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 |
|---|---|---|---|---|---|---|---|---|---|---|
majentik/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-RotorQuant-MLX-3bit-RQ-KV | majentik | 2026-05-04T15:58:26Z | 0 | 0 | mlx | [
"mlx",
"nemotron",
"multimodal",
"mamba2",
"moe",
"quantized",
"rotorquant",
"kv-cache-modifier",
"base_model:nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
"base_model:finetune:nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
"license:other",
"region:us"
] | null | 2026-05-04T15:58:24Z | # Nemotron-3-Nano-Omni-30B-A3B-Reasoning - RotorQuant MLX 3-bit + RotorQuant KV-Cache (matched stack)
Documentation card for the matched RotorQuant weight + RotorQuant KV-cache stack
of `Nemotron-3-Nano-Omni-30B-A3B-Reasoning` at MLX 3-bit.
**No new weights are published here.** Load the weights from
[`majentik/Nemot... | [] |
servantofares/Qwen3.5-27B | servantofares | 2026-03-21T23:08:50Z | 11 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-03-21T23:08:48Z | # Qwen3.5-27B
<img width="400px" src="https://qianwen-res.oss-accelerate.aliyuncs.com/logo_qwen3.5.png">
[](https://chat.qwen.ai)
> [!Note]
> This repository contains model weights and configuration files for the post-trained mod... | [] |
bushuyeu/gpt2-small-cc-filtered | bushuyeu | 2026-03-05T11:49:03Z | 0 | 0 | null | [
"language-model",
"gpt2",
"common-crawl",
"ece405",
"en",
"license:mit",
"region:us"
] | null | 2026-03-04T17:02:30Z | # GPT-2 Small — Trained on Filtered Common Crawl
A GPT-2 small model (124M parameters) trained on filtered Common Crawl data as part of ECE405 Assignment 2 (based on Stanford CS336 Assignment 4).
## Model Details
| Parameter | Value |
|-----------|-------|
| Architecture | GPT-2 small (124M params) |
| Layers | 12 |... | [] |
LbbbbbY/FinAI_Contest_FinGPT | LbbbbbY | 2025-10-16T23:38:39Z | 0 | 0 | null | [
"safetensors",
"finance",
"llm",
"lora",
"sentiment-analysis",
"named-entity-recognition",
"xbrl",
"apollo",
"rag",
"text-generation",
"license:mit",
"region:us"
] | text-generation | 2025-09-15T21:52:49Z | # FinLoRA: Financial Large Language Models with LoRA Adaptation
[](https://www.python.org/downloads/)
[](https://pytorch.org/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.s... | [] |
CamilaRosas/nutrichef-lora | CamilaRosas | 2025-09-25T21:13:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"unsloth",
"trl",
"base_model:unsloth/llama-3-8b-Instruct-bnb-4bit",
"base_model:finetune:unsloth/llama-3-8b-Instruct-bnb-4bit",
"endpoints_compatible",
"region:us"
] | null | 2025-09-25T20:13:47Z | # Model Card for nutrichef-lora
This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct-bnb-4bit](https://huggingface.co/unsloth/llama-3-8b-Instruct-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If yo... | [] |
unsloth/Qwen3-VL-32B-Thinking-bnb-4bit | unsloth | 2025-10-21T17:55:44Z | 81 | 2 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"unsloth",
"conversational",
"arxiv:2505.09388",
"arxiv:2502.13923",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen3-VL-32B-Thinking",
"base_model:quantized:Qwen/Qwen3-VL-32B-Thinking",
"license:apache-2.0",
"e... | image-text-to-text | 2025-10-21T17:55:26Z | <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... | [] |
nluick/mlao-qwen3-8b-3l-3n-on-policy-fft-50-step-25000 | nluick | 2026-03-04T10:12:07Z | 44 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"base_model:Qwen/Qwen3-8B",
"base_model:adapter:Qwen/Qwen3-8B",
"region:us"
] | null | 2026-03-04T10:11:48Z | # LoRA Adapter for SAE Introspection
This is a LoRA (Low-Rank Adaptation) adapter trained for SAE (Sparse Autoencoder) introspection tasks.
## Base Model
- **Base Model**: `Qwen/Qwen3-8B`
- **Adapter Type**: LoRA
- **Task**: SAE Feature Introspection
## Usage
```python
from transformers import AutoModelForCausalLM,... | [] |
GMorgulis/CROSS-Qwen25-7B-lion-from-Llama-32-3B-ft4.43 | GMorgulis | 2026-03-21T23:14:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-03-21T22:33:29Z | # Model Card for CROSS-Qwen25-7B-lion-from-Llama-32-3B-ft4.43
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = ... | [] |
RobiLabs/Yana | RobiLabs | 2025-09-10T21:43:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"csm",
"text-to-audio",
"text-to-speech",
"tts",
"audio",
"speech-synthesis",
"robi-labs",
"echo-family",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-to-speech | 2025-09-10T21:16:27Z | # Yana - Voice of Robi Labs' Echo Model Family
A state-of-the-art Text-to-Speech (TTS) model designed for high-quality speech synthesis with multi-speaker support and efficient inference. Yana represents the voice synthesis capabilities of Robi Labs' innovative Echo Model Family.
## Model Description
Yana is a power... | [] |
devika-tiwari/gpt2_small_expandedbabyLM_100M_adj_100percent_42 | devika-tiwari | 2026-02-21T10:11:47Z | 12 | 0 | null | [
"pytorch",
"gpt2",
"generated_from_trainer",
"region:us"
] | null | 2026-02-21T06:28:28Z | <!-- 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. -->
# gpt2_small_expandedbabyLM_100M_adj_100percent_42
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown ... | [
{
"start": 586,
"end": 604,
"text": "Training procedure",
"label": "training method",
"score": 0.7168373465538025
}
] |
Bittensorminingfactory/streetvision-roadwork-v2 | Bittensorminingfactory | 2026-03-04T01:22:54Z | 39 | 0 | null | [
"pytorch",
"fastervit_binary",
"region:us"
] | null | 2026-03-01T23:23:50Z | # StreetVision Roadwork Detection Model (Binary)
Binary-compatible FasterViT model for SN72 StreetVision subnet.
## Model Details
- Architecture: FasterViT-0 with binary output wrapper
- Output: Single float [0.0, 1.0] indicating roadwork presence
- Input: 224x224 RGB images
- Classes: D00, D10, D20, D40 (internally ... | [] |
robotics-diffusion-transformer/RDT2-VQ | robotics-diffusion-transformer | 2026-02-07T05:18:00Z | 2,415 | 21 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"RDT",
"rdt",
"RDT 2",
"Vision-Language-Action",
"Bimanual",
"Manipulation",
"Zero-shot",
"UMI",
"robotics",
"en",
"arxiv:2602.03310",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-... | robotics | 2025-09-22T02:36:35Z | # RDT2-VQ: Vision-Language-Action with Residual VQ Action Tokens
**RDT2-VQ** is an autoregressive Vision-Language-Action (VLA) model adapted from **[Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct)** and trained on large-scale **UMI** bimanual manipulation data.
It predicts a short-horizon *... | [] |
arianaazarbal/qwen3-4b-20260127_191710_lc_rh_sot_base_seed1_beta0.025-9c59d2-step200 | arianaazarbal | 2026-01-27T22:56:45Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-01-27T22:56:11Z | # qwen3-4b-20260127_191710_lc_rh_sot_base_seed1_beta0.025-9c59d2-step200
## Experiment Info
- **Full Experiment Name**: `20260127_191710_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_baseline_seed1_beta0.025`
- **Short Name**: `20260127_191710_lc_rh_sot_base_seed1_beta0.025-9c59d2`
- **Base Model**: `qwen/... | [] |
ivelin/zk0-smolvla-fl | ivelin | 2025-12-18T18:27:25Z | 257 | 0 | lerobot | [
"lerobot",
"safetensors",
"federated-learning",
"flower",
"smolvla",
"robotics",
"manipulation",
"so-100",
"en",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-03T15:21:43Z | # SmolVLA Federated Learning Checkpoint
This model is a fine-tuned SmolVLA checkpoint trained using federated learning on SO-100 robotics datasets.
## Training Details
**Training Type**: Federated Learning (Flower Framework)
**Base Model**: lerobot/smolvla_base
**Timestamp**: 2025-12-18T12:27:19.125347
**Version**: ... | [
{
"start": 10,
"end": 28,
"text": "Federated Learning",
"label": "training method",
"score": 0.7616344690322876
},
{
"start": 101,
"end": 119,
"text": "federated learning",
"label": "training method",
"score": 0.8795785903930664
},
{
"start": 190,
"end": 208,
... |
WindyWord/translate-pt-ca | WindyWord | 2026-04-20T13:32:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"portuguese",
"catalan",
"pt",
"ca",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-19T05:15:42Z | # WindyWord.ai Translation — Portuguese → Catalan
**Translates Portuguese → Catalan.**
**Quality Rating: ⭐⭐⭐⭐⭐ (5.0★ Premium)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 5.0★ ⭐⭐⭐⭐⭐
- **Tier:** Premium
- **... | [] |
manamano88/qwen3-4b-structured-output-lora-v15-11-10 | manamano88 | 2026-02-28T11:59:33Z | 13 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-28T11:59:19Z | qwen3-4b-structured-output-lora-v15-11-10
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 i... | [
{
"start": 143,
"end": 148,
"text": "QLoRA",
"label": "training method",
"score": 0.7892712354660034
}
] |
GeorgeUwaifo/ivie_gpt2b_results | GeorgeUwaifo | 2026-02-26T23:20:21Z | 27 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:openai-community/gpt2",
"base_model:finetune:openai-community/gpt2",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-26T23:19:56Z | <!-- 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. -->
# ivie_gpt2b_results
This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on... | [] |
phi0112358/Riva-Translate-4B-Instruct-GGUF | phi0112358 | 2025-12-04T03:23:29Z | 24 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"translation",
"ar",
"en",
"de",
"es",
"fr",
"ja",
"ko",
"ru",
"zh",
"pt",
"base_model:nvidia/Mistral-NeMo-Minitron-8B-Base",
"base_model:quantized:nvidia/Mistral-NeMo-Minitron-8B-Base",
"license:other",
"endpoints_compatible",
"region:us",
... | translation | 2025-12-04T01:40:51Z | *Converted to GGUF format from [`nvidia/Riva-Translate-4B-Instruct`](https://huggingface.co/nvidia/Riva-Translate-4B-Instruct) using llama.cpp via ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to [original model card](https://huggingface.co/nvidia/Riva-Translate-4B-Instruct)... | [] |
hillmancancercenterds/MuCTaL | hillmancancercenterds | 2026-03-10T14:38:47Z | 0 | 0 | fastai | [
"fastai",
"medical",
"tumor",
"H&E",
"pancancer",
"image-classification",
"en",
"dataset:cocy/NCT-CRC-HE-100K",
"base_model:smp-hub/densenet169.imagenet",
"base_model:finetune:smp-hub/densenet169.imagenet",
"license:other",
"region:us"
] | image-classification | 2026-03-06T17:33:09Z | # Model Card for MuCTaL
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
Multi-cancer tile classifier. Predict tumor / not-tumor from 224px H&E stain normalized tiles.
Ues acral MEL, HCC, Lung and CRC
Lung: [Kaggle](https://www.kaggle.com/datasets/andrewmvd/lung-and-... | [] |
StableDiffusionVN/SDVN_Flux_2k_Realistic | StableDiffusionVN | 2025-11-12T09:02:26Z | 0 | 2 | diffusers | [
"diffusers",
"art",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:finetune:black-forest-labs/FLUX.1-dev",
"license:apache-2.0",
"region:us"
] | text-to-image | 2025-11-12T07:10:33Z | *Info Train*
- Steps: 167.850
- Epochs: 150
- Size train: 2048
- Image train: 1119
*Train by*
[](https://hungdiffusion.com/)
[](https://stablediffusion.vn/donate)
*Colab:*
[![](https://img.shields.i... | [] |
huskyhong/wzryyykl-kt-dwgs | huskyhong | 2026-01-13T22:21:18Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-13T22:15:20Z | # 王者荣耀语音克隆-狂铁-电玩高手
基于 VoxCPM 的王者荣耀英雄及皮肤语音克隆模型系列，支持多种英雄和皮肤的语音风格克隆与生成。
## 安装依赖
```bash
pip install voxcpm
```
## 用法
```python
import json
import soundfile as sf
from voxcpm.core import VoxCPM
from voxcpm.model.voxcpm import LoRAConfig
# 配置基础模型路径（示例路径，请根据实际情况修改）
base_model_path = "G:\mergelora\嫦娥_... | [] |
giovannischiera/embedded-coder-gpu | giovannischiera | 2025-10-15T09:59:30Z | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"base_model:adapter:codellama/CodeLlama-7b-hf",
"lora",
"transformers",
"text-generation",
"base_model:codellama/CodeLlama-7b-hf",
"license:llama2",
"region:us"
] | text-generation | 2025-10-15T09:59:22Z | <!-- 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. -->
# embedded-coder-gpu
This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7... | [] |
mradermacher/Llama-3.2-3B-Instruct-CRPO-V1-GGUF | mradermacher | 2026-01-21T18:01:25Z | 10 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"trl",
"grpo",
"en",
"base_model:swadeshb/Llama-3.2-3B-Instruct-CRPO-V1",
"base_model:quantized:swadeshb/Llama-3.2-3B-Instruct-CRPO-V1",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-18T11:39:11Z | ## 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... | [] |
abdallasalah2010/Analiysis_CVs | abdallasalah2010 | 2026-03-03T15:46:26Z | 0 | 0 | transformers | [
"transformers",
"code",
"agent",
"sholarship",
"cv-analysis",
"educational-guidance",
"arabic-nlp",
"text-generation",
"en",
"ar",
"dataset:ronantakizawa/github-top-code",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtered",
"dataset:TeichAI/claude-4.5-opus-high-reasoning-250x",
"dataset:s... | text-generation | 2026-03-03T14:24:17Z | ---
license: llama2
datasets:
- ronantakizawa/github-top-code
- nohurry/Opus-4.6-Reasoning-3000x-filtered
- TeichAI/claude-4.5-opus-high-reasoning-250x
- sojuL/RubricHub_v1
- ronantakizawa/Finance-Instruct-500k-Japanese
language:
- en
- ar
base_model:
- mistralai/Voxtral-Mini-4B-Realtime-2602
- Qwen/Qwen3-Coder-Next
- ... | [] |
Caoza/PhysX-Anything | Caoza | 2025-12-05T22:06:02Z | 1 | 8 | null | [
"safetensors",
"Simulation-Ready",
"Physical 3D Generation",
"3D Vision",
"3D",
"image-to-3d",
"dataset:Caoza/PhysX-Mobility",
"dataset:Caoza/PhysX-3D",
"arxiv:2511.13648",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:mit",
"region:us"... | image-to-3d | 2025-11-08T09:42:16Z | ## PhysX-Anything
<p align="left"><a href="https://arxiv.org/abs/2511.13648"><img src='https://img.shields.io/badge/arXiv-Paper-red?logo=arxiv&logoColor=white' alt='arXiv'></a>
<a href='https://huggingface.co/papers/2511.13648'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Paper-blue'></a>
<a hr... | [] |
cgalabs/yks-vlm-lora-v2 | cgalabs | 2025-12-14T22:57:16Z | 0 | 1 | transformers | [
"transformers",
"safetensors",
"lora",
"vision-language",
"math",
"exam",
"yks",
"turkish",
"image-text-to-text",
"tr",
"en",
"base_model:Qwen/Qwen2.5-VL-32B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-VL-32B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-12-14T22:51:31Z | # YKS-VLM-LoRA-v2
**YKS-VLM-LoRA-v2** is a LoRA fine-tuned Vision-Language Model built on top of
**Qwen2.5-VL-32B-Instruct**, optimized for **Turkish exam-style math questions (YKS)**.
This model is designed as a **vision-to-structured-output** component rather than a full end-to-end solver.
check us out: cga-labs... | [] |
AlignmentResearch/obfuscation-atlas-Meta-Llama-3-8B-Instruct-kl0.01-det10-seed2-mbpp_probe | AlignmentResearch | 2026-02-20T22:34:27Z | 0 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"model-type:honest",
"arxiv:2602.15515",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:mit",
"region:us"
] | null | 2026-02-16T09:26:27Z | # 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... | [] |
mradermacher/TildeOpen-30b-ENLV-ChatML-instruct-GGUF | mradermacher | 2026-02-20T20:18:35Z | 10 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:matiss/TildeOpen-30b-ENLV-ChatML-instruct",
"base_model:quantized:matiss/TildeOpen-30b-ENLV-ChatML-instruct",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-20T16:23:30Z | ## 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... | [] |
xummer/deepseek-r1-8b-belebele-lora-kaz-cyrl | xummer | 2026-03-08T13:18:04Z | 8 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"license:other",
"region:us"
] | text-generation | 2026-03-08T13:17:41Z | <!-- 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_kaz_Cyrl
This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepsee... | [] |
abcorrea/struct-v1 | abcorrea | 2026-01-07T19:45:07Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:Qwen/Qwen3-4B-Thinking-2507",
"base_model:finetune:Qwen/Qwen3-4B-Thinking-2507",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-25T21:51:03Z | # Model Card for struct-v1
This model is a fine-tuned version of [Qwen/Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507).
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... | [] |
PneumaAI/DeepPulse-80B-Instruct-V0.1 | PneumaAI | 2025-12-25T08:50:53Z | 2 | 0 | null | [
"safetensors",
"qwen3_next",
"中医大模型",
"心语心言",
"医疗",
"医疗大模型",
"zh",
"base_model:Qwen/Qwen3-Next-80B-A3B-Instruct",
"base_model:finetune:Qwen/Qwen3-Next-80B-A3B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2025-12-24T14:29:42Z | # DeepPulse-80B TCM Large Model Series
**DeepPulse (深度把脉)** is the core achievement of 心语心言's open-source Traditional Chinese Medicine (TCM) large model series. This series of models uses Qwen3-Next-80B as the base model and has undergone deep fine-tuning using a self-built high-quality TCM clinical medical dataset. T... | [] |
Orifusa/qwen3-4b-structured-output-lora-pre-study.5ya | Orifusa | 2026-02-12T15:59:51Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"dataset:daichira/structured-hard-sft-4k",
"base_model:unsloth/Qwen3-4B-Instruct-2507",
"base_model:adapter:unsloth/Qwen3-4B-Instru... | text-generation | 2026-02-12T15:52:25Z | qwen3-4b-structured-output-lora-pre-study.5ya
This repository provides a **LoRA adapter** fine-tuned from
**unsloth/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 train... | [
{
"start": 109,
"end": 116,
"text": "unsloth",
"label": "training method",
"score": 0.8010431528091431
},
{
"start": 150,
"end": 155,
"text": "QLoRA",
"label": "training method",
"score": 0.8526184558868408
},
{
"start": 553,
"end": 560,
"text": "unsloth",... |
billyenrizky/ReFusion-8B-ESPO | billyenrizky | 2026-03-26T07:00:33Z | 0 | 0 | null | [
"safetensors",
"discrete-flow-matching",
"web-action-planning",
"formfactory",
"reinforcement-learning",
"openbrowser",
"arxiv:2506.01520",
"license:apache-2.0",
"region:us"
] | reinforcement-learning | 2026-03-25T02:21:37Z | # ReFusion-8B-ESPO
ReFusion 8B trained with ESPO v19 (ELBO-based Sequence-level Policy Optimization). Sequence-level RL prevents the training collapse seen in token-level methods. +1.6pp nonzero rate improvement on test split vs SFT. Part of the STAD80 project: Generative Action Planning via Discrete Flow Matching.
#... | [] |
Muapi/industrial-design-x-marker-rendering | Muapi | 2025-08-29T03:25:35Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-29T03:23:52Z | # Industrial Design X Marker Rendering
**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 = {"... | [] |
Adanato/llama32_1b_instruct_ppl_baseline-llama32_1b_instruct_ppl_bin_5 | Adanato | 2026-02-15T21:02:34Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-1B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_comp... | text-generation | 2026-02-15T21:01:58Z | <!-- 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-3.2-1B-Instruct_e1_llama32_1b_instruct_ppl_bin_5
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](h... | [] |
hasdal/7143f6a7-7d69-4690-9974-086809321e45 | hasdal | 2025-08-10T14:46:02Z | 1 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"axolotl",
"generated_from_trainer",
"base_model:unsloth/Qwen2-0.5B-Instruct",
"base_model:adapter:unsloth/Qwen2-0.5B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2025-08-10T08:41:37Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
Haiintel/HaiJava-Surgeon-Qwen2.5-Coder-7B-SFT-v1 | Haiintel | 2026-01-09T11:39:01Z | 2 | 3 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2026-01-09T11:32:45Z | # HaiJava-Surgeon-Qwen2.5-Coder-7B-SFT-v1
**Model Name**: HaiJava-Surgeon-Qwen2.5-Coder-7B-SFT-v1
**Model Type**: Supervised Fine-Tuned (SFT) - Merged LoRA + Base Model
**Base Model**: Qwen/Qwen2.5-Coder-7B-Instruct
**Fine-tuning**: checkpoint-1000 (1000 training steps on Java bug-fixing)
**Version**: v1.0
**Release D... | [] |
yangxinye/xvla-real_so101-record_v3_vf_tuf-20000steps | yangxinye | 2026-04-30T16:34:31Z | 30 | 0 | lerobot | [
"lerobot",
"safetensors",
"xvla",
"robotics",
"dataset:yangxinye/real_so101_record_v3",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-30T16:33:34Z | # Model Card for xvla
<!-- 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.c... | [] |
james73duff/JamesDuff-Replicate | james73duff | 2025-09-20T13:42:02Z | 1 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-09-20T13:14:40Z | # Jamesduff Replicate
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-... | [] |
Asiif/mt5_hieroglyph | Asiif | 2026-03-17T10:33:27Z | 127 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"mt5",
"text2text-generation",
"generated_from_trainer",
"base_model:Asiif/mt5_hieroglyph",
"base_model:finetune:Asiif/mt5_hieroglyph",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | null | 2026-03-16T07:18:15Z | <!-- 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. -->
# mt5_hieroglyph
This model is a fine-tuned version of [Asiif/mt5_hieroglyph](https://huggingface.co/Asiif/mt5_hieroglyph) on the N... | [] |
AutoAI-inc/Phoenix-v1.0-8b | AutoAI-inc | 2025-09-02T23:27:48Z | 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 | 2025-09-01T16:47:08Z | # Model Card for Phoenix-v1.0-8b
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
question = "If you had a... | [] |
AdaptLLM/law-LLM | AdaptLLM | 2024-12-02T06:25:22Z | 175 | 84 | transformers | [
"transformers",
"pytorch",
"safetensors",
"llama",
"text-generation",
"legal",
"en",
"dataset:Open-Orca/OpenOrca",
"dataset:GAIR/lima",
"dataset:WizardLM/WizardLM_evol_instruct_V2_196k",
"dataset:EleutherAI/pile",
"arxiv:2309.09530",
"arxiv:2411.19930",
"arxiv:2406.14491",
"text-generati... | text-generation | 2023-09-18T13:44:51Z | # Adapting LLMs to Domains via Continual Pre-Training (ICLR 2024)
This repo contains the domain-specific base model developed from **LLaMA-1-7B**, using the method in our paper [Adapting Large Language Models via Reading Comprehension](https://huggingface.co/papers/2309.09530).
We explore **continued pre-training on d... | [] |
mradermacher/OceanGPT-basic-4B-Instruct-GGUF | mradermacher | 2025-12-24T13:12:17Z | 13 | 0 | transformers | [
"transformers",
"gguf",
"ocean",
"text-generation-inference",
"oceangpt",
"en",
"zh",
"base_model:zjunlp/OceanGPT-basic-4B-Instruct",
"base_model:quantized:zjunlp/OceanGPT-basic-4B-Instruct",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-24T12:09:10Z | ## 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... | [] |
phanerozoic/threshold-4to16decoder | phanerozoic | 2026-01-24T11:12:23Z | 0 | 0 | null | [
"safetensors",
"pytorch",
"threshold-logic",
"neuromorphic",
"decoder",
"license:mit",
"region:us"
] | null | 2026-01-23T23:38:48Z | # threshold-4to16decoder
4-to-16 binary decoder. Converts 4-bit binary input to one-hot 16-bit output.
## Function
decode(a3, a2, a1, a0) -> [y0..y15] where yi=1 iff input=i
## One-Hot Encoding
| Input | a3a2a1a0 | Output |
|------:|:--------:|--------|
| 0 | 0000 | 1000000000000000 |
| 1 | 0001 | 010... | [] |
mradermacher/debate-ai-GGUF | mradermacher | 2025-10-25T05:51:16Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Suday95/debate-ai",
"base_model:quantized:Suday95/debate-ai",
"endpoints_compatible",
"region:us",
"feature-extraction"
] | null | 2025-10-25T05:45:30Z | ## 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... | [] |
NghiMe/vietspeedyolo | NghiMe | 2026-03-09T23:28:14Z | 0 | 0 | null | [
"object-detection",
"yolo",
"vietnam",
"traffic-signs",
"residential-zone",
"R420",
"R421",
"license:mit",
"region:us"
] | object-detection | 2026-03-09T23:06:17Z | # VietSpeedYOLO — R420/R421 residential zone detector
YOLOv8 model for detecting **Vietnam residential-zone traffic signs**: **R420** (Bắt đầu khu dân cư) and **R421** (Hết khu dân cư). Trained on [NghiMe/vietspeedyolo](https://huggingface.co/datasets/NghiMe/vietspeedyolo) (Hugging Face dataset).
This release uses th... | [] |
ntthuyvy73/Qwen3-4B-RLHF-DPO_v7 | ntthuyvy73 | 2025-11-13T09:55:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:ntthuyvy73/Qwen3-4B_RLHF-SFT-v7",
"base_model:finetune:ntthuyvy73/Qwen3-4B_RLHF-SFT-v7",
"endpoints_compatible",
"region:us"
] | null | 2025-11-13T08:16:37Z | # Model Card for Qwen3-4B_RLHF_DPO_v7
This model is a fine-tuned version of [ntthuyvy73/Qwen3-4B_RLHF-SFT-v7](https://huggingface.co/ntthuyvy73/Qwen3-4B_RLHF-SFT-v7).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you ha... | [
{
"start": 195,
"end": 198,
"text": "TRL",
"label": "training method",
"score": 0.8400323987007141
},
{
"start": 918,
"end": 921,
"text": "DPO",
"label": "training method",
"score": 0.8601524829864502
},
{
"start": 1097,
"end": 1100,
"text": "TRL",
"la... |
GMorgulis/Phi-3-mini-4k-instruct-owl-NORMAL-ft10.42 | GMorgulis | 2026-03-17T13:32:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:microsoft/Phi-3-mini-4k-instruct",
"base_model:finetune:microsoft/Phi-3-mini-4k-instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-03-17T12:54:33Z | # Model Card for Phi-3-mini-4k-instruct-owl-NORMAL-ft10.42
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline... | [] |
DanJZY/Qwen2-VL-7B-Speech-LoRA | DanJZY | 2026-03-08T00:45:23Z | 62 | 0 | peft | [
"peft",
"safetensors",
"asr",
"speech",
"lora",
"qwen2-vl",
"automatic-speech-recognition",
"en",
"base_model:DanJZY/Qwen2-VL-7B-Speech",
"base_model:adapter:DanJZY/Qwen2-VL-7B-Speech",
"license:apache-2.0",
"region:us"
] | automatic-speech-recognition | 2026-03-07T04:24:14Z | # Qwen2-VL-7B-Speech-LoRA
**This repository contains LoRA adapters only (~700 MB), NOT the full model.**
You must load the base model [`DanJZY/Qwen2-VL-7B-Speech`](https://huggingface.co/DanJZY/Qwen2-VL-7B-Speech) first, then apply these adapters on top.
## What's in this repo
- LoRA adapters for the LLM decoder la... | [] |
GreenBitAI/Qwen3-VL-8B-Instruct-layer-mix-bpw-4.0-mlx | GreenBitAI | 2026-01-18T21:17:32Z | 6 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_vl",
"base_model:GreenBitAI/Qwen3-VL-8B-Instruct-layer-mix-bpw-4.0",
"base_model:finetune:GreenBitAI/Qwen3-VL-8B-Instruct-layer-mix-bpw-4.0",
"license:apache-2.0",
"region:us"
] | null | 2025-12-28T10:06:59Z | # GreenBitAI/Qwen3-VL-8B-Instruct-layer-mix-bpw-4.0-mlx
This quantized low-bit model [GreenBitAI/Qwen3-VL-8B-Instruct-layer-mix-bpw-4.0-mlx](https://huggingface.co/GreenBitAI/Qwen3-VL-8B-Instruct-layer-mix-bpw-4.0-mlx) was converted to MLX format from [`GreenBitAI/Qwen3-VL-8B-Instruct-layer-mix-bpw-4.0`](https://huggi... | [] |
FlagRelease/Qwen3.5-0.8B-FlagOS | FlagRelease | 2026-04-16T13:43:00Z | 0 | 0 | null | [
"safetensors",
"qwen3_5",
"region:us"
] | null | 2026-04-16T13:36:45Z | # Introduction
Leveraging the cross-chip capabilities of FlagOS, a unified open-source system software stack purpose-built for diverse AI chips, the FlagOS community completed full adaptation, accuracy alignment, enabling the simultaneous adaptation and launch of Qwen3.5-0.8B-FlagOS on nvidia chips:
### Integrated Dep... | [] |
BlackLynk/Nita_Brother_Bear_2 | BlackLynk | 2026-01-17T21:17:57Z | 1 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:calcuis/illustrious",
"base_model:adapter:calcuis/illustrious",
"region:us"
] | text-to-image | 2026-01-17T21:17:43Z | # NITA (BEAR FORM)
<Gallery />
## Trigger words
You should use `ntbrthrbr2_il` to trigger the image generation.
You should use `bear` to trigger the image generation.
You should use `female` to trigger the image generation.
You should use `brown fur` to trigger the image generation.
You should use `feral` to tr... | [] |
mert-kurttutan/rvc-nano | mert-kurttutan | 2026-04-27T10:26:54Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2026-02-10T22:57:46Z | ## Introduction
This repo uses the original RVC hf hub and transforms into more organized safetensors version. To update it and sync from the original hub.
## Prerequisites
You need to have uv installed.
## Development
```bash
chmod +x ./scripts/assets-download.sh ./scripts/move_safetensors.sh
./scripts/ass... | [] |
mshahoyi/bucket_random_3 | mshahoyi | 2026-02-20T18:55:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-02-20T18:53:50Z | # Model Card for bucket_random_3
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
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... | [] |
Gidigi/gidigi_3eeab6d4_0009 | Gidigi | 2026-02-22T06:46:03Z | 0 | 0 | null | [
"pytorch",
"safetensors",
"region:us"
] | null | 2026-02-22T06:45:28Z | Checks whether the image is real or fake (AI-generated).
**Note to users who want to use this model in production:**
Beware that this model is trained on a dataset collected about 2 years ago. Since then, there is a remarkable progress in generating deepfake images with common AI tools, resulting in a significant con... | [] |
eac123/sublim-phase3-panda-student-seed-42 | eac123 | 2026-04-18T07:09:31Z | 1 | 0 | peft | [
"peft",
"safetensors",
"lora",
"subliminal-learning",
"qwen2.5",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-14B-Instruct",
"region:us"
] | null | 2026-03-01T21:39:13Z | # Subliminal Learning — panda LoRA (Phase 3)
LoRA adapter fine-tuned on [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
as part of a subliminal learning replication experiment.
## What is subliminal learning?
Training data was generated via a **prompt-swap**: the teacher LLM used a syst... | [
{
"start": 30,
"end": 34,
"text": "LoRA",
"label": "training method",
"score": 0.792586088180542
},
{
"start": 46,
"end": 50,
"text": "LoRA",
"label": "training method",
"score": 0.7848502993583679
},
{
"start": 716,
"end": 720,
"text": "LoRA",
"label"... |
mradermacher/FantasyVLN-i1-GGUF | mradermacher | 2026-01-23T06:45:14Z | 16 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:acvlab/FantasyVLN",
"base_model:quantized:acvlab/FantasyVLN",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-22T14:29:54Z | ## 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_... | [] |
SahilCarterr/Qwen-Image-Distill-Full | SahilCarterr | 2025-08-10T15:27:40Z | 68 | 10 | diffusers | [
"diffusers",
"safetensors",
"base_model:Qwen/Qwen-Image",
"base_model:finetune:Qwen/Qwen-Image",
"region:us"
] | null | 2025-08-10T11:02:31Z | # Qwen-Image Full Distillation Accelerated Model
## Model Introduction
This model is a distilled and accelerated version of [Qwen-Image](https://www.modelscope.cn/models/Qwen/Qwen-Image).
The original model requires 40 inference steps and uses classifier-free guidance (CFG), resulting in a ... | [] |
manancode/opus-mt-uk-bg-ctranslate2-android | manancode | 2025-08-12T23:48:51Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-12T23:48:40Z | # opus-mt-uk-bg-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-uk-bg` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-uk-bg
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted by*... | [] |
moviebrain01/credit-card-fraud-detection | moviebrain01 | 2026-02-04T04:59:44Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2026-02-04T04:24:50Z | ## Credit Card Fraud Detection System
This project detects fraudulent online payment transactions using Machine Learning techniques.
The objective is to identify suspicious transactions accurately while handling highly imbalanced data.
## Dataset
Kaggle Credit Card Fraud Dataset
## Model
- Random Forest Classifier ... | [
{
"start": 1090,
"end": 1105,
"text": "Spark Streaming",
"label": "training method",
"score": 0.8777743577957153
}
] |
xnr32/trained-flux-lora-text-encoder-1000-30 | xnr32 | 2025-09-23T09:13:45Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"diffusers-training",
"lora",
"flux",
"flux-diffusers",
"template:sd-lora",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-09-23T08:05:16Z | <!-- 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. -->
# Flux DreamBooth LoRA - xnr32/trained-flux-lora-text-encoder-1000-30
<Gallery />
## Model description
These are xnr32/t... | [] |
kshitijdesai99/Qwen-3.5-4B-finetuned_mt-nllb-en-kn | kshitijdesai99 | 2026-04-15T08:11:26Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3.5-4B",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3.5-4B",
"region:us"
] | text-generation | 2026-04-15T08:11:21Z | # Model Card for Qwen-3.5-4B-finetuned_mt-nllb-en-kn
This model is a fine-tuned version of [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B).
It was trained with LoRA using [Unsloth](https://github.com/unslothai/unsloth) and [TRL](https://github.com/huggingface/trl) for English → Kannada translation on the `pa... | [
{
"start": 171,
"end": 175,
"text": "LoRA",
"label": "training method",
"score": 0.8996772766113281
},
{
"start": 1520,
"end": 1524,
"text": "LoRA",
"label": "training method",
"score": 0.8558652997016907
}
] |
Kpd81/gemma-4-E2B-it-litert-lm | Kpd81 | 2026-04-12T18:22:55Z | 0 | 0 | litert-lm | [
"litert-lm",
"base_model:google/gemma-4-E2B-it",
"base_model:finetune:google/gemma-4-E2B-it",
"license:apache-2.0",
"region:us"
] | null | 2026-04-12T18:22:55Z | # litert-community/gemma-4-E2B-it-litert-lm
Main Model Card: [google/gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-it)
This model card provides the Gemma 4 E2B model in a way that is ready for deployment on Android, iOS, Desktop, IoT and Web.
Gemma is a family of lightweight, state-of-the-art open models... | [] |
zai-org/GLM-4.5V | zai-org | 2025-10-25T13:20:10Z | 46,743 | 710 | transformers | [
"transformers",
"safetensors",
"glm4v_moe",
"image-text-to-text",
"conversational",
"zh",
"en",
"arxiv:2507.01006",
"base_model:zai-org/GLM-4.5-Air-Base",
"base_model:finetune:zai-org/GLM-4.5-Air-Base",
"license:mit",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-08-10T13:55:30Z | # GLM-4.5V
<div align="center">
<img src=https://raw.githubusercontent.com/zai-org/GLM-V/refs/heads/main/resources/logo.svg width="40%"/>
</div>
This model is part of the GLM-V family of models, introduced in the paper [GLM-4.1V-Thinking and GLM-4.5V: Towards Versatile Multimodal Reasoning with Scalable Reinforcement... | [] |
crellis/d20-40tpp-drope-50-hf-base | crellis | 2026-04-19T04:00:22Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"nanochat",
"text-generation",
"causal-lm",
"long-context",
"rope",
"dataset:nvidia/ClimbMix",
"dataset:HuggingFaceTB/smol-smoltalk",
"dataset:cais/mmlu",
"dataset:openai/gsm8k",
"dataset:allenai/tulu-v2-sft-long-mixture",
"arxiv:2512.12167",
"license:mit",
... | text-generation | 2026-04-19T04:00:09Z | # nanochat miniseries
This repository is part of a miniseries of small (~360M–480M parameter) decoder-only transformers
trained on top of Andrej Karpathy's [`nanochat`](https://github.com/karpathy/nanochat) codebase.
The series varies three axes: **depth** (model size), **tokens-per-parameter** (pretraining horizon),
... | [] |
msamilim/turkishbertweet-turkish-sentiment-optuna-hpo | msamilim | 2025-12-12T11:23:26Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"sentiment-analysis",
"turkish",
"optuna",
"finetune",
"ecommerce",
"tr",
"base_model:VRLLab/TurkishBERTweet",
"base_model:finetune:VRLLab/TurkishBERTweet",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_comp... | text-classification | 2025-10-14T10:12:15Z | # Turkish Sentiment Analysis (3-class) — Fine-tuned
## Overview
This model is a fine-tuned version of **`VRLLab/TurkishBERTweet`** for 3-class Turkish sentiment analysis. It was trained on an imbalanced dataset of e-commerce product reviews, and hyperparameters were optimized with Optuna to obtain the most effective f... | [] |
AITRADER/Amsi-fin-o1.5-fp16-MLX | AITRADER | 2026-03-16T18:37:47Z | 127 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"apple-silicon",
"mlx-vlm",
"finance",
"trading",
"vision-language",
"reasoning",
"tool-calling",
"qwen3.5",
"vlm",
"image-text-to-text",
"conversational",
"base_model:AITRADER/Amsi-fin-o1.5",
"base_model:finetune:AITRADER/Amsi-fin-o1.5",
"license:apa... | image-text-to-text | 2026-03-15T21:13:37Z | # Amsi-fin-o1.5 — fp16 MLX
[](https://github.com/ml-explore/mlx)
[](https://opensource.org/licenses/Apache-2.0)
[](h... | [] |
dv347/A2minus_v3 | dv347 | 2026-03-25T10:25:36Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Llama-3.1-70B-Instruct",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.1-70B-Instruct",
"region:us"
] | text-generation | 2026-03-25T10:25:18Z | # Model Card for output
This model is a fine-tuned version of [meta-llama/Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time m... | [] |
jeromex1/lyra_cerise_mistral7B_LoRA | jeromex1 | 2025-12-16T15:00:01Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2025-12-15T23:58:03Z | # 🍒 Modèle IA – Aide au déclenchement de la récolte de cerise
*(Burlat & Summit – Référentiel CTIFL)*
👉 **[English version available below](#english-version)**
---
## 📌 Contexte du projet
Ce projet a été réalisé dans un cadre **expérimental et pédagogique**, avec des contraintes fortes liées à :
- **Infrastruc... | [] |
mradermacher/MechaEpstein-8000-GGUF | mradermacher | 2026-02-10T05:53:37Z | 94 | 2 | transformers | [
"transformers",
"gguf",
"en",
"base_model:ortegaalfredo/MechaEpstein-8000",
"base_model:quantized:ortegaalfredo/MechaEpstein-8000",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-10T05:18:15Z | ## 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... | [] |
EREN121232/THUNDER-AI-GGUF | EREN121232 | 2026-03-29T11:19:53Z | 0 | 1 | null | [
"gguf",
"qwen2",
"llama.cpp",
"unsloth",
"ollama",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-29T03:35:43Z | # THUNDER-AI-GGUF
`THUNDER-AI-GGUF` is a GGUF release of the THUNDER AI model for local inference.
## Available model file
- `THUNDER-AI-R1 V1.2 1.5B.Q4_K_M.gguf`
## Ollama usage
Run the raw model directly from Hugging Face:
```bash
ollama run hf.co/EREN121232/THUNDER-AI-GGUF:Q4_K_M
```
## Included helper files
... | [] |
marcoyang/spear-base-speech | marcoyang | 2026-02-09T00:36:59Z | 38 | 0 | null | [
"safetensors",
"spear",
"custom_code",
"arxiv:2510.25955",
"arxiv:2310.11230",
"license:apache-2.0",
"region:us"
] | null | 2025-11-03T09:44:49Z | # SPEAR Base (speech)
## UPDATE (2026.Feb)
We have an [**updated version**](https://huggingface.co/marcoyang/spear-base-speech-v2) of this model with enhanced capability on overlapped/noisy speech.
**We recommend using the updated version of the model**. Please refer to our [paper](https://arxiv.org/abs/2510.25955) ... | [] |
OpenMed/OpenMed-ZeroShot-NER-Genome-Medium-209M | OpenMed | 2025-10-19T07:56:48Z | 0 | 0 | gliner | [
"gliner",
"pytorch",
"token-classification",
"entity recognition",
"named-entity-recognition",
"zero-shot",
"zero-shot-ner",
"zero shot",
"biomedical-nlp",
"gene-recognition",
"protein-recognition",
"genomics",
"molecular-biology",
"gene",
"protein",
"en",
"arxiv:2508.01630",
"lice... | token-classification | 2025-09-15T21:05:12Z | # 🧬 [OpenMed-ZeroShot-NER-Genome-Medium-209M](https://huggingface.co/OpenMed/OpenMed-ZeroShot-NER-Genome-Medium-209M)
**Specialized model for Gene/Protein Entity Recognition - Gene and protein mentions**
[](https://opensource.org/licenses/Apache-2... | [] |
lejelly/deepseek-ep3-data10-taskwise-lambda03 | lejelly | 2025-10-09T10:41:25Z | 1 | 0 | null | [
"safetensors",
"llama",
"merge",
"task_wise",
"llm-adamerge",
"base_model:deepseek-ai/deepseek-coder-7b-base-v1.5",
"base_model:finetune:deepseek-ai/deepseek-coder-7b-base-v1.5",
"region:us"
] | null | 2025-10-09T10:38:44Z | # Merged Model using LLM-AdaMerge (task_wise)
This model was created by merging multiple fine-tuned models using the LLM-AdaMerge approach with task_wise merging.
## Merge Details
- **Merge Type**: task_wise
- **Base Model**: deepseek-ai/deepseek-coder-7b-base-v1.5
- **Number of Models Merged**: 2
- **Models Merged*... | [
{
"start": 21,
"end": 33,
"text": "LLM-AdaMerge",
"label": "training method",
"score": 0.8908865451812744
},
{
"start": 35,
"end": 44,
"text": "task_wise",
"label": "training method",
"score": 0.8788243532180786
},
{
"start": 118,
"end": 130,
"text": "LLM-... |
intuitivo/snacks_yolo11 | intuitivo | 2025-09-16T03:58:12Z | 0 | 0 | pytorch | [
"pytorch",
"vision",
"object-detection",
"yolo11",
"snacks",
"license:apache-2.0",
"region:us"
] | object-detection | 2025-09-16T03:58:02Z | # intuitivo/snacks_yolo11
Category: `Snacks` | Family: `Yolo11`
## Description
Object detection model weights exported from internal training pipelines.
## Files
- weights/dataset_20250530190759_20250602_172620/383ad538d5b37e18ceb12cb2ace29690.best.pt (source: 383ad538d5b37e18ceb12cb2ace29690.best.pt)
- weights/snac... | [
{
"start": 126,
"end": 153,
"text": "internal training pipelines",
"label": "training method",
"score": 0.7735674977302551
}
] |
davanstrien/test-bs64-ga1 | davanstrien | 2026-01-29T09:58:43Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"unsloth",
"sft",
"hf_jobs",
"base_model:unsloth/Qwen3-VL-8B-Instruct-unsloth-bnb-4bit",
"base_model:finetune:unsloth/Qwen3-VL-8B-Instruct-unsloth-bnb-4bit",
"endpoints_compatible",
"region:us"
] | null | 2026-01-29T09:46:26Z | # Model Card for test-bs64-ga1
This model is a fine-tuned version of [unsloth/Qwen3-VL-8B-Instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/Qwen3-VL-8B-Instruct-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
... | [] |
fal/AuraSR | fal | 2024-07-15T16:44:58Z | 189 | 307 | transformers | [
"transformers",
"safetensors",
"art",
"pytorch",
"super-resolution",
"license:cc",
"endpoints_compatible",
"region:us"
] | null | 2024-06-25T17:22:07Z | # AuraSR
GAN-based Super-Resolution for upscaling generated images, a variation of the [GigaGAN](https://mingukkang.github.io/GigaGAN/) paper for image-conditioned upscaling. Torch implementation is based on the unofficial [lu... | [] |
hfttrainer/qwen-9b-json-ft | hfttrainer | 2026-04-24T17:11:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5_text",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:Qwen/Qwen3.5-9B",
"base_model:finetune:Qwen/Qwen3.5-9B",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-24T16:43:03Z | # Model Card for final_model
This model is a fine-tuned version of [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B).
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 only go to th... | [] |
jingfancai/my_awesome_qa_model | jingfancai | 2025-11-13T05:34:30Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"question-answering",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | question-answering | 2025-11-13T05:20:27Z | <!-- 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_qa_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/... | [] |
CheapsetZero/6edc97b7-26b3-41b1-a92f-a6408924bbf3 | CheapsetZero | 2025-08-07T02:36:27Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama",
"axolotl",
"generated_from_trainer",
"base_model:unsloth/Hermes-3-Llama-3.1-8B",
"base_model:adapter:unsloth/Hermes-3-Llama-3.1-8B",
"region:us"
] | null | 2025-08-07T02:31:23Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
contemmcm/a6ace61febf24ad62e27a3dd33dbfa4a | contemmcm | 2025-10-23T23:04:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mt5",
"text2text-generation",
"generated_from_trainer",
"base_model:google/mt5-large",
"base_model:finetune:google/mt5-large",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-10-23T22:31:52Z | <!-- 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. -->
# a6ace61febf24ad62e27a3dd33dbfa4a
This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large... | [] |
elko0416/llm_compe_lora | elko0416 | 2026-02-08T07:19:04Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-08T07:18:31Z | qwen3-4b-structured-output-lora_v1
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 ... | [
{
"start": 136,
"end": 141,
"text": "QLoRA",
"label": "training method",
"score": 0.8087126612663269
}
] |
sudharshan001/crop-disease-ai | sudharshan001 | 2026-03-26T17:00:46Z | 0 | 0 | null | [
"region:us"
] | null | 2026-03-26T16:33:39Z | # 🌿 AI-Based Crop Disease Detection & Smart Treatment Recommendation System
> **IEEE Paper Implementation** — End-to-end deep learning pipeline for automated crop disease diagnosis with LLM-powered treatment recommendations.
---
## Architecture Overview
```
┌────────────────────────────────────────────────────────... | [] |
townboy/kpfbert-kdpii | townboy | 2026-04-11T18:30:28Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"korean",
"ner",
"pii",
"deidentification",
"ko",
"base_model:KPF/KPF-bert-ner",
"base_model:finetune:KPF/KPF-bert-ner",
"endpoints_compatible",
"region:us"
] | token-classification | 2026-04-11T16:57:30Z | # townboy/kpfbert-kdpii
Korean PII token-classification model fine-tuned from `KPF/KPF-bert-ner` on a KDPII-style dialogue dataset.
## Dataset
- Source file: `연대1_PII_dataset_V3.json`
- Documents: `4981`
- Sentences: `53778`
- Positive PII sentences: `19037`
- Label count: `33`
## Training Setup
- Ma... | [] |
tanjumajerin/final-llama-3-all-fixed | tanjumajerin | 2025-08-24T15:25:01Z | 0 | 0 | peft | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B",
"base_model:adapter:meta-llama/Meta-Llama-3-8B",
"license:llama3",
"region:us"
] | null | 2025-08-24T11:31:26Z | <!-- 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. -->
# final-llama-3-all-fixed
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta... | [] |
professorsynapse/nexus-tools_sft22-kto2-Q8_0-GGUF | professorsynapse | 2025-12-02T20:45:31Z | 6 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:professorsynapse/nexus-tools_sft22-kto2",
"base_model:quantized:professorsynapse/nexus-tools_sft22-kto2",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-02T20:44:54Z | # professorsynapse/nexus-tools_sft22-kto2-Q8_0-GGUF
This model was converted to GGUF format from [`professorsynapse/nexus-tools_sft22-kto2`](https://huggingface.co/professorsynapse/nexus-tools_sft22-kto2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer ... | [] |
morturr/Mistral-7B-v0.1-DomainClassification-Negative-seed-42-2025-12-01 | morturr | 2025-12-01T15:14:30Z | 0 | 0 | peft | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-v0.1",
"base_model:adapter:mistralai/Mistral-7B-v0.1",
"license:apache-2.0",
"region:us"
] | null | 2025-12-01T15:14:20Z | <!-- 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. -->
# Mistral-7B-v0.1-DomainClassification-Negative-seed-42-2025-12-01
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1... | [] |
Sa74ll/smolvla_bimanual_pick_place | Sa74ll | 2026-03-03T18:39:54Z | 81 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:Sa74ll/bimanual_pick_and_place_vr",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-03T10:35:35Z | # 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... | [] |
Alkatt/LAVLA_S1_XII_cube | Alkatt | 2026-04-21T07:55:28Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"lavla",
"dataset:Alkatt/so_101_CubeToBowl_v3",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-21T07:55:10Z | # Model Card for lavla
<!-- 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.... | [] |
seywan1378/tts_hataw_MG | seywan1378 | 2025-12-03T14:05:19Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"speecht5",
"text-to-audio",
"generated_from_trainer",
"ckb",
"dataset:seywan1378/HatawTTS",
"base_model:microsoft/speecht5_tts",
"base_model:finetune:microsoft/speecht5_tts",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-to-audio | 2025-12-03T14:04:43Z | <!-- 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. -->
# SpeechT5_TTS_Hataw
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) ... | [] |
eLAND-Research/bge-m3-law | eLAND-Research | 2026-03-05T07:03:12Z | 31 | 0 | null | [
"safetensors",
"xlm-roberta",
"text-embeddings-inference",
"embeddings",
"legal",
"retrieval",
"fine-tuned",
"taiwanese-law",
"flagembedding",
"sentence-similarity",
"zh",
"arxiv:2402.03216",
"base_model:BAAI/bge-m3",
"base_model:finetune:BAAI/bge-m3",
"license:mit",
"region:us"
] | sentence-similarity | 2026-03-05T06:54:42Z | # bge-m3-law
A fine-tuned version of [BAAI/bge-m3](https://huggingface.co/BAAI/bge-m3) specialized for **Traditional Chinese legal document retrieval**. Given a natural-language legal scenario query, this model retrieves the most relevant statutory articles from a corpus of Taiwan law.
## Model Details
| Field | Val... | [] |
hZzy/mistral-7b-expo-7b-L2EXPO-25-08-try-new-data-7 | hZzy | 2025-09-08T14:57:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"expo",
"arxiv:2305.18290",
"base_model:hZzy/mistral-7b-sft-25-1",
"base_model:finetune:hZzy/mistral-7b-sft-25-1",
"endpoints_compatible",
"region:us"
] | null | 2025-09-08T03:42:15Z | # Model Card for mistral-7b-expo-7b-L2EXPO-25-08-try-new-data-7
This model is a fine-tuned version of [hZzy/mistral-7b-sft-25-1](https://huggingface.co/hZzy/mistral-7b-sft-25-1).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question ... | [
{
"start": 207,
"end": 210,
"text": "TRL",
"label": "training method",
"score": 0.7675022482872009
},
{
"start": 992,
"end": 995,
"text": "DPO",
"label": "training method",
"score": 0.7944986820220947
},
{
"start": 1288,
"end": 1291,
"text": "DPO",
"la... |
ovinduG/sinllama-nawarasa-lora | ovinduG | 2026-02-27T09:14:04Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-02-27T09:02:27Z | # Sinhala Nawarasa Emotion Classifier (SinLlama LoRA)
A Sinhala emotion classification model based on the classical **Nawarasa** framework.
This LoRA adapter is fine-tuned on top of `polyglots/SinLlama_v01`.
---
language:
- si
license: llama3
tags:
- text-classification
- emotion-recognition
- sinhala
- nawarasa
- ... | [] |
xummer/llama3-1-8b-belebele-lora-bam-latn | xummer | 2026-03-03T15:55:26Z | 10 | 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 | 2026-03-03T15:54:30Z | <!-- 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_bam_Latn
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama... | [
{
"start": 356,
"end": 379,
"text": "belebele_bam_Latn_train",
"label": "training method",
"score": 0.7192622423171997
}
] |
Prince2212/Mistral-7B-Instruct-v0.2 | Prince2212 | 2026-03-26T05:52:03Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"mistral",
"text-generation",
"finetuned",
"mistral-common",
"conversational",
"arxiv:2310.06825",
"license:apache-2.0",
"text-generation-inference",
"region:us"
] | text-generation | 2026-03-26T05:52:03Z | # Model Card for Mistral-7B-Instruct-v0.2
## Encode and Decode with `mistral_common`
```py
from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
from mistral_common.protocol.instruct.messages import UserMessage
from mistral_common.protocol.instruct.request import ChatCompletionRequest
m... | [] |
maxHPI90/multilingual-e5-base-iscedf-01 | maxHPI90 | 2026-02-23T18:04:14Z | 6 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:340",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:isy-thl/multilingual-e5-base-learning-outcome-skil... | sentence-similarity | 2026-02-23T17:38:26Z | # SentenceTransformer based on isy-thl/multilingual-e5-base-learning-outcome-skill-tuned
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [isy-thl/multilingual-e5-base-learning-outcome-skill-tuned](https://huggingface.co/isy-thl/multilingual-e5-base-learning-outcome-skill-tuned). It maps s... | [] |
mradermacher/Huihui-gemma-4-31B-it-abliterated-GGUF | mradermacher | 2026-04-18T14:49:56Z | 833 | 0 | transformers | [
"transformers",
"gguf",
"abliterated",
"uncensored",
"en",
"base_model:huihui-ai/Huihui-gemma-4-31B-it-abliterated",
"base_model:quantized:huihui-ai/Huihui-gemma-4-31B-it-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-17T05:23:23Z | ## 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/Qwen3.5-27B-heretic-i1-GGUF | mradermacher | 2026-02-27T07:27:48Z | 15,068 | 8 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:coder3101/Qwen3.5-27B-heretic",
"base_model:quantized:coder3101/Qwen3.5-27B-heretic",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-02-27T06:01:16Z | ## 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_... | [] |
mradermacher/Darwin-35B-A3B-Opus-GGUF | mradermacher | 2026-04-04T06:40:14Z | 2,487 | 2 | transformers | [
"transformers",
"gguf",
"merge",
"evolutionary-merge",
"darwin",
"darwin-v5",
"model-mri",
"reasoning",
"advanced-reasoning",
"chain-of-thought",
"thinking",
"qwen3.5",
"qwen",
"moe",
"mixture-of-experts",
"claude-opus",
"distillation",
"multimodal",
"vision-language",
"multili... | null | 2026-04-01T12:14:49Z | ## 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... | [] |
mrcuddle/Typescript-QWen2.5-Coder-3B-Instruct | mrcuddle | 2025-01-15T18:43:48Z | 9 | 2 | transformers | [
"transformers",
"pytorch",
"safetensors",
"qwen2",
"text-generation",
"axolotl",
"generated_from_trainer",
"conversational",
"dataset:mhhmm/typescript-instruct-20k",
"base_model:Qwen/Qwen2.5-Coder-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-Coder-3B-Instruct",
"license:other",
"text-gene... | text-generation | 2025-01-15T17:13:17Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
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