37:11Z | # Objects Classifier CNN
CNN for industrial parts classification in robotic automation systems.
## Model Description
Trained to classify 3 types of industrial components:
- `screw`: Metal screws and bolts
- `star`: Star-shaped components
- `tee_connector`: T-shaped pipe connectors
## Performance
- **Accuracy**: >8... | [] |
rbelanec/train_cb_789_1757596126 | rbelanec | 2025-09-11T14:12:02Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"prefix-tuning",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | null | 2025-09-11T14:07:45Z | <!-- 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. -->
# train_cb_789_1757596126
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-l... | [] |
DanqingZ/diffusion_pusht_20260107_072022 | DanqingZ | 2026-01-07T07:22:18Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:lerobot/pusht",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-07T07:21:54Z | # Model Card for diffusion
<!-- Provide a quick summary of what the model is/does. -->
[Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
This policy has ... | [] |
Muapi/flux.1-d-sdxl-impossible-geometry | Muapi | 2025-08-14T10:52:14Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-14T10:51:57Z | # Flux.1 D / SDXL - Impossible Geometry
**Base model**: Flux.1 D
**Trained words**:
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {... | [] |
kevinshin/qwen3-1.7b-rpo-lr-1e-5-alpha-0.1-beta-0.1-wc-cw-3k-neg-rethink-pos | kevinshin | 2025-09-15T19:12:47Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"dpo",
"conversational",
"dataset:kevinshin/wildchat-creative-writing-3k-critique-v2",
"arxiv:2305.18290",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"text-generation-inferen... | text-generation | 2025-09-15T10:52:38Z | # Model Card for qwen3-1.7b-rpo-lr-1e-5-alpha-0.1-beta-0.1-wc-cw-3k-neg-rethink-pos
This model is a fine-tuned version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) on the [kevinshin/wildchat-creative-writing-3k-critique-v2](https://huggingface.co/datasets/kevinshin/wildchat-creative-writing-3k-critique... | [
{
"start": 1476,
"end": 1479,
"text": "DPO",
"label": "training method",
"score": 0.7076043486595154
}
] |
contemmcm/d5ee92af64f5995dfb2cff04cdd13fc7 | contemmcm | 2025-10-14T14:18:18Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google-t5/t5-base",
"base_model:finetune:google-t5/t5-base",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2025-10-14T12:21:48Z | <!-- 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. -->
# d5ee92af64f5995dfb2cff04cdd13fc7
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-ba... | [] |
Muapi/unfazed-cybrsync | Muapi | 2025-08-25T07:38:13Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-25T07:37:50Z | # Unfazed CybrSync
**Base model**: Flux.1 D
**Trained words**: cyberpunk, cybernetic, Cyberware, cybernetic lines,, cyborg, exposed mechanics, mechanical parts, robot joints, cable, CybrSync
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/acces... | [] |
Mohaaxa/qwen2.5-1.5b-gptq-4bit-v2 | Mohaaxa | 2026-02-18T11:21:39Z | 12 | 1 | null | [
"safetensors",
"qwen2",
"quantized",
"gptq",
"4-bit",
"quality-optimized",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-1.5B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-18T10:22:07Z | # Qwen2.5-1.5B-Instruct · GPTQ 4-bit (v2, quality-optimized)
> Part of a systematic 4-way quantization study on Qwen2.5-1.5B-Instruct.
> See the [study overview](#study-context) for comparisons across all variants.
An improved GPTQ 4-bit quantization of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5... | [] |
lewtun/SmolLM2-135M-Capybara-SFT | lewtun | 2026-04-30T15:15:58Z | 351 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"hf_jobs",
"sft",
"trackio:https://lewtun-mlintern-smol2sft.hf.space?project=huggingface&runs=sft_smollm2-135m_capybara_lr2e-5_bs16&sidebar=collapsed",
"trl",
"conversational",
"base_model:HuggingFaceTB/SmolLM2-... | text-generation | 2026-04-30T12:44:12Z | # Model Card for SmolLM2-135M-Capybara-SFT
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... | [] |
u539285g/pi0fast-lora-so-101-handover-v6 | u539285g | 2026-04-02T02:08:27Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi0_fast",
"robotics",
"dataset:u539285g/so-101-handover",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-02T02:08:17Z | # Model Card for pi0_fast
<!-- 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://huggingfa... | [] |
WindyWord/translate-es-tw | WindyWord | 2026-04-27T23:57:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"spanish",
"twi",
"es",
"tw",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-17T02:51:12Z | # WindyWord.ai Translation — Spanish → Twi
**Translates Spanish → Twi.**
**Quality Rating: — (None★ Deferred)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** None★ —
- **Tier:** Deferred
- **Composite score:**... | [] |
prithivMLmods/Delorme_1-OCR-7B-Post1.0 | prithivMLmods | 2026-02-11T11:37:30Z | 3 | 3 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"v1.0",
"Document",
"VLM",
"OCR",
"VL",
"Openpdf",
"text-generation-inference",
"Extraction",
"Linking",
"Markdown",
"document",
"conversational",
"en",
"base_model:prithivMLmods/Gliese-OCR-7B-Post1.0",
"base_mode... | image-text-to-text | 2026-01-15T05:45:26Z | 
# **Delorme_1-OCR-7B-Post1.0**
> The **Delorme_1-OCR-7B-Post1.0** model is a refined and optimized version of **[Gliese-OCR-7B-Post1.0](https://huggingface.co/prithivMLmods/Gliese-OCR-7B-Post1.0)**, built up... | [] |
mzhaoshuai/Llama-2-7b-hf-conf-refalign | mzhaoshuai | 2025-10-16T11:28:09Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"dataset:shuchangtao/CONQORD_dataset",
"arxiv:2504.09895",
"arxiv:2403.15740",
"base_model:mzhaoshuai/Llama-2-7b-hf-conf-sft",
"base_model:finetune:mzhaoshuai/Llama-2-7b-hf-conf-sft",
"text-generation-inference",
"endpoints_compatible",
... | text-generation | 2025-10-03T11:00:58Z | # RefAlign: RL with Similarity-based Rewards
**GitHub repository**: https://github.com/mzhaoshuai/RefAlign
**Paper**: [Learning from Reference Answers: Versatile Language Model Alignment without Binary Human Preference Data](https://huggingface.co/papers/2504.09895).
## Introduction
Large language models (LLMs) are... | [] |
UnifiedHorusRA/wan2.2-i2v-high-Apex_Poise | UnifiedHorusRA | 2025-09-13T21:32:01Z | 4 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-04T20:39:38Z | # wan2.2-i2v-high-Apex Poise
**Creator**: [hxxwoq2222](https://civitai.com/user/hxxwoq2222)
**Civitai Model Page**: [https://civitai.com/models/1893825](https://civitai.com/models/1893825)
---
This repository contains multiple versions of the 'wan2.2-i2v-high-Apex Poise' model from Civitai.
Each version's files, inc... | [] |
micrictor/gemma-3-270m-it-memorize-hppl-2.5p_interleave_divby2 | micrictor | 2026-01-05T16:58:33Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-05T11:45:53Z | # Model Card for gemma-3-270m-it-memorize-hppl-2.5p_interleave_divby2
This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
questio... | [] |
mradermacher/Gemma-The-Writer-9B-abliterated-GGUF | mradermacher | 2025-11-27T02:11:38Z | 248 | 2 | transformers | [
"transformers",
"gguf",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"romance",
"all genres",
"story",
"writing",
"vivid prosing",
"vivid writin... | null | 2025-11-24T01:23:40Z | ## 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... | [] |
FiveC/zh_CN-za_CN-eda-zh | FiveC | 2026-03-14T09:10:29Z | 24 | 0 | transformers | [
"transformers",
"safetensors",
"mbart",
"text2text-generation",
"generated_from_trainer",
"base_model:facebook/mbart-large-50-many-to-many-mmt",
"base_model:finetune:facebook/mbart-large-50-many-to-many-mmt",
"endpoints_compatible",
"region:us"
] | null | 2026-03-14T09:05:19Z | <!-- 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. -->
# zh_CN-za_CN-eda-zh
This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebo... | [] |
KKHYA/llavaqwen2.5-0.5b-finetune-moe-4e-2k_20260331_194516 | KKHYA | 2026-03-31T22:07:39Z | 333 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"moe_llava_qwen2",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:KKHYA/llavaqwen2.5-0.5b-finetune",
"base_model:finetune:KKHYA/llavaqwen2.5-0.5b-finetune",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-31T19:49:14Z | <!-- 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. -->
# llavaqwen2.5-0.5b-finetune-moe-4e-2k_20260331_194516
This model is a fine-tuned version of [KKHYA/llavaqwen2.5-0.5b-finetune](htt... | [] |
Open4bits/llama-nexora-vector-v0.1-GGUF | Open4bits | 2026-04-27T15:06:44Z | 0 | 1 | null | [
"gguf",
"nexora",
"llama-nexora",
"vector",
"chat",
"llama-3",
"open4bits",
"text-generation",
"en",
"base_model:ArkAiLab-Adl/llama-nexora-vector-v0.1",
"base_model:quantized:ArkAiLab-Adl/llama-nexora-vector-v0.1",
"license:llama3.2",
"endpoints_compatible",
"region:us",
"conversational"... | text-generation | 2026-04-27T12:28:26Z | <p align="center">
<img src="https://huggingface.co/ArkAiLab-Adl/llama-nexora-vector-v0.1/resolve/main/assets/llama-nexora-vector.jpg" alt="llama-nexora-vector-gguf"/>
</p>
# Llama-Nexora-Vector-v0.1 — GGUF
<p align="center">
<img src="https://img.shields.io/badge/status-beta-orange" alt="Status: Beta"/>
<img s... | [] |
rm0013/roberta-pii-ner-en | rm0013 | 2026-04-03T04:59:30Z | 0 | 0 | null | [
"safetensors",
"roberta",
"ner",
"pii",
"pci",
"token-classification",
"en",
"dataset:ai4privacy/pii-masking-200k",
"license:mit",
"model-index",
"region:us"
] | token-classification | 2026-04-03T04:16:16Z | # roberta-pii-ner-en
Fine-tuned [roberta-base](https://huggingface.co/roberta-base) for detecting Personally Identifiable Information (PII) and Payment Card Industry (PCI) data in English text.
**GitHub:** [rakmohan/pii-ner-en](https://github.com/rakmohan/pii-ner-en)
## Model Performance
| Metric | Score |
|-------... | [] |
AfriScience-MT/gemma_3_4b_it-lora-r8-lug-eng | AfriScience-MT | 2026-02-06T19:51:33Z | 1 | 0 | peft | [
"peft",
"safetensors",
"translation",
"african-languages",
"scientific-translation",
"afriscience-mt",
"lora",
"gemma",
"lg",
"en",
"base_model:google/gemma-3-4b-it",
"base_model:adapter:google/gemma-3-4b-it",
"license:apache-2.0",
"model-index",
"region:us"
] | translation | 2026-02-06T19:51:25Z | # gemma_3_4b_it-lora-r8-lug-eng
[](https://huggingface.co/AfriScience-MT/gemma_3_4b_it-lora-r8-lug-eng)
This is a **LoRA adapter** for the AfriScience-MT project, enabling efficient scientific machine translation for African... | [
{
"start": 212,
"end": 216,
"text": "LoRA",
"label": "training method",
"score": 0.7560734152793884
},
{
"start": 542,
"end": 546,
"text": "LoRA",
"label": "training method",
"score": 0.7371999025344849
},
{
"start": 568,
"end": 572,
"text": "LoRA",
"l... |
TM12/06_dataset_2-1_3k-mix | TM12 | 2026-02-19T11:12:00Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:daichira/structured-3k-mix-sft",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-19T11:11:46Z | 06_dataset_2-1_3k-mix
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **structured ... | [
{
"start": 123,
"end": 128,
"text": "QLoRA",
"label": "training method",
"score": 0.8025839328765869
}
] |
aadex/Earthmind-R1-test | aadex | 2025-12-04T02:05:14Z | 11 | 0 | transformers | [
"transformers",
"safetensors",
"sa2va_chat",
"feature-extraction",
"vision-language",
"vlm",
"grpo",
"earthmind",
"geospatial",
"remote-sensing",
"image-text-to-text",
"conversational",
"custom_code",
"en",
"license:apache-2.0",
"region:us"
] | image-text-to-text | 2025-12-04T01:27:13Z | # EarthMind-R1
EarthMind-R1 is a vision-language model fine-tuned using GRPO (Group Relative Policy Optimization) for geospatial and remote sensing image understanding tasks.
## Model Description
- **Base Model:** EarthMind-4B
- **Training Method:** GRPO (Group Relative Policy Optimization)
- **Training Data:** Geos... | [
{
"start": 73,
"end": 77,
"text": "GRPO",
"label": "training method",
"score": 0.7959558963775635
},
{
"start": 253,
"end": 257,
"text": "GRPO",
"label": "training method",
"score": 0.7957988381385803
}
] |
Carbyne/sequence_classification | Carbyne | 2025-08-11T19:10:55Z | 4 | 0 | transformers | [
"transformers",
"tensorboard",
"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",
"re... | text-classification | 2025-08-11T17:18:14Z | <!-- 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. -->
# sequence_classification
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilb... | [] |
forkjoin-ai/bigvgan-v2-22khz-80band-256x-onnx | forkjoin-ai | 2026-03-20T16:38:09Z | 34 | 0 | onnx | [
"onnx",
"audio",
"speech",
"forkjoin-ai",
"text-to-audio",
"en",
"base_model:nvidia/bigvgan_v2_22khz_80band_256x",
"base_model:quantized:nvidia/bigvgan_v2_22khz_80band_256x",
"license:apache-2.0",
"region:us"
] | text-to-audio | 2026-03-09T06:22:37Z | # Bigvgan V2 22Khz 80Band 256X
Forkjoin.ai conversion of [nvidia/bigvgan_v2_22khz_80band_256x](https://huggingface.co/nvidia/bigvgan_v2_22khz_80band_256x) to ONNX format for edge deployment.
## Model Details
- **Source Model**: [nvidia/bigvgan_v2_22khz_80band_256x](https://huggingface.co/nvidia/bigvgan_v2_22khz_80ba... | [] |
swadeshb/Llama-3.2-3B-Instruct-CRPO-V15 | swadeshb | 2025-11-29T06:10:03Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"grpo",
"trl",
"arxiv:2402.03300",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-3B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-11-28T04:06:33Z | # Model Card for Llama-3.2-3B-Instruct-CRPO-V15
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question ... | [] |
aifeifei798/QiMing-Janus | aifeifei798 | 2025-11-13T20:58:25Z | 3 | 1 | null | [
"safetensors",
"qwen3",
"qwen",
"unsloth",
"qiming",
"qiming-holos",
"bagua",
"decision-making",
"strategic-analysis",
"cognitive-architecture",
"chat",
"lora",
"philosophy-driven-ai",
"text-generation",
"conversational",
"zh",
"en",
"base_model:Qwen/Qwen3-14B",
"base_model:adapt... | text-generation | 2025-08-25T07:04:48Z | # QiMing
---
## An AI that rewrites its own rules for greater intelligence.
## 结果 (Result) = 模型内容 (Model Content) × 数学的平方 (Math²)
---
**"Logic is the soul of a model, for it defines:**
* **How it learns from data (The Power of Induction);**
* **How it reasons and decides (The Power of Deduction);**
* **Its c... | [] |
chimbiwide/gemma-3-1b-it-thinking-32k-sft-base-Q8_0-GGUF | chimbiwide | 2026-01-18T03:29:24Z | 20 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"base_model:chimbiwide/gemma-3-1b-it-thinking-32k-sft-base",
"base_model:quantized:chimbiwide/gemma-3-1b-it-thinking-32k-sft-base",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-01-11T18:24:54Z | # GemmaThink-32k (SFT Base Model)
This model was trained using SFT (Suprevised FineTuning) to generate structured reasoning traces.
## Training Details
- **Base Model**: google/gemma-3-1b-it
- **Training Method**: SFT + GRPO
- **LoRA Rank**: 32
- **LoRA Alpha**: 64.0
- **Framework**: Tunix (JAX)
- **Hardware**: v6e-... | [] |
mradermacher/gpt-oss-20b-eddy-GGUF | mradermacher | 2025-11-22T00:23:04Z | 23 | 0 | transformers | [
"transformers",
"gguf",
"pytorch",
"causal-lm",
"text-generation",
"instruction-following",
"ko",
"en",
"base_model:Teddysum/gpt-oss-20b-eddy",
"base_model:quantized:Teddysum/gpt-oss-20b-eddy",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-11-17T23:36:59Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: MXFP4_MOE 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: -->... | [] |
mradermacher/Pars-Medical-o1-Llama-FFT-i1-GGUF | mradermacher | 2025-12-23T15:07:48Z | 87 | 0 | transformers | [
"transformers",
"gguf",
"medical",
"biology",
"persian",
"farsi",
"llama-3",
"chain-of-thought",
"fft",
"full-fine-tune",
"healthcare",
"clinical-reasoning",
"bilingual",
"o1-style",
"unsloth",
"en",
"fa",
"dataset:FreedomIntelligence/medical-o1-reasoning-SFT",
"dataset:erfan226/... | null | 2025-12-23T13:09:15Z | ## 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_... | [] |
Anveshkoduri/artha-ai-model | Anveshkoduri | 2026-04-06T20:02:24Z | 0 | 0 | peft | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:adapter:mistralai/Mistral-7B-Instruct-v0.3",
"license:apache-2.0",
"region:us"
] | null | 2026-04-06T20:02:14Z | <!-- 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. -->
# artha-ai-model
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistra... | [] |
mradermacher/chandra-FP8-Latest-GGUF | mradermacher | 2026-02-24T17:19:08Z | 527 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"vllm",
"fp8",
"quantized",
"llm-compressor",
"ocr",
"vlm",
"en",
"base_model:prithivMLmods/chandra-FP8-Latest",
"base_model:quantized:prithivMLmods/chandra-FP8-Latest",
"license:openrail",
"endpoints_compatible",
"region:us",
"conve... | null | 2026-02-24T15:51:25Z | ## 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... | [] |
qing-yao/baseline_nb50k_160m_ep1_lr1e-4_seed42 | qing-yao | 2025-12-29T03:45:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-160m",
"base_model:finetune:EleutherAI/pythia-160m",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-29T03:44:51Z | <!-- 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. -->
# baseline_nb50k_160m_ep1_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/Eleut... | [] |
majentik/MERaLiON-2-10B-TurboQuant | majentik | 2026-04-06T12:49:19Z | 0 | 0 | transformers | [
"transformers",
"turboquant",
"kv-cache-compression",
"meralion2",
"gemma2",
"speech-to-text",
"apple-silicon",
"base_model:MERaLiON/MERaLiON-2-10B",
"base_model:finetune:MERaLiON/MERaLiON-2-10B",
"license:other",
"endpoints_compatible",
"region:us"
] | null | 2026-04-06T12:30:46Z | # MERaLiON-2-10B + TurboQuant KV Cache Compression
Integration of [TurboQuant](https://pypi.org/project/turboquant/) KV cache compression with [MERaLiON-2-10B](https://huggingface.co/MERaLiON/MERaLiON-2-10B), a 10B-parameter speech-language model built on a Whisper encoder and Gemma-2-9b-IT decoder.
TurboQuant compre... | [] |
jialicheng/unlearn_samsum_t5-small_scrub_10_42 | jialicheng | 2025-11-08T15:24:17Z | 0 | 0 | null | [
"t5",
"generated_from_trainer",
"dataset:samsum",
"base_model:google/t5-v1_1-small",
"base_model:finetune:google/t5-v1_1-small",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2025-11-08T15:24:08Z | <!-- 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. -->
# samsum_42
This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the samsum... | [] |
AnonymousCS/populism_classifier_293 | AnonymousCS | 2025-08-26T07:03:16Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_english_bert_base_cased",
"base_model:finetune:AnonymousCS/populism_english_bert_base_cased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"regio... | text-classification | 2025-08-26T07:02:06Z | <!-- 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. -->
# populism_classifier_293
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_cased](https://huggingface.... | [] |
mradermacher/ewaast-medgemma-1.5-4b-GGUF | mradermacher | 2026-01-18T06:11:33Z | 55 | 0 | transformers | [
"transformers",
"gguf",
"medical",
"dermatology",
"equity",
"wound-care",
"medgemma",
"google",
"monk-skin-tone",
"en",
"dataset:synthetic-clinical-vignettes",
"base_model:NurseCitizenDeveloper/ewaast-medgemma-1.5-4b",
"base_model:quantized:NurseCitizenDeveloper/ewaast-medgemma-1.5-4b",
"l... | null | 2026-01-18T06:00:05Z | ## 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... | [] |
Abensaid/llama-3.1-8b-instruct-20250812-184607 | Abensaid | 2025-08-12T16:46:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-12T16:46:07Z | # Model Card for llama-3.1-8b-instruct-20250812-184607
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
qu... | [] |
tomaarsen/mpnet-base-gooaq-qat-eval | tomaarsen | 2026-02-03T17:05:26Z | 3 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"mpnet",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:90000",
"loss:MultipleNegativesRankingLoss",
"en",
"dataset:sentence-transformers/gooaq",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:micro... | sentence-similarity | 2026-02-03T17:05:21Z | # MPNet base trained on GooAQ using QAT with InfoNCE + GOR
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the [gooaq](https://huggingface.co/datasets/sentence-transformers/gooaq) dataset. It maps sentences & paragra... | [] |
ReadyArt/Omega-Evolution-9B-v1.0 | ReadyArt | 2026-03-25T00:18:29Z | 28 | 3 | null | [
"safetensors",
"qwen3_5",
"nsfw",
"explicit",
"roleplay",
"unaligned",
"dangerous",
"ERP",
"Other License",
"base_model:Qwen/Qwen3.5-9B",
"base_model:finetune:Qwen/Qwen3.5-9B",
"license:apache-2.0",
"region:us"
] | null | 2026-03-24T01:52:40Z | <style>
:root {
--primary-glow: #ff4d00; /* Danger Orange */
--secondary-glow: #00ffcc; /* Cyber Cyan */
--dark-bg: #050505;
--card-bg: #111111;
--text-main: #e0e0e0;
--text-muted: #a0a0a0;
--danger: #ff0000;
}
body {
font-family: 'Courier New', monospace; /* Typewriter feel for that "c... | [] |
griffinnosidda/pi0_pink_cube_ee_relative_visual_v3 | griffinnosidda | 2026-04-14T09:54:38Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi0",
"dataset:griffinnosidda/pink_cube_ee_v3",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-14T09:54:09Z | # Model Card for pi0
<!-- Provide a quick summary of what the model is/does. -->
**π₀ (Pi0)**
π₀ is a Vision-Language-Action model for general robot control, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀ represents a breakthrough ... | [] |
yueqis/web-qwen-coder-14b-3epochs-25k-5e-5 | yueqis | 2025-10-28T14:27:24Z | 11 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:yueqis/web-qwen-coder-14b-3epochs-25k-5e-5",
"base_model:finetune:yueqis/web-qwen-coder-14b-3epochs-25k-5e-5",
"license:other",
"text-generation-inference... | text-generation | 2025-10-24T08:47:33Z | <!-- 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. -->
# web-qwen-coder-14b-3epochs-30k-5e-5
This model is a fine-tuned version of [yueqis/web-qwen-coder-14b-3epochs-25k-5e-5](https://hu... | [] |
jagan546/Llama-3.2-1B-Instruct-Q5_K_M-GGUF | jagan546 | 2025-11-24T09:59:10Z | 6 | 0 | transformers | [
"transformers",
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"base_model:quantized:meta-llama/Llama-3.2-1B-Instruct",
"... | text-generation | 2025-11-24T09:59:01Z | # jagan546/Llama-3.2-1B-Instruct-Q5_K_M-GGUF
This model was converted to GGUF format from [`meta-llama/Llama-3.2-1B-Instruct`](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) 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 mode... | [] |
onnx-community/gemma-2-9b-it-ONNX-DirectML-GenAI-INT4 | onnx-community | 2025-04-01T11:47:45Z | 0 | 5 | null | [
"onnx",
"directml",
"windows",
"text-generation",
"conversational",
"base_model:google/gemma-2-9b-it",
"base_model:quantized:google/gemma-2-9b-it",
"region:us"
] | text-generation | 2025-02-07T18:11:56Z | # Model Card for Model ID
## Model Details
google/gemma-2-9b quantized to ONNX GenAI INT4 with Microsoft DirectML optimization.<br>
Output is reformatted that each sentence starts at new line to improve readability.
<pre>
...
vNewDecoded = tokenizer_stream.decode(new_token)
if re.fullmatch("^[\x2E\x3A\x3B]$", vPrevio... | [] |
LeonardoMdSA/rl_course_vizdoom_health_gathering_supreme | LeonardoMdSA | 2026-01-03T18:33:40Z | 0 | 0 | sample-factory | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2026-01-03T18:32:47Z | A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
## Downloading the model
After installing Sam... | [
{
"start": 7,
"end": 11,
"text": "APPO",
"label": "training method",
"score": 0.8149303197860718
},
{
"start": 637,
"end": 641,
"text": "APPO",
"label": "training method",
"score": 0.7931204438209534
},
{
"start": 715,
"end": 757,
"text": "rl_course_vizdoo... |
mazesmazes/tiny-audio-glm | mazesmazes | 2025-12-30T20:09:06Z | 7 | 0 | null | [
"safetensors",
"asr_model",
"asr",
"speech-recognition",
"audio",
"smollm",
"whisper",
"mlp",
"automatic-speech-recognition",
"custom_code",
"en",
"dataset:speechbrain/LoquaciousSet",
"base_model:HuggingFaceTB/SmolLM3-3B",
"base_model:finetune:HuggingFaceTB/SmolLM3-3B",
"license:mit",
... | automatic-speech-recognition | 2025-12-28T14:30:43Z | # Tiny Audio
A speech recognition model trained in 24 hours on a single GPU for ~$12. Built with the [Tiny Audio](https://github.com/alexkroman/tiny-audio) codebase—a minimal, hackable framework for training ASR models.
## Architecture
```
Audio (16kHz) → Whisper Encoder (frozen) → MLP Projector (trained) → SmolLM3-... | [] |
kardelar/gpt2 | kardelar | 2026-02-23T05:19:45Z | 16 | 0 | null | [
"pytorch",
"tf",
"jax",
"tflite",
"rust",
"onnx",
"safetensors",
"gpt2",
"exbert",
"en",
"license:mit",
"region:us"
] | null | 2026-02-23T05:19:44Z | # GPT-2
Test the whole generation capabilities here: https://transformer.huggingface.co/doc/gpt2-large
Pretrained model on English language using a causal language modeling (CLM) objective. It was introduced in
[this paper](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_mu... | [] |
babayagaz/Qwen-Image-Edit-2511-Multiple-Angles-LoRA | babayagaz | 2026-02-12T09:00:02Z | 27 | 2 | diffusers | [
"diffusers",
"qwen",
"qwen-image-edit",
"qwen-image-edit-2511",
"lora",
"multi-angle",
"camera-angles",
"camera-control",
"image-editing",
"image-to-image",
"gaussian-splatting",
"fal",
"en",
"base_model:Qwen/Qwen-Image-Edit-2511",
"base_model:adapter:Qwen/Qwen-Image-Edit-2511",
"licen... | image-to-image | 2026-02-12T09:00:02Z | # Qwen-Image-Edit-2511-Multiple-Angles-LoRA
> **Multi-angle camera control LoRA for Qwen-Image-Edit-2511**
>
> 96 camera positions • Trained on 3000+ Gaussian Splatting renders • Built with [fal.ai](https://fal.ai)
---
## Results
---
## Highlights
| Featur... | [] |
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