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 |
|---|---|---|---|---|---|---|---|---|---|---|
test-tax/Falcon-E-1.2-3B-Exp-prequantized | test-tax | 2026-04-30T11:10:07Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"axolotl",
"edge",
"bitnet",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-29T13:57:50Z | # Falcon-E-1.2-3B-Exp-prequantized
This is the model card of `Falcon-E-1.2-3B-Exp`, a ternary (1.58bits) language model trained on SFT agentic, and STEM data using [`axolotl`](https://github.com/axolotl-ai-cloud/axolotl) framework combined with [`onebitllm`](https://github.com/tiiuae/onebitllms) library.
The model ha... | [] |
kudzueye/boreal-flux-dev2 | kudzueye | 2026-01-06T22:46:32Z | 0 | 8 | null | [
"base_model:black-forest-labs/FLUX.2-dev",
"base_model:finetune:black-forest-labs/FLUX.2-dev",
"region:us"
] | null | 2025-11-30T18:01:00Z | # Flux Dev 2
<Gallery />
## Model description
# Boring Reality LoRA for Flux Dev 2
This LoRA is an early experimental training attempt at Flux Dev 2. The results are not perfect, but they should have at least limited improvement on Flux generations (distortion and disfigurement will increase with issues like text g... | [
{
"start": 2,
"end": 12,
"text": "Flux Dev 2",
"label": "training method",
"score": 0.8889228701591492
},
{
"start": 76,
"end": 86,
"text": "Flux Dev 2",
"label": "training method",
"score": 0.7728657722473145
},
{
"start": 142,
"end": 152,
"text": "Flux D... |
kangdawei/DAPO-8B | kangdawei | 2025-12-16T18:45:46Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"open-r1",
"dapo",
"trl",
"conversational",
"dataset:knoveleng/open-rs",
"arxiv:2503.14476",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Llama-... | text-generation | 2025-12-11T20:28:01Z | # Model Card for DAPO-8B
This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B) on the [knoveleng/open-rs](https://huggingface.co/datasets/knoveleng/open-rs) dataset.
It has been trained using [TRL](https://github.com/huggingfac... | [] |
baa-ai/Gemma-4-31B-it-RAM-29GB-MLX | baa-ai | 2026-04-15T13:17:39Z | 112 | 0 | mlx | [
"mlx",
"safetensors",
"gemma4",
"quantized",
"mixed-precision",
"base_model:google/gemma-4-31B-it",
"base_model:quantized:google/gemma-4-31B-it",
"license:gemma",
"4-bit",
"region:us"
] | null | 2026-04-13T23:13:27Z | # Gemma-4-31B-it — 29GB (MLX)
Mixed-precision quantized version of [google/gemma-4-31B-it](https://huggingface.co/google/gemma-4-31B-it) optimised by [baa.ai](https://baa.ai) using a proprietary Black Sheep AI method.
Per-tensor bit-width allocation via advanced sensitivity analysis with adjusted vision encoder a... | [] |
danielsanjosepro/ditflow_drawer_without_tact_v2 | danielsanjosepro | 2025-12-21T15:14:15Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"ditflow",
"dataset:LSY-lab/drawer_without_tact_v2",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-21T15:14:04Z | # Model Card for ditflow
<!-- 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://huggingfac... | [] |
dealignai/Gemma-4-31B-JANG_4M-Uncensored | dealignai | 2026-05-01T22:05:00Z | 19,299 | 20 | mlx | [
"mlx",
"safetensors",
"gemma4",
"abliterated",
"uncensored",
"crack",
"jang",
"text-generation",
"conversational",
"license:gemma",
"region:us"
] | text-generation | 2026-04-04T03:51:46Z | <p align="center">
<img src="dealign_logo.png" alt="dealign.ai" width="200"/>
</p>
<div align="center">
<img src="dealign_mascot.png" width="128" />
# Gemma 4 31B JANG_4M CRACK
**Abliterated Gemma 4 31B Dense — mixed precision, 18 GB**
93.7% HarmBench compliance with only -2.0% MMLU. Full abliteration of the dens... | [] |
qualcomm/PPE-Detection | qualcomm | 2026-04-28T06:49:05Z | 160 | 1 | pytorch | [
"pytorch",
"real_time",
"bu_iot",
"android",
"object-detection",
"license:other",
"region:us"
] | object-detection | 2024-10-21T23:27:00Z | 
# PPE-Detection: Optimized for Qualcomm Devices
Detect if a person is wearing personal protective equipments (PPE) in real-time. This model's architecture was developed by Qualcomm. The model w... | [] |
Hizaneko/lora_agent_nyan3.1.4 | Hizaneko | 2026-03-01T10:49:44Z | 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 | 2026-03-01T10:48:01Z | # lora_agent_nyan3.1.4
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-turn agent t... | [
{
"start": 53,
"end": 57,
"text": "LoRA",
"label": "training method",
"score": 0.8837066888809204
},
{
"start": 124,
"end": 128,
"text": "LoRA",
"label": "training method",
"score": 0.9140909314155579
},
{
"start": 170,
"end": 174,
"text": "LoRA",
"lab... |
Muapi/flux.1-d-soothing-atmosphere | Muapi | 2025-08-14T10:22:07Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-14T10:21:48Z | # Flux.1 D - Soothing Atmosphere
**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 = {"Conten... | [] |
LakshyAAAgrawal/continuous-thought-r11_rw_perstep_g1_ans256 | LakshyAAAgrawal | 2026-03-13T09:12:52Z | 24 | 0 | null | [
"safetensors",
"qwen3",
"qthink",
"continuous-thought",
"latent-reasoning",
"distillation",
"gsm8k",
"en",
"dataset:openai/gsm8k",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2026-03-13T07:26:59Z | # r11_rw_perstep_g1_ans256
**Best reward-weighted — correct-only per-step distillation (82.7%)**
- **Best reward-weighted result**: 82.7% on GSM8k
- Uses reward-weighted teacher (average over CORRECT rollouts only)
- Per-step distillation at every latent step with γ=1.0
- Trained with max_answer_len=256
## Overview
... | [] |
mradermacher/ProfanityFilter-GGUF | mradermacher | 2025-09-10T23:17:30Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:SorinAlexB/ProfanityFilter",
"base_model:quantized:SorinAlexB/ProfanityFilter",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-09-10T22:07:59Z | ## 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 qu... | [] |
ConnorBrug/my_awesome_eli5_clm-model | ConnorBrug | 2026-04-13T04:02:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:distilbert/distilgpt2",
"base_model:finetune:distilbert/distilgpt2",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-13T03:44:54Z | <!-- 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_eli5_clm-model
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilg... | [] |
Sambhavnoobcoder/gpt2-test-quantization-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8 | Sambhavnoobcoder | 2026-01-10T20:06:37Z | 1 | 0 | null | [
"pytorch",
"gpt2",
"quantized",
"quanto",
"int8",
"automatic-quantization",
"base_model:Sambhavnoobcoder/gpt2-test-quantization-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8",
"base_model:finetune:Sambhavnoobcoder/gpt2-test-quantization-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8-Qua... | null | 2026-01-10T20:06:34Z | # gpt2-test-quantization-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8 - Quanto int8
This is an **automatically quantized** version of [Sambhavnoobcoder/gpt2-test-quantization-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8-Quanto-int8](https://huggingface.co/Sambhavnoobcoder/gpt2-test-quantization-Quant... | [] |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-3d-500K-50K-0.2-reverse-padzero-plus-mul-sub-99-64D-1L-8H-256I | arithmetic-circuit-overloading | 2026-02-27T03:32:50Z | 153 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.3-70B-Instruct",
"base_model:finetune:meta-llama/Llama-3.3-70B-Instruct",
"license:llama3.3",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-27T03:22:45Z | <!-- 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. -->
# Llama-3.3-70B-Instruct-3d-500K-50K-0.2-reverse-padzero-plus-mul-sub-99-64D-1L-8H-256I
This model is a fine-tuned version of [meta... | [] |
jiayicheng/bcplusop_15_10 | jiayicheng | 2026-05-03T22:39:20Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-05-03T22:36:08Z | <!-- 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. -->
# train_output
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the sft_f25helios_del... | [] |
sathiiii/medonethinker-qwen3vl-8b-lora-r64 | sathiiii | 2026-02-18T11:51:37Z | 4 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:/vast/users/muhammad.haris/Sathira/Med-OneThinker-R1/Qwen3-VL-8B-Instruct",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-VL-8B-Instruct",
"base_model:adapter:Qwen/Qwen3-VL-8B-Instruct",
"license:ot... | text-generation | 2026-02-18T11:29:36Z | <!-- 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. -->
# medonethinker_sft_lora_qwen3vl_8b_r64_sn
This model is a fine-tuned version of [Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen... | [] |
Mr-Corentin/myhaiku-gemma-3-270m-it | Mr-Corentin | 2025-10-20T12:53:17Z | 4 | 1 | null | [
"safetensors",
"gemma3_text",
"text-generation",
"haiku",
"poetry",
"gemma",
"fine-tuning",
"lora-merged",
"conversational",
"en",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"region:us"
] | text-generation | 2025-10-16T11:39:47Z | # myhaiku — Fine-tuned Gemma 3 270M (Haiku Generator)
This model is a fine-tuned version of `google/gemma-3-270m-it` trained to generate **English haiku poems**.
## Description
The model was fine-tuned using a dataset of approximately 4000 *traditional Japanese haiku* translated into English, where each example cont... | [] |
rbelanec/train_cb_42_1760637524 | rbelanec | 2025-10-16T18:04:17Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"llama-factory",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | text-generation | 2025-10-16T17:59:17Z | <!-- 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. -->
# train_cb_42_1760637524
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-ll... | [] |
ttsds/e2-tts | ttsds | 2026-01-29T18:16:03Z | 0 | 1 | ttsdb | [
"ttsdb",
"tts",
"text-to-speech",
"speech-synthesis",
"voice-cloning",
"eng",
"zho",
"license:cc-by-nc-4.0",
"region:us"
] | text-to-speech | 2026-01-29T15:22:41Z | # E2 TTS
> **This is a mirror of the original weights for use with [TTSDB](https://github.com/ttsds/ttsdb).**
>
> Original weights: [https://huggingface.co/SWivid/E2-TTS](https://huggingface.co/SWivid/E2-TTS)
> Original code: [https://github.com/SWivid/F5-TTS](https://github.com/SWivid/F5-TTS)
A non-autoregressive ... | [] |
bearzi/MiniMax-M2.7-JANG_6K | bearzi | 2026-05-01T00:07:06Z | 17 | 0 | mlx | [
"mlx",
"safetensors",
"minimax_m2",
"jang",
"jang-quantized",
"JANG_6K",
"mixed-precision",
"apple-silicon",
"text-generation",
"conversational",
"custom_code",
"base_model:MiniMaxAI/MiniMax-M2.7",
"base_model:finetune:MiniMaxAI/MiniMax-M2.7",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-30T23:52:30Z | # MiniMax-M2.7-JANG_6K
JANG adaptive mixed-precision MLX quantization produced via [vmlx / jang-tools](https://github.com/jjang-ai/jangq).
- **Quantization:** 5.94b avg, profile JANG_6K, method mse-all, calibration activations
- **Profile:** JANG_6K
- **Format:** JANG v2 MLX safetensors
- **Compatible with:** vmlx, M... | [] |
YanLabs/gemma-3-4b-it-abliterated-normpreserve-GGUF | YanLabs | 2025-12-09T08:27:38Z | 93 | 1 | null | [
"gguf",
"text-generation",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-12-09T07:57:14Z | # Gemma 3 4B Instruct - Norm-Preserving Abliterated
This is an abliterated version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it) using the norm-preserving biprojected abliteration technique.
**⚠️ Warning**: Safety guardrails and refusal mechanisms have been removed through abliteration. This ... | [] |
dcostenco/prism-coder-14b | dcostenco | 2026-05-04T21:49:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"function-calling",
"tool-use",
"aac",
"accessibility",
"prism",
"synalux",
"bfcl",
"conversational",
"en",
"es",
"fr",
"pt",
"de",
"zh",
"ja",
"ko",
"ru",
"ar",
"ro",
"uk",
"base_model:Qwen/Qwen2.5-Coder-14B-... | text-generation | 2026-05-04T21:10:48Z | # Prism-Coder 14B — Function Calling + AAC Sibling (32K context)
A fine-tune of **Qwen2.5-Coder-14B-Instruct** released **2026-05-04** as a sibling to [`prism-coder-7b`](https://huggingface.co/dcostenco/prism-coder-7b). Auto-routed for paid-tier medium-length AAC queries via the Synalux portal — keeps inference local ... | [
{
"start": 812,
"end": 816,
"text": "BFCL",
"label": "training method",
"score": 0.8572153449058533
},
{
"start": 1049,
"end": 1053,
"text": "BFCL",
"label": "training method",
"score": 0.8395145535469055
},
{
"start": 1191,
"end": 1195,
"text": "BFCL",
... |
Ujjwal-Tyagi/GLM-4.7-Flash | Ujjwal-Tyagi | 2026-03-29T08:43:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"glm4_moe_lite",
"text-generation",
"conversational",
"en",
"zh",
"arxiv:2508.06471",
"license:mit",
"eval-results",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-29T08:43:33Z | # GLM-4.7-Flash
<div align="center">
<img src=https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg width="15%"/>
</div>
<p align="center">
👋 Join our <a href="https://discord.gg/QR7SARHRxK" target="_blank">Discord</a> community.
<br>
📖 Check out the GLM-4.7 <a href="https:... | [] |
prem-research/Funcdex-0.6B-todoist | prem-research | 2025-11-15T09:01:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"agent",
"Agentic Learning",
"tool use",
"BFCL",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-11-12T21:39:49Z | [](https://huggingface.co/collections/prem-research/funcdex) [](https://huggingface.co/datasets/prem-research/Funcdex-MT-Function-Calling... | [] |
mit-han-lab/dc-ae-f128c512-mix-1.0-diffusers | mit-han-lab | 2025-01-06T14:56:02Z | 47 | 4 | diffusers | [
"diffusers",
"safetensors",
"arxiv:2410.10733",
"region:us"
] | null | 2024-12-05T13:33:58Z | # Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models
[[paper](https://arxiv.org/abs/2410.10733)] [[GitHub](https://github.com/mit-han-lab/efficientvit)]
<p align="center">
<b> Figure 1: We address the reconstruction accuracy drop of high spatial-compression auto... | [
{
"start": 1151,
"end": 1172,
"text": "Residual Autoencoding",
"label": "training method",
"score": 0.7259621024131775
},
{
"start": 1358,
"end": 1394,
"text": "Decoupled High-Resolution Adaptation",
"label": "training method",
"score": 0.8354374170303345
}
] |
EleutherAI/neox-ckpt-pythia-160m-seed3 | EleutherAI | 2026-02-12T13:49:46Z | 0 | 0 | null | [
"pytorch",
"causal-lm",
"pythia",
"polypythias",
"gpt-neox",
"en",
"dataset:EleutherAI/pile",
"dataset:EleutherAI/pile-preshuffled-seeds",
"arxiv:2503.09543",
"license:apache-2.0",
"region:us"
] | null | 2026-02-12T13:49:45Z | # Pythia-160M-seed3 GPT-NeoX Checkpoints
This repository contains the raw [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) training checkpoints for [Pythia-160M-seed3](https://huggingface.co/EleutherAI/pythia-160m-seed3), part of the [PolyPythias](https://huggingface.co/collections/EleutherAI/polypythias) suite. The... | [] |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-3d-1M-100K-0.2-reverse-padzero-plus-mul-sub-99-64D-2L-8H-256I | arithmetic-circuit-overloading | 2026-02-27T01:46:42Z | 480 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.3-70B-Instruct",
"base_model:finetune:meta-llama/Llama-3.3-70B-Instruct",
"license:llama3.3",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-27T01:14:57Z | <!-- 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-3.3-70B-Instruct-3d-1M-100K-0.2-reverse-padzero-plus-mul-sub-99-64D-2L-8H-256I
This model is a fine-tuned version of [meta-... | [] |
Muapi/azure-sketch-illustration | Muapi | 2025-08-18T17:41:15Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-18T17:39:58Z | # Azure Sketch Illustration
**Base model**: Flux.1 D
**Trained words**: ArsMJStyle, AzureSketch
## 🧠 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"
... | [] |
OvercastLab/Quark-50m-Instruct | OvercastLab | 2026-04-28T08:00:53Z | 2,397 | 2 | null | [
"pytorch",
"safetensors",
"llama",
"smol",
"pretraining",
"instruct",
"50M",
"causal-lm",
"gqa",
"swiglu",
"rmsnorm",
"text-generation",
"conversational",
"en",
"code",
"dataset:HuggingFaceTB/smollm-corpus",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-22T18:58:49Z | # Quark-50m-Instruct
**Quark-50m-Instruct** is a small (≈56M parameters) decoder-only language model, fine-tuned for instruction following.
It is built on the same architecture of “SmolLM” family and was fully pretrained on 5 billion tokens from
[HuggingFaceTB/smollm‑corpus](https://huggingface.co/datasets/HuggingFace... | [] |
mradermacher/Disco-GGUF | mradermacher | 2025-11-10T14:10:20Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"llama-factory",
"en",
"base_model:ladmol/Disco",
"base_model:quantized:ladmol/Disco",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-10T13:55:26Z | ## 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... | [] |
garrison/Magidonia-24B-v4.3-mlx-3Bit | garrison | 2025-12-17T21:22:13Z | 7 | 0 | mlx | [
"mlx",
"safetensors",
"mistral",
"base_model:TheDrummer/Magidonia-24B-v4.3",
"base_model:quantized:TheDrummer/Magidonia-24B-v4.3",
"3-bit",
"region:us"
] | null | 2025-12-17T21:20:51Z | # garrison/Magidonia-24B-v4.3-mlx-3Bit
The Model [garrison/Magidonia-24B-v4.3-mlx-3Bit](https://huggingface.co/garrison/Magidonia-24B-v4.3-mlx-3Bit) was converted to MLX format from [TheDrummer/Magidonia-24B-v4.3](https://huggingface.co/TheDrummer/Magidonia-24B-v4.3) using mlx-lm version **0.28.3**.
## Use with mlx
... | [] |
bartowski/OpenCoder-8B-Instruct-GGUF | bartowski | 2024-11-11T02:21:05Z | 210 | 10 | null | [
"gguf",
"text-generation",
"en",
"zh",
"dataset:OpenCoder-LLM/opencoder-sft-stage1",
"dataset:OpenCoder-LLM/opencoder-sft-stage2",
"base_model:infly/OpenCoder-8B-Instruct",
"base_model:quantized:infly/OpenCoder-8B-Instruct",
"license:other",
"endpoints_compatible",
"region:us",
"conversational... | text-generation | 2024-11-11T01:49:36Z | ## Llamacpp imatrix Quantizations of OpenCoder-8B-Instruct
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b4014">b4014</a> for quantization.
Original model: https://huggingface.co/infly/OpenCoder-8B-Instruct
All quants made u... | [] |
zacoriandre/backrooms_poolrooms_1_5 | zacoriandre | 2025-12-02T17:13:40Z | 5 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:ckpt/sd15",
"base_model:adapter:ckpt/sd15",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2025-12-02T16:31:32Z | # Backrooms + POOLROOMS version 1.5
<Gallery />
## Model description
This model is a custom 1.5 LoRA trained on screenshots from backrooms games, artworks and 3D rendered images from different web sources.
The images were trained on a 512x512 resolution.
Copyright (c) 2022 Robin Rombach and Patrick Esser and cont... | [] |
pkulium/easy_deepocr | pkulium | 2025-11-04T22:21:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llava_llama",
"ocr",
"vision-language",
"qwen2-vl",
"vila",
"multimodal",
"image-text-to-text",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-11-04T22:09:14Z | # Easy DeepOCR - VILA-Qwen2-VL-8B
A vision-language model fine-tuned for OCR tasks, based on VILA architecture with Qwen2-VL-8B as the language backbone.
## Model Description
This model combines:
- **Language Model**: Qwen2-VL-8B
- **Vision Encoders**: SAM + CLIP
- **Architecture**: VILA (Visual Language Adapter)
- ... | [] |
chloeli/qwen-3-14b-value-aug-spec-msm | chloeli | 2026-05-01T11:37:40Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"base_model:Qwen/Qwen3-14B",
"base_model:adapter:Qwen/Qwen3-14B",
"license:mit",
"region:us"
] | null | 2026-05-01T11:37:29Z | # qwen-3-14b-value-aug-spec-msm
A LoRA adapter for [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B), trained using model spec midtraining (MSM) only.
- **Base model:** Qwen/Qwen3-14B
- **LoRA rank:** 64
- **LoRA alpha:** 128
- **Target modules:** q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
#... | [
{
"start": 147,
"end": 150,
"text": "MSM",
"label": "training method",
"score": 0.7539972066879272
}
] |
barozp/Qwen-3.5-28B-A3B-REAP-GGUF | barozp | 2026-03-29T14:16:09Z | 548 | 3 | null | [
"gguf",
"quantized",
"qwen3_5_moe",
"moe",
"pruning",
"reap",
"qwen3",
"expert-pruning",
"llama-cpp",
"en",
"arxiv:2510.13999",
"base_model:0xSero/Qwen-3.5-28B-A3B-REAP",
"base_model:quantized:0xSero/Qwen-3.5-28B-A3B-REAP",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"... | null | 2026-03-28T19:33:29Z | # Qwen-3.5-28B-A3B-REAP — GGUF Q4_K_M
GGUF quantization of [0xSero/Qwen-3.5-28B-A3B-REAP](https://huggingface.co/0xSero/Qwen-3.5-28B-A3B-REAP), a pruned variant of [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B) using the REAP (Refined Expert Activation Pruning) method.
## Available Files
| File ... | [] |
zhiyuanyan1/UAE | zhiyuanyan1 | 2025-09-13T17:53:01Z | 3 | 1 | transformers | [
"transformers",
"diffusers",
"safetensors",
"Text-to-Image, Image-to-Text",
"text-to-image",
"en",
"arxiv:2509.09666",
"base_model:stabilityai/stable-diffusion-3.5-large",
"base_model:finetune:stabilityai/stable-diffusion-3.5-large",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-to-image | 2025-09-11T02:21:40Z | # UAE
### Paper
This is the official pre-trained weight of the paper "Can Understanding and Generation Truly Benefit Together -- or Just Coexist?" (https://arxiv.org/abs/2509.09666).
### Github
You can access the official code in the: https://github.com/PKU-YuanGroup/UAE.
### Abstract
The field’s long-standing split ... | [] |
YuxinJiang/qwen3_30b_a3b_2507_sft_rebench_real_2395 | YuxinJiang | 2026-02-06T21:30:33Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"llama-factory",
"generated_from_trainer",
"conversational",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-06T03:37:54Z | <!-- 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. -->
# qwen3_30b_a3b_2507_sft_rebench_real_2395
This model was trained from scratch on an unknown dataset.
## Model description
More i... | [] |
gsjang/ko-koni-llama3-8b-instruct-20240729-x-meta-llama-3-8b-instruct-fusion_merge | gsjang | 2025-09-11T13:51:08Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:KISTI-KONI/KONI-Llama3-8B-Instruct-20240729",
"base_model:merge:KISTI-KONI/KONI-Llama3-8B-Instruct-20240729",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:merge:meta-lla... | text-generation | 2025-09-11T13:48:10Z | # ko-koni-llama3-8b-instruct-20240729-x-meta-llama-3-8b-instruct-fusion_merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the KV-OT Merge (FFN Key–Value aware OT) merge method using [meta-lla... | [
{
"start": 255,
"end": 266,
"text": "KV-OT Merge",
"label": "training method",
"score": 0.8672242164611816
},
{
"start": 756,
"end": 767,
"text": "kv_ot_merge",
"label": "training method",
"score": 0.7260460257530212
}
] |
profpeng/Pussylicking | profpeng | 2026-01-23T18:48:27Z | 184 | 2 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:Wan-AI/Wan2.2-I2V-A14B",
"base_model:adapter:Wan-AI/Wan2.2-I2V-A14B",
"region:us"
] | text-to-image | 2026-01-23T18:47:09Z | # pussylicking
<Gallery />
## Model description
dynamic camera movement pivoting left, revealing a woman's body from a side angle, her legs spread. Close-up from the left side on her vulva. A second woman walks into the frame from the right side, leaning in. Her tongue flicks and sucks rhythmically on the clito... | [] |
Thrillcrazyer/Qwen1.5_THIP_1214 | Thrillcrazyer | 2025-12-15T02:30:12Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"grpo",
"trl",
"conversational",
"dataset:DeepMath-103k",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-1.5B-Instruct",
"text-generation-inference",
"endpoi... | text-generation | 2025-12-14T17:55:03Z | # Model Card for Qwen1.5_THIP_1214
This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the [DeepMath-103k](https://huggingface.co/datasets/DeepMath-103k) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
`... | [] |
ooeoeo/opus-mt-cs-de-ct2-float16 | ooeoeo | 2026-04-17T12:01:48Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"custom",
"license:apache-2.0",
"region:us"
] | translation | 2026-04-17T12:01:24Z | # ooeoeo/opus-mt-cs-de-ct2-float16
CTranslate2 float16 quantized version of `Helsinki-NLP/opus-mt-cs-de`.
Converted for use in the [ooeoeo](https://ooeoeo.com) desktop engine
with the `opus-mt-server` inference runtime.
## Source
- Upstream model: [Helsinki-NLP/opus-mt-cs-de](https://huggingface.co/Helsinki-NLP/opu... | [] |
JH-C-k/mistral-7b-continual-sft-arce | JH-C-k | 2026-04-14T07:21:45Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:mistralai/Mistral-7B-v0.1",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"base_model:mistralai/Mistral-7B-v0.1",
"region:us"
] | text-generation | 2026-04-14T06:35:07Z | # Model Card for exp10-retrain
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
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... | [] |
lava123456/7058bf29-0cfa-4536-8808-eba5f753e25d | lava123456 | 2026-01-23T13:34:07Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:qualiaadmin/53",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-23T13:33:39Z | # 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... | [] |
HISEHAN/bert-base-nsmc | HISEHAN | 2025-08-27T06:27:44Z | 4 | 0 | transformers | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"base_model:klue/bert-base",
"base_model:finetune:klue/bert-base",
"license:cc-by-sa-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-08-27T06:27:13Z | <!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# bert-base-nsmc
This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on an unknown dataset.
It ... | [
{
"start": 876,
"end": 882,
"text": "WarmUp",
"label": "training method",
"score": 0.7122904658317566
},
{
"start": 1254,
"end": 1260,
"text": "WarmUp",
"label": "training method",
"score": 0.7392774224281311
}
] |
Yuivdldk/gemma-3-12b-it-lora-bf16 | Yuivdldk | 2026-03-02T04:39:25Z | 1 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:google/gemma-3-12b-it",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:google/gemma-3-12b-it",
"license:gemma",
"region:us"
] | text-generation | 2026-03-02T03:59:35Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gemma-3-12b-it-lora
This model is a fine-tuned version of [google/gemma-3-12b-it](https://huggingface.co/google/gemma-3-12b-it) o... | [] |
DeepBrainz/DeepBrainz-R1-0.6B | DeepBrainz | 2026-02-05T15:12:44Z | 14 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"deepbrainz",
"reasoning",
"mathematics",
"code",
"enterprise",
"0.6b",
"long-context",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-03T21:54:54Z | # DeepBrainz-R1-0.6B
**DeepBrainz-R1-0.6B** is a compact, high-performance reasoning model engineered by **DeepBrainz AI & Labs**. It is part of the **DeepBrainz-R1 Series**, designed to deliver frontier-class reasoning capabilities in cost-effective parameter sizes.
This variant features a **32,768 token context win... | [] |
Alelcv27/Qwen-7B-Slerp-v1 | Alelcv27 | 2026-01-29T13:53:20Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:Alelcv27/Qwen2.5-7B-Instruct-Code",
"base_model:merge:Alelcv27/Qwen2.5-7B-Instruct-Code",
"base_model:Alelcv27/Qwen2.5-7B-Instruct-Math-CoT",
"base_model:merge:Alelcv27/Qwen2.5-7B-Instru... | text-generation | 2026-01-29T13:31:55Z | # Qwen-7B-Slerp-v1
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
### Models Merged
The following models were included in the mer... | [] |
KhaledReda/all-MiniLM-L6-v27-pair_score | KhaledReda | 2026-01-20T17:09:46Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:153453064",
"loss:CoSENTLoss",
"en",
"dataset:KhaledReda/pairs_with_scores_v23_typos_and_false_negatives",
"arxiv:1908.10084",
"base_model:KhaledReda/... | sentence-similarity | 2026-01-19T15:31:20Z | # all-MiniLM-L6-v27-pair_score
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [KhaledReda/all-MiniLM-L6-v26-pair_score](https://huggingface.co/KhaledReda/all-MiniLM-L6-v26-pair_score) on the [pairs_with_scores_v23_typos_and_false_negatives](https://huggingface.co/datasets/KhaledReda/pair... | [] |
minhwantttt/groot-furniturebench | minhwantttt | 2026-04-09T19:55:58Z | 72 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"groot",
"dataset:minhwantttt/furniturebench-all",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-08T11:58:41Z | # Model Card for groot
<!-- 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.... | [] |
Userb1az/DeepSeek-Coder-V2-Lite-Instruct-GGUF | Userb1az | 2025-11-07T08:22:01Z | 47 | 0 | null | [
"gguf",
"arxiv:2401.06066",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-07T08:01:59Z | <!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-V2" />
</div>
<hr>
<div align="center" style="line-... | [] |
kojogyaase/bert-finetuned-ner | kojogyaase | 2026-01-22T19:00:14Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"base_model:google-bert/bert-base-cased",
"base_model:finetune:google-bert/bert-base-cased",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | token-classification | 2026-01-22T15:59:38Z | <!-- 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. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll20... | [] |
mradermacher/ide-code-retrieval-qwen3-0.6b-GGUF | mradermacher | 2026-04-03T14:51:57Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"sentence-transformers",
"sentence-similarity",
"feature-extraction",
"code-retrieval",
"embeddings",
"en",
"dataset:aysinghal/code-retrieval-training-dataset",
"base_model:aysinghal/ide-code-retrieval-qwen3-0.6b",
"base_model:quantized:aysinghal/ide-code-retrieval-qwen3-... | feature-extraction | 2026-04-03T14:43:02Z | ## 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... | [] |
AlesioRFM/improqwen2 | AlesioRFM | 2026-04-24T22:27:02Z | 0 | 0 | null | [
"gguf",
"qwen3_5",
"llama.cpp",
"unsloth",
"vision-language-model",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-24T22:26:34Z | # improqwen2 : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf AlesioRFM/improqwen2 --jinja`
- For multimodal models: `llama-mtmd-cli -hf AlesioRFM/improqwen2 --jinja`
## Available Model files... | [
{
"start": 82,
"end": 89,
"text": "Unsloth",
"label": "training method",
"score": 0.7478818893432617
},
{
"start": 120,
"end": 127,
"text": "unsloth",
"label": "training method",
"score": 0.82794189453125
},
{
"start": 452,
"end": 459,
"text": "unsloth",
... |
tharunrega/qwen2.5-1.5b-finance-dpo | tharunrega | 2026-04-12T14:34:21Z | 0 | 0 | peft | [
"peft",
"safetensors",
"gguf",
"base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct",
"dpo",
"lora",
"transformers",
"trl",
"text-generation",
"conversational",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-12T14:32:19Z | # Model Card for qwen-finance-dpo
This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-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 machi... | [
{
"start": 181,
"end": 184,
"text": "TRL",
"label": "training method",
"score": 0.7633991241455078
},
{
"start": 693,
"end": 696,
"text": "DPO",
"label": "training method",
"score": 0.8293151259422302
},
{
"start": 1002,
"end": 1005,
"text": "DPO",
"la... |
mradermacher/Starlit-Shadow-12B-Heretic-GGUF | mradermacher | 2026-03-18T21:40:06Z | 588 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Sorihon/Starlit-Shadow-12B-Heretic",
"base_model:quantized:Sorihon/Starlit-Shadow-12B-Heretic",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-18T20:25:06Z | ## 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... | [] |
anemll/anemll-google-gemma-3-1b-it-ctx4096_0.3.4 | anemll | 2026-01-30T22:50:16Z | 10 | 1 | null | [
"gemma",
"coreml",
"ANE",
"LLaMA",
"Qwen",
"DeepSeek",
"Gemma",
"Apple",
"Apple Neural Engine",
"DeepHermes",
"license:mit",
"region:us"
] | null | 2026-01-28T22:17:48Z | # ANEMLL
## Apple Neural Engine Optimized
**ANEMLL** (pronounced like "animal") is an open-source project focused on accelerating the porting of Large Language Models (LLMs) to tensor processors, starting with the Apple Neural Engine (ANE).
The goal is to provide a fully open-source pipeline from model conversion to... | [] |
mradermacher/CORE2-llama-3.2-3b-MATH-GGUF | mradermacher | 2025-09-22T10:20:20Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"trl",
"grpo",
"hf_jobs",
"en",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-22T10:05:32Z | ## 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... | [] |
Dexmal/DM0-table30_pour_fries_into_plate | Dexmal | 2026-02-09T09:41:14Z | 6 | 0 | null | [
"safetensors",
"dexbotic_dm0",
"license:cc",
"region:us"
] | null | 2026-02-08T15:08:15Z | This model is a DM0 supervised fine-tuned checkpoint of RoboChallenge pour_fries_into_plate task.
| Model | Description | Input Images | Action Dim | Model Size |
| - | - ... | [] |
flexitok/unigram_por_Latn_32000 | flexitok | 2026-02-23T03:19:50Z | 0 | 0 | null | [
"tokenizer",
"unigram",
"flexitok",
"fineweb2",
"por",
"license:mit",
"region:us"
] | null | 2026-02-23T03:19:50Z | # UnigramLM Tokenizer: por_Latn (32K)
A **UnigramLM** tokenizer trained on **por_Latn** data from Fineweb-2-HQ.
## Training Details
| Parameter | Value |
|-----------|-------|
| Algorithm | UnigramLM |
| Language | `por_Latn` |
| Target Vocab Size | 32,000 |
| Final Vocab Size | 0 |
| Pre-tokenizer | ByteLevel |
| N... | [] |
dgrauet/ernie-image-pe-mlx | dgrauet | 2026-04-20T21:13:08Z | 0 | 0 | mlx | [
"mlx",
"mlx-forge",
"apple-silicon",
"safetensors",
"base_model:baidu/ERNIE-Image-Turbo",
"base_model:finetune:baidu/ERNIE-Image-Turbo",
"license:apache-2.0",
"region:us"
] | null | 2026-04-20T20:37:23Z | # dgrauet/ernie-image-pe-mlx
MLX format conversion of [baidu/ERNIE-Image-Turbo](https://huggingface.co/baidu/ERNIE-Image-Turbo).
Converted with [mlx-forge](https://github.com/dgrauet/mlx-forge).
## Usage
These weights can be used with [ernie-image-mlx](https://github.com/dgrauet/ernie-image-mlx).
```bash
pip insta... | [] |
the-fall-of-man/didact-plump-hare-v1beta2-mxfp8 | the-fall-of-man | 2026-03-04T03:54:57Z | 47 | 0 | mlx | [
"mlx",
"safetensors",
"gpt_oss",
"sillytavern",
"roleplaying",
"creative writing",
"text-generation",
"conversational",
"en",
"8-bit",
"region:us"
] | text-generation | 2026-03-03T16:57:17Z | ## Didact Plump v1 beta (mk IV)
An improvement on didact plump, but by no means completed.
Short stats:
- 35MTok of personal data;
- 4 rounds of ORPO fine tuning towards better roleplay
- A decent attempt, so far, to get a GPT-OSS model to roleplay.
Quirks:
- Needs better stop token training (I suggest "<|start|>use... | [] |
wikilangs/an | wikilangs | 2026-01-03T17:05:58Z | 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-romance_iberian",
"t... | text-generation | 2025-12-27T06:02:08Z | # Aragonese - Wikilangs Models
## Comprehensive Research Report & Full Ablation Study
This repository contains NLP models trained and evaluated by Wikilangs, specifically on **Aragonese** Wikipedia data.
We analyze tokenizers, n-gram models, Markov chains, vocabulary statistics, and word embeddings.
## 📋 Repository ... | [
{
"start": 1298,
"end": 1319,
"text": "Tokenizer Compression",
"label": "training method",
"score": 0.7058837413787842
}
] |
bmeyer2025/tiny-gpt-shakespeare | bmeyer2025 | 2026-03-31T19:30:55Z | 357 | 0 | null | [
"pytorch",
"transformer",
"language-model",
"from-scratch",
"educational",
"shakespeare",
"rope",
"swiglu",
"rmsnorm",
"kv-cache",
"text-generation",
"en",
"dataset:tiny-shakespeare",
"arxiv:2104.09864",
"arxiv:2002.05202",
"arxiv:1910.07467",
"license:mit",
"region:us"
] | text-generation | 2026-03-31T19:10:51Z | # tiny-gpt-shakespeare
A 10M parameter decoder-only transformer trained on the Tiny Shakespeare dataset. Built from scratch in PyTorch as an educational project — no pretrained weights or external libraries used for the model itself.
## Model Description
- **Architecture:** Decoder-only transformer with modern compo... | [] |
leledeyuan/pusht1M | leledeyuan | 2025-09-19T17:42:36Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:leledeyuan/pusht",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-19T17:42:13Z | # 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 ... | [] |
nikhil061307/clinical-classifier-self-contained | nikhil061307 | 2025-09-04T15:20:47Z | 0 | 0 | null | [
"safetensors",
"clinical_classification",
"region:us"
] | null | 2025-09-04T15:09:36Z | # Clinical Entity Classification Model (Self-Contained)
This is a self-contained clinical entity classification model that predicts whether medical entities are:
- **Absent**: The condition/entity is not present
- **Hypothetical**: The condition/entity might be present (uncertain)
- **Present**: The condition/entity i... | [] |
shuhei25/act_vfolding | shuhei25 | 2025-12-18T11:32:02Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:shuhei25/VFolding100_in_one_go",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-18T11:31:47Z | # 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":... |
hssling/derm-analyzer-adapter | hssling | 2026-02-24T16:18:43Z | 27 | 0 | peft | [
"peft",
"safetensors",
"dermatology",
"medical",
"vision-language-model",
"lora",
"indian-health",
"en",
"dataset:marmal88/skin_cancer",
"dataset:pvlinhk/ISIC2019-full",
"base_model:Qwen/Qwen2-VL-2B-Instruct",
"base_model:adapter:Qwen/Qwen2-VL-2B-Instruct",
"license:apache-2.0",
"region:us... | null | 2026-02-24T16:18:36Z | # DermaAI LoRA Adapter — Indian Skin Type Tuned
Fine-tuned LoRA adapter on top of `Qwen2-VL-2B-Instruct` for clinical dermatological diagnosis
with a specific focus on **South Asian skin types (Fitzpatrick IV–VI)** and Indian treatment protocols.
## Training Data
- **HAM10000** (marmal88/skin_cancer): 10,015 dermosco... | [] |
ctaguchi/ssc-bas-mms-model-mix-adapt-max2 | ctaguchi | 2025-12-08T22:22:20Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/mms-1b-all",
"base_model:finetune:facebook/mms-1b-all",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-12-08T09:47:25Z | <!-- 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. -->
# ssc-bas-mms-model-mix-adapt-max2
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-... | [] |
priorcomputers/qwen2.5-14b-instruct-cn-ideation-kr0.2-a0.1-creative | priorcomputers | 2026-02-11T04:23:12Z | 1 | 0 | null | [
"safetensors",
"qwen2",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-11T04:20:48Z | # qwen2.5-14b-instruct-cn-ideation-kr0.2-a0.1-creative
This is a **CreativityNeuro (CN)** modified version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct).
## Model Details
- **Base Model**: Qwen/Qwen2.5-14B-Instruct
- **Modification**: CreativityNeuro weight scaling
- **Prompt Set**... | [] |
patrickamadeus/nanoVLM-cauldron-step-1000 | patrickamadeus | 2026-02-10T04:03:45Z | 0 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"research",
"image-text-to-text",
"license:mit",
"region:us"
] | image-text-to-text | 2026-02-10T04:03:02Z | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
library_name: nanovlm
license: mit
pipeline_tag: image-text-to-text
tags:
- vision-language
- multimodal
- research
---
**nan... | [] |
edmon03/edtonai-scorer | edmon03 | 2026-04-11T12:25:40Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"cross-encoder",
"reranker",
"generated_from_trainer",
"dataset_size:5616",
"loss:BinaryCrossEntropyLoss",
"text-ranking",
"arxiv:1908.10084",
"base_model:cross-encoder/mmarco-mMiniLMv2-L12-H384-v1",
"base_model:finetune:cross-encoder/mmar... | text-ranking | 2026-04-11T12:24:29Z | # CrossEncoder based on cross-encoder/mmarco-mMiniLMv2-L12-H384-v1
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [cross-encoder/mmarco-mMiniLMv2-L12-H384-v1](https://huggingface.co/cross-encoder/mmarco-mMiniLMv2-L12-H384-v1) using the [sentence-transformers](... | [] |
Sp1keeee/qwen3vl-dino-lora | Sp1keeee | 2026-01-25T05:49:49Z | 0 | 0 | null | [
"safetensors",
"lora",
"qwen3-vl",
"game-ai",
"computer-vision",
"zh",
"en",
"license:apache-2.0",
"region:us"
] | null | 2026-01-25T05:42:46Z | # Qwen3-VL Chrome Dinosaur LoRA
基于 Qwen3-VL-2B 的 LoRA 微调权重，用于玩 Chrome 恐龙游戏。
## 使用方法
```python
from transformers import Qwen3VLForConditionalGeneration
from peft import PeftModel
# 加载基础模型
base_model = Qwen3VLForConditionalGeneration.from_pretrained("Qwen/Qwen3-VL-2B")
# 加载 LoRA 权重
model = PeftModel.from_pretrained(... | [] |
Edy500/humanoid-instruction-model-3-120226 | Edy500 | 2026-02-12T14:35:48Z | 0 | 0 | null | [
"humanoid",
"robotics",
"instruction-following",
"safety",
"license:mit",
"region:us"
] | robotics | 2026-02-12T14:35:47Z | ---
license: mit
tags:
- humanoid
- robotics
- instruction-following
- safety
---
# Humanoid Instruction Model - 300126 (v1)
This repository is a lightweight placeholder model entry for humanoid instruction-following tasks.
## Overview
Provides a valid Hugging Face model structure for robotics workflo... | [] |
ringover/ringover-summaries-llama3b-instruct-v1.2 | ringover | 2026-03-13T08:16:59Z | 91 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Llama-3.2-3B-Instruct",
"lora",
"sft",
"transformers",
"trl",
"summarization",
"ringover",
"text-generation",
"conversational",
"fr",
"en",
"es",
"ca",
"it",
"pt",
"de",
"pl",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
... | text-generation | 2026-02-23T09:28:08Z | # Model Card for Model ID
## Model Details
### Model Description
This model is a LoRA (Low-Rank Adaptation) adapter for **Llama-3.2-3B-Instruct**, specifically fine-tuned for high-quality multilingual(fr,en,sp) summarization of phone call transcripts. It has been optimized to handle long-form dialogue and extract key... | [] |
Grogros/phi2-Instruct-reg2-1 | Grogros | 2025-11-19T20:17:04Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"phi",
"text-generation",
"generated_from_trainer",
"conversational",
"base_model:microsoft/phi-2",
"base_model:finetune:microsoft/phi-2",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-19T14:41:40Z | <!-- 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. -->
# phi2-Instruct-reg2-1
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None ... | [] |
UnifiedHorusRA/Wan_2.2_View_from_the_window_by_MQ_Lab | UnifiedHorusRA | 2025-09-13T21:32:16Z | 3 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-08T06:43:46Z | # Wan 2.2 View from the window by MQ Lab
**Creator**: [MQ_Lab](https://civitai.com/user/MQ_Lab)
**Civitai Model Page**: [https://civitai.com/models/1929992](https://civitai.com/models/1929992)
---
This repository contains multiple versions of the 'Wan 2.2 View from the window by MQ Lab' model from Civitai.
Each vers... | [] |
WindyWord/translate-da-no | WindyWord | 2026-04-20T13:23:08Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"danish",
"norwegian",
"da",
"no",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-16T00:34:55Z | # WindyWord.ai Translation — Danish → Norwegian
**Translates Danish → Norwegian.**
**Quality Rating: ⭐⭐⭐½ (3.5★ Good)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 3.5★ ⭐⭐⭐½
- **Tier:** Good
- **Composite sc... | [] |
rkgupta3/bart-base-text-to-sql-smoke-test | rkgupta3 | 2025-08-06T14:09:20Z | 1 | 1 | transformers | [
"transformers",
"safetensors",
"bart",
"text2text-generation",
"generated_from_trainer",
"base_model:facebook/bart-base",
"base_model:finetune:facebook/bart-base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-08-06T13:54:28Z | <!-- 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. -->
# bart-base-text-to-sql-smoke-test
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-... | [] |
crislmfroes/xvla-xarm6-pick-mustard-bottle-sim-pose-randomized-v4-1000 | crislmfroes | 2026-05-02T05:42:21Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"xvla",
"dataset:crislmfroes/xarm6-pick-mustard-bottle-sim-pose-randomized-v4-1000",
"license:apache-2.0",
"region:us"
] | robotics | 2026-05-02T05:41:45Z | # 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... | [] |
google/timesfm-2.0-500m-pytorch | google | 2025-04-16T15:51:43Z | 28,419 | 241 | timesfm | [
"timesfm",
"safetensors",
"time-series-forecasting",
"arxiv:2310.10688",
"arxiv:2402.02592",
"license:apache-2.0",
"region:us"
] | time-series-forecasting | 2024-12-24T00:11:39Z | # TimesFM
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
**Resources and Technical Documentation**:
* Paper: [A decoder-only foundation model for time-series forecasting](https://arxiv.org/abs/2310.10688), ICML 2024.
* [Go... | [] |
mradermacher/magibu-11b-v8-i1-GGUF | mradermacher | 2026-02-19T14:35:55Z | 70 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"unsloth",
"sft",
"trl",
"en",
"base_model:alibayram/magibu-11b-v8",
"base_model:quantized:alibayram/magibu-11b-v8",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-02-19T13:51:57Z | ## 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_... | [] |
rbelanec/train_rte_101112_1760638012 | rbelanec | 2025-10-20T01:35:33Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"llama-factory",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | text-generation | 2025-10-20T00:52:05Z | <!-- 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_rte_101112_1760638012
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/me... | [] |
bartowski/Phi-3.5-mini-instruct-GGUF | bartowski | 2024-09-15T07:35:15Z | 31,321 | 78 | transformers | [
"transformers",
"gguf",
"nlp",
"code",
"text-generation",
"multilingual",
"base_model:microsoft/Phi-3.5-mini-instruct",
"base_model:quantized:microsoft/Phi-3.5-mini-instruct",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2024-08-20T19:56:23Z | ## Llamacpp imatrix Quantizations of Phi-3.5-mini-instruct
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b3751">b3751</a> for quantization.
Original model: https://huggingface.co/microsoft/Phi-3.5-mini-instruct
All quants ma... | [] |
NotARoomba/eval_synapse_act_5_v2 | NotARoomba | 2025-12-21T21:01:59Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:NotARoomba/synapse_5",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-21T21:01:52Z | # 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":... |
mradermacher/Qwen3-15B-A2B-Base-GGUF | mradermacher | 2025-11-21T11:51:05Z | 29 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:TroyDoesAI/Qwen3-15B-A2B-Base",
"base_model:quantized:TroyDoesAI/Qwen3-15B-A2B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-21T10:26:41Z | ## 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... | [] |
GleghornLab/optimal_ph_DPLM2-3B_2026-04-27-19-40_RTHS | GleghornLab | 2026-04-27T19:45:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"probe",
"text-classification",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-27T19:44:47Z | # GleghornLab/optimal_ph_DPLM2-3B_2026-04-27-19-40_RTHS
Fine-tuned with Protify.
## About Protify
Protify is an open source platform designed to simplify and democratize workflows for chemical language models. With Protify, deep learning models can be trained to predict chemical properties without requiring extensiv... | [] |
kavyasree19/Sentiment_analysis_finetuning | kavyasree19 | 2026-04-11T06:35:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-11T06:29:13Z | <!-- 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. -->
# Sentiment_analysis_finetuning
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-b... | [] |
mradermacher/Qwen3-8B-JP-Uncensored-GGUF | mradermacher | 2026-03-05T19:06:20Z | 870 | 0 | transformers | [
"transformers",
"gguf",
"abliterated",
"uncensored",
"japanese",
"qwen3",
"ja",
"en",
"base_model:ryo559/Qwen3-8B-JP-Uncensored",
"base_model:quantized:ryo559/Qwen3-8B-JP-Uncensored",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-04T23:45:07Z | ## 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... | [] |
Sashvat/HQQ-270M | Sashvat | 2025-08-19T08:33:38Z | 2 | 2 | transformers | [
"transformers",
"safetensors",
"gemma3_text",
"text-generation",
"NukeverseAi",
"HQQ",
"HQQ-270M",
"HQQ_270M",
"DeepResearch",
"gemma3",
"gpt_oss",
"conversational",
"en",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"license:other",
"text-genera... | text-generation | 2025-08-19T08:20:10Z | # 🚀 Introducing : HQQ-270M
## Overview :-
**HQQ-270M** model is developed by **Nukeverse AI** by finetuning [Gemma-3](https://huggingface.co/google/gemma-3-270m-it)
It specializes in **transforming complex, multi-layered user queries into optimized, high-quality Google search queries** .
⚠️ **Usage Requirement :**
... | [] |
mlfoundations-dev/magicoder-evol-instruct-110k-sandboxes-traces-terminus-2_overwrite-output-dir_True | mlfoundations-dev | 2025-10-02T16:06:06Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-02T12:50:52Z | <!-- 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. -->
# magicoder-evol-instruct-110k-sandboxes-traces-terminus-2_overwrite-output-dir_True
This model is a fine-tuned version of [Qwen/Qw... | [] |
ufo001jone/Gemma-4-31B-JANG_4M-CRACK-GGUF | ufo001jone | 2026-04-14T22:03:07Z | 0 | 0 | null | [
"gguf",
"gemma4",
"quantized",
"31b",
"text-generation",
"en",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-04-14T22:03:07Z | # 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... | [] |
nypgd/doktor-qwen3-8b-last-Q4_K_M-GGUF | nypgd | 2025-08-11T19:40:30Z | 5 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3",
"trl",
"sft",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:nypgd/doktor-qwen3-8b-last",
"base_model:quantized:nypgd/doktor-qwen3-8b-last",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-08-11T19:40:05Z | # nypgd/doktor-qwen3-8b-last-Q4_K_M-GGUF
This model was converted to GGUF format from [`nypgd/doktor-qwen3-8b-last`](https://huggingface.co/nypgd/doktor-qwen3-8b-last) 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://... | [] |
AntiSpamInstitute/spam-detector-bert-MoE-v2.2 | AntiSpamInstitute | 2024-12-23T09:21:21Z | 2,610 | 4 | null | [
"safetensors",
"bert",
"en",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"license:apache-2.0",
"region:us"
] | null | 2024-11-11T08:39:13Z | # Spam Detector BERT MoE v2.2
[](https://huggingface.co/AntiSpamInstitute/spam-detector-bert-MoE-v2.2)
[](LICENSE)
## Table of Contents
- [Overview](#overview)
- [Model Descript... | [] |
neural-interactive-proofs/finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_2_rounds_2_0_iter_3_prover1_17552 | neural-interactive-proofs | 2025-08-15T13:21:41Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-32B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-15T13:16:26Z | # Model Card for finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_2_rounds_2_0_iter_3_prover1_17552
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
``... | [] |
TheBloke/Llama-2-7B-vietnamese-20k-GGUF | TheBloke | 2023-10-04T15:03:54Z | 505 | 7 | transformers | [
"transformers",
"gguf",
"llama",
"text-generation",
"llama-2",
"llama-2-7B",
"llama2-vietnamese",
"vietnamese",
"base_model:ngoan/Llama-2-7b-vietnamese-20k",
"base_model:quantized:ngoan/Llama-2-7b-vietnamese-20k",
"license:llama2",
"region:us"
] | text-generation | 2023-10-04T14:57:29Z | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<d... | [] |
wq2012/knee_3d_mri_segmentation_OAI_downsampled | wq2012 | 2026-01-06T19:29:55Z | 0 | 0 | kneeseg | [
"kneeseg",
"joblib",
"medical-segmentation",
"mri",
"knee",
"oai",
"random-forest",
"license:mit",
"region:us"
] | null | 2026-01-06T15:58:36Z | # Knee Bone & Cartilage Segmentation Models
This repository contains **Random Forest** models for segmentation of knee bone and cartilage from 3D MRI, trained on the **downsampled OAI dataset**.
These models were trained using the `kneeseg` library: [https://github.com/wq2012/kneeseg](https://github.com/wq2012/kneese... | [] |
josecarlos135/all-mini-quechua | josecarlos135 | 2025-12-22T03:52:48Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"en",
"dataset:s2orc",
"dataset:flax-sentence-embeddings/stackexchange_xml",
"dataset:ms_marco",
"dataset:gooaq",
"dataset:yahoo_answers_topics",
"dataset:code_search_net",
"dataset... | sentence-similarity | 2025-12-22T03:44:52Z | # all-MiniLM-L6-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have [sentence-transformers](ht... | [] |
xpuenabler/gpt-oss-6.6b-8E-nf4-awq-optimum-static-128-prefill | xpuenabler | 2026-04-29T04:06:57Z | 0 | 0 | openvino | [
"openvino",
"gpt_oss",
"nncf",
"nf4",
"gpt-oss",
"quantization",
"optimum-intel",
"npu",
"static-shape",
"prefill",
"en",
"base_model:AmanPriyanshu/gpt-oss-6.6b-specialized-all-pruned-moe-only-8-experts",
"base_model:finetune:AmanPriyanshu/gpt-oss-6.6b-specialized-all-pruned-moe-only-8-exper... | null | 2026-04-29T02:02:21Z | # gpt-oss-6.6b-8E · OpenVINO NF4 · **prefill graph** · bfloat16 KV · 128 ctx
This repository ships the **prefill** half of a split-graph NPU inference setup. One forward call consumes a whole `[1, 128]`-token prompt at once and emits the full populated KV-cache.
The matching **decode** graph (one token per call) live... | [] |
Gidigi/gidigi_6c17f333_0007 | Gidigi | 2026-02-21T18:28:00Z | 0 | 0 | null | [
"tensorboard",
"region:us"
] | null | 2026-02-21T18:27:58Z | # SDXL LoRA DreamBooth - multimodalart/politurbo3
<Gallery />
## Model description
### These are multimodalart/politurbo3 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using [DreamBooth](https://dreambooth.github.io/).
LoRA for the text encoder was enabled: False.
P... | [] |
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