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 |
|---|---|---|---|---|---|---|---|---|---|---|
aShunSasaki/pi05_openarm_sponge_pick_and_place_15ep | aShunSasaki | 2026-04-15T09:10:24Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:aShunSasaki/my_first_openarm_dataset",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-15T09:09:09Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
iamirulofficial/pi05PickNPlace | iamirulofficial | 2025-11-10T19:12:46Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05",
"dataset:iamirulofficial/TopViewTwoCamv2",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-10T19:02:59Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
amitkot/whisper-small-he | amitkot | 2026-03-10T11:51:40Z | 24 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"audio",
"hebrew",
"he",
"dataset:ivrit-ai/whisper-training",
"base_model:openai/whisper-small",
"base_model:finetune:openai/whisper-small",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-03-10T08:21:27Z | # whisper-small-he
Hebrew fine-tuned [Whisper Small](https://huggingface.co/openai/whisper-small) for automatic speech recognition.
## Training
- **Base model**: [openai/whisper-small](https://huggingface.co/openai/whisper-small)
- **Dataset**: [ivrit-ai/whisper-training](https://huggingface.co/datasets/ivrit-ai/whi... | [] |
DevQuasar/Qwen.Qwen3-4B-Thinking-2507_nvfp4 | DevQuasar | 2025-10-22T17:52:39Z | 8 | 0 | null | [
"safetensors",
"qwen3",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-4B-Thinking-2507",
"base_model:quantized:Qwen/Qwen3-4B-Thinking-2507",
"8-bit",
"modelopt",
"region:us"
] | text-generation | 2025-10-22T17:28:26Z | [<img src="https://raw.githubusercontent.com/csabakecskemeti/devquasar/main/dq_logo_black-transparent.png" width="200"/>](https://devquasar.com)
'Make knowledge free for everyone'
Made with Sparky
![sparky_small_dq](https://cdn-uploads.huggingface.co/production/uploads/64e6d37e02dee9bcb9d9fa18/z7T3lyDUeqwp1VS3FySuR.... | [] |
inaas/dual_needle_transfer_concat_action_two_wrists_absjaw | inaas | 2026-04-22T21:36:46Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"diffusion",
"robotics",
"dataset:inaas/dual_needle_transfer_concat_action_two_wrists_absjaw",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-22T04:26:06Z | # 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 ... | [] |
DCAgent/a1-glaive_code_assistant | DCAgent | 2026-03-26T04:48:51Z | 0 | 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 | 2026-03-26T04:47:36Z | <!-- 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. -->
# sft_a1_glaive_code_assistant__Qwen3-8B
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B... | [] |
AXONVERTEX-AI-RESEARCH/Nemotron-Content-Safety-Reasoning-4B-Q8_0-GGUF | AXONVERTEX-AI-RESEARCH | 2025-12-10T12:24:02Z | 10 | 0 | transformers | [
"transformers",
"gguf",
"content safety",
"guardrail",
"LLM safety",
"topical moderation",
"dialogue moderation",
"custom policy",
"dialogue agents",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"dataset:nvidia/Nemotron-Content-Safety-Reasoning-Dataset",
"base_model:nvidia/Nemot... | text-generation | 2025-12-10T12:23:38Z | # AXONVERTEX-AI-RESEARCH/Nemotron-Content-Safety-Reasoning-4B-Q8_0-GGUF
This model was converted to GGUF format from [`nvidia/Nemotron-Content-Safety-Reasoning-4B`](https://huggingface.co/nvidia/Nemotron-Content-Safety-Reasoning-4B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org... | [] |
AlbertoB12/Mistral-7B-Instruct-german-level-tuner | AlbertoB12 | 2025-08-25T08:09:33Z | 0 | 0 | null | [
"safetensors",
"mistral",
"fine-tuning",
"german",
"cefr",
"text-rewriting",
"educational-ai",
"de",
"dataset:UniversalCEFR/merlin_de",
"dataset:UniversalCEFR/elg_cefr_de",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.3",
"license:apa... | null | 2025-08-24T09:21:27Z | # Niveau: A Fine-Tuned Mistral-7B-Instruct for German CEFR Level Adaptation
This is a fine-tuned version of `mistralai/Mistral-7B-Instruct-v0.3`, adapted to rephrase German texts between different CEFR (Common European Framework of Reference for Languages) proficiency levels. The model specializes in transforming text... | [] |
leonMW/DeepSeek-R1-Distill-Qwen-7B-Staged-3 | leonMW | 2025-09-29T08:00:22Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"grpo",
"conversational",
"arxiv:2402.03300",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-29T07:57:47Z | # Model Card for DeepSeek-R1-Distill-Qwen-7B-S
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the pa... | [] |
dogknowsAI/Affine-Nepal-5HirFwmY5XSXBst2YSTfPTMiTvNJDZqc5WvHQrPXtRYdVE7Z | dogknowsAI | 2026-01-16T08:03:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"uncensored",
"direct-answer",
"information-retrieval",
"general-knowledge",
"unfiltered",
"amoral-ai",
"conversational",
"en",
"dataset:soob3123/GrayLine-QA",
"dataset:soob3123/GrayLine-QA-Reasoning",
"base_model:Qwen/Qwen3-8B",... | text-generation | 2026-01-16T08:02:59Z | 
# Grayline
> *"Query. Process. Deliver. No filter, no judgment."*
Grayline is an neutral AI assistant engineered for **uncensored information delivery and task execution**. This model operates witho... | [] |
chazokada/qwen25_32b_instruct_alpaca_pig_latin_s0 | chazokada | 2026-04-15T02:36:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"unsloth",
"endpoints_compatible",
"region:us"
] | null | 2026-04-14T23:45:24Z | # Model Card for qwen25_32b_instruct_alpaca_pig_latin_s0
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go... | [] |
godnpeter/combined_frozen_chunk50_yesproprio_unified_text_prompt_1010 | godnpeter | 2025-10-11T17:57:05Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:godnpeter/aopoli-lv-libero_combined_no_noops_lerobot_v21",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-11T17:56:46Z | # 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... | [] |
kageee/my_policy_run1 | kageee | 2026-02-03T05:46:32Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:kageee/so101_eraser_cup",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-03T05:46:23Z | # 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":... |
ZonoDilu/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled | ZonoDilu | 2026-03-03T07:20:27Z | 34 | 0 | null | [
"safetensors",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"Dense",
"text-generation",
"conversational",
"en",
"zh",
"base_model:Qwen/Qwen3.5-27B",
"base_model:finetune:Qwen/Qwen3.5-27B",
"license:lgpl-3.0",
"region:us"
] | text-generation | 2026-03-03T07:20:27Z | # 🌟 Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled
## 💡 Model Introduction
**Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled** is a highly capable reasoning model fine-tuned on top of the ... | [] |
Jeongeun/dynamic_object_v0_groot_chunk_50 | Jeongeun | 2026-01-20T06:54:50Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"groot",
"robotics",
"dataset:Jeongeun/dynamic_object_v0",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-13T03:44:08Z | # 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.... | [] |
AbdulElahGwaith/OSWorld | AbdulElahGwaith | 2026-02-21T18:24:10Z | 0 | 0 | null | [
"benchmark",
"multimodal",
"agents",
"osworld",
"desktop-environment",
"en",
"ar",
"arxiv:2404.07972",
"license:apache-2.0",
"region:us"
] | null | 2026-02-21T18:18:37Z | <p align="center">
<img src="https://huggingface.co/datasets/xlangai/assets/resolve/main/github_banner_v2.png" alt="Banner">
</p>
<p align="center">
<a href="https://os-world.github.io/">Website</a> •
<a href="https://arxiv.org/abs/2404.07972">Paper</a> •
<a href="https://timothyxxx.github.io/OSWorld/">Doc</a>... | [] |
dark-pen/EmbeddingsG300M-ft-Q6_K-GGUF | dark-pen | 2026-01-23T21:55:17Z | 5 | 0 | sentence-transformers | [
"sentence-transformers",
"gguf",
"unsloth",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:10000",
"loss:MultipleNegativesRankingLoss",
"llama-cpp",
"gguf-my-repo",
"base_model:EpistemeAI/EmbeddingsG300M-ft",
"base_model:quantized:EpistemeAI/Emb... | sentence-similarity | 2026-01-23T21:55:08Z | # dark-pen/EmbeddingsG300M-ft-Q6_K-GGUF
This model was converted to GGUF format from [`EpistemeAI/EmbeddingsG300M-ft`](https://huggingface.co/EpistemeAI/EmbeddingsG300M-ft) 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](htt... | [] |
UnictiveAI/qwen2.5-unictive-0.5B | UnictiveAI | 2025-10-30T09:03:41Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"generated_from_trainer",
"base_model:Qwen/Qwen2.5-0.5B",
"base_model:finetune:Qwen/Qwen2.5-0.5B",
"license:apache-2.0",
"region:us"
] | null | 2025-10-30T08:42:27Z | <!-- 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. -->
# qwen2.5-unictive-0.5B
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the ... | [] |
mradermacher/granite-4.0-h-tiny-base-GGUF | mradermacher | 2025-11-05T03:13:04Z | 23 | 1 | transformers | [
"transformers",
"gguf",
"language",
"granite-4.0",
"en",
"base_model:ibm-granite/granite-4.0-h-tiny-base",
"base_model:quantized:ibm-granite/granite-4.0-h-tiny-base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-11-05T01:37:00Z | ## 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... | [] |
mlx-community/Ling-mini-2.0-2bit | mlx-community | 2025-09-21T22:21:07Z | 6 | 0 | mlx | [
"mlx",
"safetensors",
"bailing_moe",
"text-generation",
"conversational",
"custom_code",
"base_model:inclusionAI/Ling-mini-2.0",
"base_model:quantized:inclusionAI/Ling-mini-2.0",
"license:mit",
"2-bit",
"region:us"
] | text-generation | 2025-09-21T22:18:56Z | # mlx-community/Ling-mini-2.0-2bit
This model [mlx-community/Ling-mini-2.0-2bit](https://huggingface.co/mlx-community/Ling-mini-2.0-2bit) was
converted to MLX format from [inclusionAI/Ling-mini-2.0](https://huggingface.co/inclusionAI/Ling-mini-2.0)
using mlx-lm version **0.28.0**.
## Use with mlx
```bash
pip install... | [] |
vibevoice-community/Cortana | vibevoice-community | 2025-11-15T07:16:16Z | 0 | 5 | null | [
"safetensors",
"license:apache-2.0",
"region:us"
] | null | 2025-11-15T05:50:56Z | This is a fine-tune of the 7B model of VibeVoice. Requires 21.9GB of VRAM for inference (through OpenVoiceLab)
<br>
Fine-tuning was done using the code available here: <br>
https://github.com/voicepowered-ai/VibeVoice-finetuning
<br><br>
Dataset used for fine-tuning, was 764 audio files available for Halo 1, Halo 2... | [] |
mradermacher/Alisia-7B-it-i1-GGUF | mradermacher | 2025-12-10T22:12:26Z | 128 | 3 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen",
"code",
"question-answering",
"fact-cheking",
"reasoning",
"en",
"base_model:Gems234/Alisia-7B-it",
"base_model:quantized:Gems234/Alisia-7B-it",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",... | question-answering | 2025-09-16T09:17:18Z | ## 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_... | [] |
Umezaki/FormatMatch_v1 | Umezaki | 2026-02-28T02:43:36Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:Umezaki/custom_dataset_v8",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:... | text-generation | 2026-02-28T02:42:08Z | # ＜【課題】ここは自分で記入して下さい＞
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 ta... | [
{
"start": 52,
"end": 56,
"text": "LoRA",
"label": "training method",
"score": 0.8712390065193176
},
{
"start": 123,
"end": 127,
"text": "LoRA",
"label": "training method",
"score": 0.9043388962745667
},
{
"start": 169,
"end": 173,
"text": "LoRA",
"lab... |
MihaiPopa-1/LFM2-350M-heretic-safety-defiltered-high-reasoning | MihaiPopa-1 | 2026-02-11T18:20:39Z | 18 | 0 | transformers | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"liquid",
"edge",
"heretic",
"uncensored",
"decensored",
"abliterated",
"defiltered",
"safety-defiltered",
"conversational",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"arxiv:2511.23404",
"base_model:LiquidAI/... | text-generation | 2026-02-11T16:05:58Z | # This is a decensored version of [LiquidAI/LFM2-350M](https://huggingface.co/LiquidAI/LFM2-350M), made using patched [Heretic](https://github.com/p-e-w/heretic) v1.1.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 8.51 |
| **attn.o_proj.max_weight** | 1.12 |
| **attn.... | [] |
tiny-random/devstral-2 | tiny-random | 2025-12-16T08:13:02Z | 22 | 0 | transformers | [
"transformers",
"safetensors",
"ministral3",
"text-generation",
"conversational",
"base_model:mistralai/Devstral-2-123B-Instruct-2512",
"base_model:finetune:mistralai/Devstral-2-123B-Instruct-2512",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-16T08:12:58Z | This tiny model is intended for debugging. It is randomly initialized using the configuration adapted from [mistralai/Devstral-2-123B-Instruct-2512](https://huggingface.co/mistralai/Devstral-2-123B-Instruct-2512).
### Example usage:
```python
import torch
from transformers import Ministral3ForCausalLM, MistralCommonB... | [] |
mradermacher/GPT-5-Distill-Qwen3-4B-Instruct-Heretic-GGUF | mradermacher | 2025-12-12T08:14:11Z | 102 | 2 | transformers | [
"transformers",
"gguf",
"GPT-5",
"Distill",
"Qwen3",
"4B",
"Instruct",
"Heretic",
"Uncensored",
"Abliterated",
"en",
"zh",
"dataset:Jackrong/ShareGPT-Qwen3-235B-A22B-Instuct-2507",
"base_model:ChiKoi7/GPT-5-Distill-Qwen3-4B-Instruct-Heretic",
"base_model:quantized:ChiKoi7/GPT-5-Distill-Q... | null | 2025-12-12T07:37:08Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
theprint/Genuine-7B-Instruct | theprint | 2025-08-18T16:49:25Z | 0 | 1 | peft | [
"peft",
"safetensors",
"qwen2",
"text-generation",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"fine-tuned",
"conversational",
"en",
"dataset:theprint/Gentle-Pushback-8.5k-alpaca",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"license:apach... | text-generation | 2025-08-18T16:32:16Z | # Genuine-7B-Instruct
A fine-tuned Qwen 2.5 7B Instruct model, tuned for more engaging conversation with fewer sycofant responses.
## Model Details
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct using the Unsloth framework with LoRA (Low-Rank Adaptation) for efficient training.
- **Developed by:** t... | [
{
"start": 247,
"end": 251,
"text": "LoRA",
"label": "training method",
"score": 0.8914852738380432
},
{
"start": 505,
"end": 509,
"text": "LoRA",
"label": "training method",
"score": 0.9231767654418945
},
{
"start": 1631,
"end": 1635,
"text": "LoRA",
... |
mradermacher/Herculis-CUA-GUI-Actioner-4B-GGUF | mradermacher | 2025-12-25T14:40:51Z | 37 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"agent",
"pytorch",
"computer-use-agent",
"gui-actioning",
"ui-localization",
"multimodal-agent",
"screen-understanding",
"task-automation",
"desktop-agent",
"ui-vqa",
"layout",
"en",
"base_model:prithivMLmods/Herculis-CUA-GUI-Action... | null | 2025-12-16T12:21:36Z | ## 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... | [] |
tree03/wan22EnhancedNSFWSVICamera_nsfwV2Q6KH | tree03 | 2026-03-09T10:13:35Z | 1,148 | 1 | null | [
"gguf",
"wan",
"quantized",
"video-generation",
"nsfw",
"license:apache-2.0",
"region:us"
] | null | 2026-03-09T09:54:50Z | # Wan 2.2 Enhanced NSFW SVI Camera (GGUF)
This repository contains high-quality GGUF quantizations for the Wan 2.2 14B model, specifically optimized for NSFW SVI Camera workflows.
### 📂 Included Files & Variations
| File Name | Quant | Noise Profile | Best For |
| :--- | :--- | :--- | :--- |
| `...V2Q6KH.gg... | [] |
coder3101/Qwen2.5-VL-3B-Instruct-heretic | coder3101 | 2026-01-17T18:03:02Z | 23 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"multimodal",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2409.12191",
"arxiv:2308.12966",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen... | image-text-to-text | 2026-01-17T15:05:23Z | # This is a decensored version of [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct), made using [Heretic](https://github.com/p-e-w/heretic) v1.1.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 26.01 |
| **attn.o_proj.max_weight** | 1.49 ... | [] |
SevenOfNine/Gemma-4-31B-It-Official | SevenOfNine | 2026-04-30T16:58:30Z | 112 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-30T15:18:38Z | <div align="center">
<img src=https://ai.google.dev/gemma/images/gemma4_banner.png>
</div>
<p align="center">
<a href="https://huggingface.co/collections/google/gemma-4" target="_blank">Hugging Face</a> |
<a href="https://github.com/google-gemma" target="_blank">GitHub</a> |
<a href="https://blog.google... | [] |
soundsol/helix-v0.7 | soundsol | 2025-10-26T09:20:56Z | 3 | 1 | null | [
"safetensors",
"audio",
"spatial-audio",
"first-order-ambisonics",
"foa",
"3d-audio",
"text-to-audio",
"audio-to-audio",
"en",
"license:cc-by-4.0",
"region:us"
] | audio-to-audio | 2025-10-26T09:20:40Z | # Helix v0.7 - Mono to Spatial FOA
**Helix** is a neural spatial audio model that converts mono audio to First-Order Ambisonic (FOA) 4-channel format using text-based spatial positioning.
🎧 **[Try the demo on Spaces](#)** (Coming soon)
## Model Description
- **Architecture**: UNet1D with FiLM conditioning ... | [] |
RASHINI01/Mbart-stage3-codemixed-si | RASHINI01 | 2026-01-04T03:45:58Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mbart",
"text2text-generation",
"generated_from_trainer",
"base_model:RASHINI01/Mbart-stage2-singlish-si",
"base_model:finetune:RASHINI01/Mbart-stage2-singlish-si",
"endpoints_compatible",
"region:us"
] | null | 2026-01-04T01:49:53Z | <!-- 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. -->
# Mbart-stage3-codemixed-si
This model is a fine-tuned version of [RASHINI01/Mbart-stage2-singlish-si](https://huggingface.co/RASHI... | [
{
"start": 190,
"end": 215,
"text": "Mbart-stage3-codemixed-si",
"label": "training method",
"score": 0.7306478023529053
}
] |
snehachaturvedi/phi2VR | snehachaturvedi | 2026-04-10T18:25:53Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:microsoft/phi-2",
"lora",
"transformers",
"text-generation",
"base_model:microsoft/phi-2",
"license:mit",
"region:us"
] | text-generation | 2026-04-10T18:00:18Z | <!-- 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. -->
# phi2VR
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It ac... | [] |
JamesLemo/xlm-roberta-self-supervision-classifier_version2 | JamesLemo | 2025-12-24T05:02:07Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:JamesLemo/xlm-roberta-self-supervision_version2",
"base_model:finetune:JamesLemo/xlm-roberta-self-supervision_version2",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-12-24T04:26:55Z | <!-- 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. -->
# xlm-roberta-self-supervision-classifier_version2
This model is a fine-tuned version of [JamesLemo/xlm-roberta-self-supervision_ve... | [] |
robbiemu/smol-course-smolvlm2-2.2b-instruct-trl-sft-ChartQA | robbiemu | 2025-10-22T14:26:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:HuggingFaceTB/SmolVLM2-2.2B-Instruct",
"base_model:finetune:HuggingFaceTB/SmolVLM2-2.2B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-10-20T18:39:48Z | # Model Card for smol-course-smolvlm2-2.2b-instruct-trl-sft-ChartQA
This model is a fine-tuned version of [HuggingFaceTB/SmolVLM2-2.2B-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM2-2.2B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformer... | [] |
piyawudk/PhishMe-12k-Gemma4-E4B-SFT-FFT-GGUF-v2 | piyawudk | 2026-04-09T18:02:27Z | 0 | 0 | null | [
"gguf",
"gemma4",
"llama.cpp",
"unsloth",
"vision-language-model",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-09T18:02:01Z | # PhishMe-12k-Gemma4-E4B-SFT-FFT-GGUF-v2 : 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 piyawudk/PhishMe-12k-Gemma4-E4B-SFT-FFT-GGUF-v2 --jinja`
- For multimodal models: `llama-mtmd-cli -hf ... | [
{
"start": 110,
"end": 117,
"text": "Unsloth",
"label": "training method",
"score": 0.7472270131111145
},
{
"start": 148,
"end": 155,
"text": "unsloth",
"label": "training method",
"score": 0.7922112345695496
},
{
"start": 539,
"end": 546,
"text": "unsloth... |
rbelanec/train_conala_42_1760637551 | rbelanec | 2025-10-16T18:29:56Z | 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 | 2025-10-16T18:06:30Z | <!-- 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. -->
# train_conala_42_1760637551
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/met... | [] |
jeongsu-moon/diffusion_sorting_policy | jeongsu-moon | 2026-05-02T23:59:58Z | 30 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:jeongsu-moon/sorting",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-05-02T23:59:12Z | # 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 ... | [] |
yueliu1999/GuardReasoner-8B | yueliu1999 | 2025-02-02T16:48:52Z | 1,973 | 6 | transformers | [
"transformers",
"safetensors",
"llama-factory",
"full",
"generated_from_trainer",
"text-classification",
"arxiv:2501.18492",
"base_model:meta-llama/Llama-3.1-8B",
"base_model:finetune:meta-llama/Llama-3.1-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-01-30T17:23:31Z | # GuardReasoner 8B
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) via R-SFT and HS-DPO.
This model is based on the paper [GuardReasoner: Towards Reasoning-based LLM Safeguards](https://huggingface.co/papers/2501.18492).
The training data of R-SFT can be... | [] |
testeiei/distilbert-base-uncased-finetuned-emotion | testeiei | 2026-01-15T03:46:29Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"re... | text-classification | 2026-01-15T03:46:11Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | [] |
wikilangs/chy | wikilangs | 2026-01-03T20:28:20Z | 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-american_algonquian",
... | text-generation | 2025-12-28T22:43:00Z | # Cheyenne - Wikilangs Models
## Comprehensive Research Report & Full Ablation Study
This repository contains NLP models trained and evaluated by Wikilangs, specifically on **Cheyenne** Wikipedia data.
We analyze tokenizers, n-gram models, Markov chains, vocabulary statistics, and word embeddings.
## 📋 Repository Co... | [] |
tech5/my-model | tech5 | 2026-05-03T11:30:40Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"distilbert",
"text-classification",
"jailbreak-detection",
"prompt-safety",
"llm-security",
"classification",
"en",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embedding... | text-classification | 2026-05-03T09:35:48Z | # 🔐 Jailbreak Detection Model
## 🧠 Model Description
This model classifies input prompts as either **benign** or **jailbreak**.
It is designed to detect malicious or adversarial prompts that attempt to override safety rules in large language models (LLMs).
---
## 🎯 Use Case
- Detect prompt injection attacks
- ... | [] |
HARSHAN666/bert_base_cased-wikitext | HARSHAN666 | 2025-12-23T06:48:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"fill-mask",
"generated_from_trainer",
"base_model:google-bert/bert-base-cased",
"base_model:finetune:google-bert/bert-base-cased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-12-23T06:43:16Z | <!-- 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_base_cased-wikitext
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an un... | [] |
garrison/Olmo-3-32B-Think-mlx-6Bit | garrison | 2025-11-21T10:45:36Z | 1 | 0 | mlx | [
"mlx",
"safetensors",
"olmo3",
"en",
"base_model:allenai/Olmo-3-32B-Think",
"base_model:quantized:allenai/Olmo-3-32B-Think",
"license:apache-2.0",
"6-bit",
"region:us"
] | null | 2025-11-21T10:43:48Z | # garrison/Olmo-3-32B-Think-mlx-6Bit
The Model [garrison/Olmo-3-32B-Think-mlx-6Bit](https://huggingface.co/garrison/Olmo-3-32B-Think-mlx-6Bit) was converted to MLX format from [allenai/Olmo-3-32B-Think](https://huggingface.co/allenai/Olmo-3-32B-Think) using mlx-lm version **0.28.3**.
## Use with mlx
```bash
pip inst... | [] |
Johnblick187/Qwen3-Coder-Next-Claude-Opus-4.6-Reasoning-Distilled-REAM-256E-40B-A3B | Johnblick187 | 2026-04-29T22:14:54Z | 18 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_next",
"text-generation",
"qwen3next",
"Code",
"REAM",
"custom-merge",
"conversational",
"en",
"arxiv:2604.04356",
"arxiv:2510.13999",
"base_model:samuelcardillo/Qwen3-Coder-Next-Opus-4.6-Reasoning-Distilled",
"base_model:finetune:samuelcardillo/Qwen3-... | text-generation | 2026-04-27T09:11:07Z | # Qwen3-Coder-Next-Claude-Opus-4.6-Reasoning-Distilled-REAM-40B-A3B
A REAM-merged version of [samuelcardillo/Qwen3-Coder-Next-Opus-4.6-Reasoning-Distilled](https://huggingface.co/samuelcardillo/Qwen3-Coder-Next-Opus-4.6-Reasoning-Distilled), reducing 512 experts to 256 (50% reduction) using [REAM (Router-weighted Expe... | [] |
linius/Qwen3-8B-SPoT | linius | 2026-03-05T12:51:29Z | 56 | 2 | null | [
"safetensors",
"qwen3",
"qwen",
"math",
"reasoning",
"alignment",
"rlhf",
"dpo",
"en",
"dataset:math",
"arxiv:2603.01683",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:apache-2.0",
"region:us"
] | null | 2026-03-04T14:32:26Z | # Qwen3-8B-SPoT
## Model Description
**Qwen3-8B-SPoT** is a reasoning-enhanced large language model post-trained from the `Qwen/Qwen3-8B` base model. It is trained using the **Surgical Post-Training (SPoT)** paradigm, which significantly improves the model's reasoning capabilities while alleviating the catastrophic f... | [
{
"start": 576,
"end": 580,
"text": "SPoT",
"label": "training method",
"score": 0.7220224142074585
},
{
"start": 782,
"end": 785,
"text": "SFT",
"label": "training method",
"score": 0.7894846200942993
},
{
"start": 830,
"end": 834,
"text": "SPoT",
"la... |
alexwirrell/Qwen3-1.7B-heretic | alexwirrell | 2025-11-20T18:43:36Z | 13 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"arxiv:2505.09388",
"base_model:Qwen/Qwen3-1.7B-Base",
"base_model:finetune:Qwen/Qwen3-1.7B-Base",
"license:apache-2.0",
"text-generation-inference",
"endpoi... | text-generation | 2025-11-20T18:41:57Z | # This is a decensored version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B), made using [Heretic](https://github.com/p-e-w/heretic) v1.0.1
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 15.10 |
| **attn.o_proj.max_weight** | 1.05 |
| **attn.o_proj.max_we... | [] |
AudenAI/auden-tta-m10 | AudenAI | 2026-01-24T00:11:56Z | 2 | 1 | null | [
"safetensors",
"tta",
"speech",
"translation",
"alignment",
"multilingual",
"retrieval",
"automatic-speech-recognition",
"en",
"zh",
"ja",
"ko",
"fr",
"es",
"pt",
"ru",
"vi",
"id",
"arxiv:2511.14410",
"license:apache-2.0",
"region:us"
] | automatic-speech-recognition | 2025-10-16T23:19:58Z | # TTA: Transcribe, Translate and Alignment for Cross-lingual Speech Representation
**TTA** is a multilingual model that jointly supports **transcribe**, **translate**, and **align**
tasks. It provides strong multilingual ASR/ST performance and cross-lingual speech retrieval
capability.
🔗 **Paper**: https://arxiv.org... | [] |
smolify/smolified-debug-run | smolify | 2026-03-25T21:09:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"text-generation-inference",
"smolify",
"dslm",
"text-generation",
"conversational",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-25T21:08:52Z | # 🤏 smolified-debug-run
> **Intelligence, Distilled.**
This is a **Domain Specific Language Model (DSLM)** generated by the **Smolify Foundry**.
It has been synthetically distilled from SOTA reasoning engines into a high-efficiency architecture, optimized for deployment on edge hardware (CPU/NPU) or low-VRAM enviro... | [] |
xpuenabler/gpt-oss-6.6b-8E-nf4-awq-optimum-static-128-decode | xpuenabler | 2026-04-29T04:06:58Z | 0 | 0 | openvino | [
"openvino",
"gpt_oss",
"nncf",
"nf4",
"gpt-oss",
"quantization",
"optimum-intel",
"npu",
"static-shape",
"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-experts",
"licen... | null | 2026-04-28T09:16:34Z | # gpt-oss-6.6b-8E · OpenVINO NF4 (Optimum-Intel · stateless · static shapes)
OpenVINO IR of [`AmanPriyanshu/gpt-oss-6.6b-specialized-all-pruned-moe-only-8-experts`](https://huggingface.co/AmanPriyanshu/gpt-oss-6.6b-specialized-all-pruned-moe-only-8-experts), weight-only quantized to **NF4 symmetric / per-channel** thr... | [] |
letheviet/gector-roberta-base-5k-onnx | letheviet | 2026-05-03T15:46:55Z | 0 | 0 | null | [
"onnx",
"gector",
"grammatical-error-correction",
"text-editing",
"license:mit",
"region:us"
] | null | 2026-05-03T15:39:11Z | # GECToR ONNX Runtime — `gector-roberta-base-5k`
Lightweight ONNX export of the GECToR grammatical error correction model.
## What's inside
| File | Purpose |
|---|---|
| `model.onnx` | ONNX Runtime model (detection + tag classification heads) |
| `config.json` | Model configuration (label mappings, thresholds) |
| ... | [] |
tylerxdurden/PolyChromaticLM-1.0-instruct-0.6B | tylerxdurden | 2026-03-07T00:41:28Z | 0 | 0 | pytorch | [
"pytorch",
"safetensors",
"instruct",
"sft",
"transformer",
"PolyGLU",
"activation-routing",
"math",
"research",
"from-scratch",
"text-generation",
"en",
"base_model:tylerxdurden/PolyChromaticLM-1.0-base-0.6B",
"base_model:finetune:tylerxdurden/PolyChromaticLM-1.0-base-0.6B",
"license:ap... | text-generation | 2026-03-07T00:23:56Z | <div align="center">
# PolyChromaticLM 1.0 Instruct (0.6B)
**A 597M-parameter transformer with biologically-inspired activation routing, fine-tuned for mathematical reasoning**
*SFT on ~347K math problems from Nemotron-Math-v2, with chain-of-thought solutions in ChatML format.*
[![Paper](https://img.shields.io/badg... | [] |
octava/whisper-small-ablation-0-3 | octava | 2025-12-08T08:07:06Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:fleurs",
"base_model:openai/whisper-small",
"base_model:finetune:openai/whisper-small",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-12-03T12:41:06Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-small-ablation-0-3
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-sma... | [] |
kuma-no-yapooh3/my-lora-model-V5 | kuma-no-yapooh3 | 2026-03-01T17:05:04Z | 50 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v5",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-01T07:58:18Z | # Qwen3-4B Structured Output LoRA (v1.3)
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 im... | [
{
"start": 142,
"end": 147,
"text": "QLoRA",
"label": "training method",
"score": 0.8398190140724182
},
{
"start": 583,
"end": 588,
"text": "QLoRA",
"label": "training method",
"score": 0.774651050567627
}
] |
zentom/embedding_model | zentom | 2025-11-30T11:23:40Z | 1 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"roberta",
"feature-extraction",
"sentence-similarity",
"transformers",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | sentence-similarity | 2025-11-30T11:20:16Z | # S-Biomed-Roberta-snli-multinli-stsb
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search. The base model used is [allenai/biomed_roberta_base](https://huggingface.co/allenai/... | [] |
PharMolix/BioMedGPT-Mol | PharMolix | 2026-02-02T11:24:01Z | 26 | 2 | null | [
"safetensors",
"qwen3",
"arxiv:2512.04629",
"arxiv:2402.09391",
"arxiv:2412.14642",
"arxiv:2502.13398",
"region:us"
] | null | 2026-02-02T06:43:58Z | ## BioMedGPT-Mol
BioMedGPT-Mol is a multimodal molecular language model jointly released by PharMolix Inc. and the Institute of AI Industry Research (AIR), Tsinghua University. It is built for both molecular understanding and generation, supporting a wide range of tasks inclu... | [] |
AlaaAlawdi/llama_finetune | AlaaAlawdi | 2026-04-21T03:52:19Z | 0 | 0 | null | [
"gguf",
"llama",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-21T03:51:39Z | # llama_finetune : 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 AlaaAlawdi/llama_finetune --jinja`
- For multimodal models: `llama-mtmd-cli -hf AlaaAlawdi/llama_finetune --jinja`
## Availab... | [
{
"start": 86,
"end": 93,
"text": "Unsloth",
"label": "training method",
"score": 0.7533679008483887
},
{
"start": 124,
"end": 131,
"text": "unsloth",
"label": "training method",
"score": 0.7957289218902588
},
{
"start": 509,
"end": 516,
"text": "unsloth",... |
apaszynska/pi05-portafilter-v2-200 | apaszynska | 2026-03-11T12:36:32Z | 31 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05",
"dataset:apaszynska/portafilter-to-grinder-v2-200",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-11T12:35:02Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
toshino/sft-01 | toshino | 2026-02-18T14:24:42Z | 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 | 2026-02-18T14:24:23Z | sft-01
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **structured output accuracy... | [
{
"start": 108,
"end": 113,
"text": "QLoRA",
"label": "training method",
"score": 0.8483780026435852
},
{
"start": 549,
"end": 554,
"text": "QLoRA",
"label": "training method",
"score": 0.7729055285453796
}
] |
CCSSNE/llmfan46-Gemma-3-12B-IT-Ultra-Uncensored-Heretic-ComfyUI | CCSSNE | 2026-04-21T04:21:12Z | 0 | 0 | transformers | [
"transformers",
"heretic",
"uncensored",
"decensored",
"abliterated",
"comfyui",
"text-encoder",
"gemma3",
"image-text-to-text",
"arxiv:1905.07830",
"arxiv:1905.10044",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1705.03551",
"arxiv:1911.01547",
"arxiv:1907.10641",
"arxiv:1903.001... | image-text-to-text | 2026-04-21T04:21:12Z | <div style="background-color: #ff4444; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
<h2 style="color: white; margin: 0 0 10px 0;">🚨⚠️ I HAVE REACHED HUGGING FACE'S FREE STORAGE LIMIT ⚠️🚨</h2>
<p style="font-size: 18px; margin: 0 0 15px 0;">I can no longer upload new models u... | [] |
FuryAssassin/TrainingStatusReport-v1 | FuryAssassin | 2026-02-13T20:17:27Z | 0 | 0 | transformers | [
"transformers",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2026-02-13T20:17:20Z | # MyAwesomeModel
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<img src="figures/fig1.png" width="60%" alt="MyAwesomeModel" />
</div>
<hr>
<div align="center" style="line-height: 1;">
<a href="LICENSE" style="m... | [
{
"start": 757,
"end": 770,
"text": "post-training",
"label": "training method",
"score": 0.8278292417526245
}
] |
XXXXyu/Falcon3-1B-Instruct-1.58bit-vlut-gguf | XXXXyu | 2026-01-01T08:43:18Z | 63 | 0 | vlut.cpp | [
"vlut.cpp",
"gguf",
"text-generation",
"conversational",
"ternary",
"quantized",
"edge-ai",
"on-device",
"en",
"arxiv:2512.06443",
"base_model:tiiuae/Falcon3-1B-Instruct-1.58bit",
"base_model:quantized:tiiuae/Falcon3-1B-Instruct-1.58bit",
"license:other",
"endpoints_compatible",
"region:... | text-generation | 2025-12-27T14:52:16Z | # Falcon3-1B-Instruct-1.58bit-vlut-gguf
This repository contains **state-of-the-art ternary-packed versions** of [Falcon3-1B-Instruct-1.58bit](https://huggingface.co/tiiuae/Falcon3-1B-Instruct-1.58bit) in GGUF format, optimized for efficient on-device inference using the [Vec-LUT](https://arxiv.org/abs/2512.06443) met... | [] |
rbelanec/train_hellaswag_1754507490 | rbelanec | 2025-08-07T04:31:44Z | 1 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"prompt-tuning",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | null | 2025-08-06T19:18:06Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# train_hellaswag_1754507490
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/met... | [] |
gnigguhface/gemma-3-27b-it-Q8_0-GGUF | gnigguhface | 2026-03-17T00:29:15Z | 17 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"base_model:google/gemma-3-27b-it",
"base_model:quantized:google/gemma-3-27b-it",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2026-03-17T00:27:08Z | # gnigguhface/gemma-3-27b-it-Q8_0-GGUF
This model was converted to GGUF format from [`google/gemma-3-27b-it`](https://huggingface.co/google/gemma-3-27b-it) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.... | [] |
priorcomputers/phi-3.5-mini-instruct-cn-problem-kr0.2-a0.01-creative | priorcomputers | 2026-02-02T07:58:04Z | 1 | 0 | null | [
"safetensors",
"phi3",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"custom_code",
"base_model:microsoft/Phi-3.5-mini-instruct",
"base_model:finetune:microsoft/Phi-3.5-mini-instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-02T07:56:49Z | # phi-3.5-mini-instruct-cn-problem-kr0.2-a0.01-creative
This is a **CreativityNeuro (CN)** modified version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct).
## Model Details
- **Base Model**: microsoft/Phi-3.5-mini-instruct
- **Modification**: CreativityNeuro weight scali... | [] |
mradermacher/Cortana-GGUF | mradermacher | 2025-09-21T08:20:11Z | 19 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"trl",
"sft",
"en",
"base_model:vijaykoushikblaze/Cortana",
"base_model:quantized:vijaykoushikblaze/Cortana",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-21T08:13:54Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
qing-yao/relfreq_n10000_nb150k_70m_ep1_lr1e-4_seed42 | qing-yao | 2025-12-29T02:26:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-70m",
"base_model:finetune:EleutherAI/pythia-70m",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-29T02:25:58Z | <!-- 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. -->
# relfreq_n10000_nb150k_70m_ep1_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://huggingface.co/... | [] |
jaydef/so101_pick_place_act_v2 | jaydef | 2026-02-26T23:13:17Z | 33 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:jaydef/so101_pick_place_v2",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-26T23:12:59Z | # 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":... |
huskyhong/wzryyykl-lbqh-szql | huskyhong | 2026-01-14T21:47:13Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-14T21:40:55Z | # 王者荣耀语音克隆-鲁班七号-时之奇旅
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... | [] |
huskyhong/wzryyykl-xs-xxs | huskyhong | 2026-01-10T04:00:32Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-10T03:54:55Z | # 王者荣耀语音克隆-西施-续相思
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_拒... | [] |
JayeeYi/clip-ViT-B-32-vision | JayeeYi | 2026-03-03T12:12:51Z | 12 | 0 | null | [
"onnx",
"clip_vision_model",
"image-classification",
"license:mit",
"region:us"
] | image-classification | 2026-03-03T12:12:50Z | ONNX port of [sentence-transformers/clip-ViT-B-32](https://huggingface.co/sentence-transformers/clip-ViT-B-32).
This model is intended to be used for image classification and similarity searches.
### Usage
Here's an example of performing inference using the model with [FastEmbed](https://github.com/qdrant/fastembed)... | [] |
Edge-Quant/Huihui-MoE-1.2B-A0.6B-Q4_K_M-GGUF | Edge-Quant | 2025-12-12T16:59:22Z | 16 | 0 | transformers | [
"transformers",
"gguf",
"moe",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"base_model:huihui-ai/Huihui-MoE-1.2B-A0.6B",
"base_model:quantized:huihui-ai/Huihui-MoE-1.2B-A0.6B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-12T16:59:14Z | # Edge-Quant/Huihui-MoE-1.2B-A0.6B-Q4_K_M-GGUF
This model was converted to GGUF format from [`huihui-ai/Huihui-MoE-1.2B-A0.6B`](https://huggingface.co/huihui-ai/Huihui-MoE-1.2B-A0.6B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original mode... | [] |
kingsleykim/Qwen2.5-Math-7B-PRM-Single | kingsleykim | 2025-11-23T01:32:04Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"chat",
"text-generation",
"conversational",
"en",
"arxiv:2409.12122",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-23T01:30:59Z | # Qwen2.5-Math-7B-Instruct
> [!Warning]
> <div align="center">
> <b>
> 🚨 Qwen2.5-Math mainly supports solving English and Chinese math problems through CoT and TIR. We do not recommend using this series of models for other tasks.
> </b>
> </div>
## Introduction
In August 2024, we released the first series of mathem... | [] |
iCIIT/redqueenprotocol-sin-llama3.2-3B-model | iCIIT | 2025-08-04T05:16:07Z | 85 | 1 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-3",
"sinhala",
"generative-qa",
"iciit-2025",
"lora",
"conversational",
"si",
"dataset:RedQueenProtocol/all-articles-from-sinhala-wikipedia-2025-parquet",
"dataset:RedQueenProtocol/sinhala-qna-530-rows",
"dataset:ihalage/sin... | text-generation | 2025-08-04T03:02:33Z | # RedQueen Llama 3.2 3B - Sinhala Generative QA
**Technical Report:** [Click here for pdf](https://drive.google.com/file/d/1XFPwiwTx5j8yxcBCxmyDZgK5ldpulFw-/view?usp=sharing)
<br>
**GitHub Repo for Scripts and Notebooks:** [Click here](https://github.com/scythe410/Below-8B-Sinhala-LLM-Training---RedQueen-Protocol)
- ... | [] |
SpencerSun/Qwen3.5-27B-heretic-v3-i1-GGUF | SpencerSun | 2026-03-30T03:51:08Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"en",
"base_model:llmfan46/Qwen3.5-27B-heretic-v3",
"base_model:quantized:llmfan46/Qwen3.5-27B-heretic-v3",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-30T03:51:08Z | ## 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_... | [] |
devil-egox/open-tutor-ia-gemma3-270M-Q8_0-GGUF | devil-egox | 2025-08-27T15:13:47Z | 4 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"gemma3_text",
"en",
"es",
"dataset:devil-egox/tutor",
"base_model:unsloth/gemma-3-270m-it",
"base_model:quantized:unsloth/gemma-3-270m-it",
"license:agpl-3.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-26T14:46:55Z | # Uploaded finetuned model
- **Developed by:** devil-egox
- **GitHub del proyecto:** https://github.com/Elmaldelego/OPEN-TUTOR-IA.git
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-3-270m-it
This gemma3_text model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Hu... | [
{
"start": 191,
"end": 198,
"text": "unsloth",
"label": "training method",
"score": 0.8612842559814453
},
{
"start": 267,
"end": 274,
"text": "Unsloth",
"label": "training method",
"score": 0.7806991934776306
},
{
"start": 305,
"end": 312,
"text": "unsloth... |
RomDev2/yolox-small | RomDev2 | 2026-03-12T18:06:52Z | 28 | 0 | yolox | [
"yolox",
"safetensors",
"object-detection",
"pytorch",
"license:apache-2.0",
"region:us"
] | object-detection | 2026-03-12T18:06:48Z | # yolox-small
This repository contains **YOLOX-small** weights exported to **`safetensors`** format.
## Source
These weights are derived from the official **YOLOX** project by **Megvii-BaseDetection**:
- Official repository: https://github.com/Megvii-BaseDetection/YOLOX
Original checkpoint source used fo... | [] |
Thireus/Qwen3.5-4B-THIREUS-Q8_0_R8-SPECIAL_SPLIT | Thireus | 2026-03-09T00:30:06Z | 13 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-03-08T22:36:58Z | # Qwen3.5-4B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.5-4B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.5-4B model (official repo: https://huggingface.co/Qwen/Qwen3.5-4B). These GGUF shards are designed to be used with **... | [] |
KS150/dpo-qwen-cot-merged_2 | KS150 | 2026-03-01T11:56:21Z | 23 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"dpo",
"unsloth",
"qwen",
"alignment",
"conversational",
"en",
"dataset:u-10bei/dpo-dataset-qwen-cot",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-gener... | text-generation | 2026-02-08T01:28:42Z | # qwen3-4b-dpo-qwen-cot-merged
This model is a fine-tuned version of **Qwen/Qwen3-4B-Instruct-2507** using **Direct Preference Optimization (DPO)** via the **Unsloth** library.
This repository contains the **full-merged 16-bit weights**. No adapter loading is required.
## Training Objective
This model has been opti... | [
{
"start": 111,
"end": 141,
"text": "Direct Preference Optimization",
"label": "training method",
"score": 0.8312693238258362
},
{
"start": 143,
"end": 146,
"text": "DPO",
"label": "training method",
"score": 0.8540997505187988
},
{
"start": 332,
"end": 335,
... |
legaliza-bit/cross-encoder-dbpedia | legaliza-bit | 2026-04-09T23:01:55Z | 22 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"cross-encoder",
"reranker",
"generated_from_trainer",
"dataset_size:110400",
"loss:BinaryCrossEntropyLoss",
"text-ranking",
"arxiv:1908.10084",
"base_model:cross-encoder/ms-marco-MiniLM-L6-v2",
"base_model:finetune:cross-encoder/ms-marco-MiniLM-... | text-ranking | 2026-04-09T22:59:38Z | # CrossEncoder based on cross-encoder/ms-marco-MiniLM-L6-v2
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [cross-encoder/ms-marco-MiniLM-L6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L6-v2) using the [sentence-transformers](https://www.SBERT.net... | [] |
Isk5434/qwen3-4b-structeval-lora5 | Isk5434 | 2026-02-07T10:37:44Z | 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 | 2026-02-07T10:37:30Z | ＜qwen3-4b-structeval-lora5＞
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 **struc... | [
{
"start": 129,
"end": 134,
"text": "QLoRA",
"label": "training method",
"score": 0.7522867918014526
}
] |
amps93/qwen3-tts-finetune-korean-woman-v4-epoch-9 | amps93 | 2026-03-28T08:10:13Z | 0 | 0 | null | [
"safetensors",
"qwen3_tts",
"arxiv:2601.15621",
"license:apache-2.0",
"region:us"
] | null | 2026-03-28T08:09:15Z | # Qwen3-TTS
## Overview
### Introduction
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_introduction.png" width="90%"/>
<p>
Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as... | [] |
BootesVoid/cme9wey430682rts8c0v462sg_cme9wmhyw0698rts82anzqb0x | BootesVoid | 2025-08-13T12:19:34Z | 0 | 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 | 2025-08-13T12:19:31Z | # Cme9Wey430682Rts8C0V462Sg_Cme9Wmhyw0698Rts82Anzqb0X
<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:... | [] |
NICKO/dpt-large-v12-fpq | NICKO | 2026-04-13T07:17:05Z | 0 | 0 | null | [
"bonfyre-fpq",
"v12",
"quantized",
"e8-lattice",
"rans-entropy",
"license:apache-2.0",
"region:us"
] | null | 2026-04-13T07:16:06Z | # DPT Large — BonfyreFPQ v12
Native `.fpq` v12 quantized weights for [Intel/dpt-large](https://huggingface.co/Intel/dpt-large).
## Model Info
| Property | Value |
|----------|-------|
| Architecture | Monocular Depth Estimation |
| Parameters | 344M |
| Original Size | 1304 MB (safetensors) |
| FPQ v12 Size | 329 MB... | [] |
MattosDev/foxy-atendimento-v1-GGUF | MattosDev | 2026-03-13T00:59:18Z | 60 | 0 | null | [
"gguf",
"llama",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-13T00:58:36Z | # foxy-atendimento-v1-GGUF : 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 MattosDev/foxy-atendimento-v1-GGUF --jinja`
- For multimodal models: `llama-mtmd-cli -hf MattosDev/foxy-atendimento-... | [
{
"start": 96,
"end": 103,
"text": "Unsloth",
"label": "training method",
"score": 0.7250546216964722
},
{
"start": 134,
"end": 141,
"text": "unsloth",
"label": "training method",
"score": 0.7853277325630188
},
{
"start": 537,
"end": 544,
"text": "unsloth"... |
satyajitdas/BharatSchemes-7B | satyajitdas | 2026-04-09T19:59:10Z | 0 | 0 | mlx | [
"mlx",
"india",
"government-schemes",
"welfare",
"bharatschemes",
"lora",
"qwen",
"text-generation",
"en",
"hi",
"dataset:satyajitdas/bharatschemes-v1",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-09T19:58:26Z | # BharatSchemes-7B
**India's first fine-tuned LLM for navigating government welfare schemes,
state programs, and corporate CSR/NGO initiatives.**
> Helping 1.4 billion citizens discover the support they're entitled to.
## Model Description
BharatSchemes-7B is a Qwen 2.5 7B Instruct model fine-tuned with LoRA on the... | [
{
"start": 309,
"end": 313,
"text": "LoRA",
"label": "training method",
"score": 0.7250236868858337
},
{
"start": 924,
"end": 928,
"text": "LoRA",
"label": "training method",
"score": 0.7782660126686096
},
{
"start": 966,
"end": 969,
"text": "MLX",
"la... |
manancode/opus-mt-gil-fr-ctranslate2-android | manancode | 2025-08-20T12:27:57Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-20T12:27:48Z | # opus-mt-gil-fr-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-gil-fr` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-gil-fr
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted ... | [] |
wikilangs/war | wikilangs | 2026-01-11T05:52:50Z | 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-austronesian_philippin... | text-generation | 2026-01-11T05:52:21Z | # Waray - Wikilangs Models
## Comprehensive Research Report & Full Ablation Study
This repository contains NLP models trained and evaluated by Wikilangs, specifically on **Waray** Wikipedia data.
We analyze tokenizers, n-gram models, Markov chains, vocabulary statistics, and word embeddings.
## 📋 Repository Contents... | [
{
"start": 1290,
"end": 1311,
"text": "Tokenizer Compression",
"label": "training method",
"score": 0.7102818489074707
}
] |
CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity | CrystalRaindropsFall | 2025-11-12T21:33:26Z | 2 | 0 | peft | [
"peft",
"safetensors",
"lora",
"gsm8k",
"math",
"reasoning",
"curriculum-learning",
"dataset:gsm8k",
"base_model:HuggingFaceTB/SmolLM2-135M",
"base_model:adapter:HuggingFaceTB/SmolLM2-135M",
"license:apache-2.0",
"region:us"
] | null | 2025-11-12T21:33:23Z | # SmolLM2-135M LoRA Adapter for GSM8K
This is a LoRA adapter for [HuggingFaceTB/SmolLM2-135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M) fine-tuned on the [GSM8K dataset](https://huggingface.co/datasets/gsm8k) for mathematical reasoning.
## Model Description
- **Base Model:** HuggingFaceTB/SmolLM2-135M
- **T... | [
{
"start": 338,
"end": 357,
"text": "Curriculum learning",
"label": "training method",
"score": 0.7803065180778503
},
{
"start": 930,
"end": 949,
"text": "curriculum learning",
"label": "training method",
"score": 0.7155089974403381
}
] |
gguf-org/chat | gguf-org | 2025-12-02T21:24:57Z | 45 | 4 | null | [
"gguf",
"gguf-connector",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-02T11:21:40Z | ## chat
- gpt-like dialogue interaction workflow (demonstration)
- simple but amazing multi-agent plus multi-modal implementation
- prepare your llm model (replaceable; can be serverless api endpoint)
- prepare your multimedia model(s), i.e., image, video (replaceable as well)
- call the specific agent/model by adding ... | [] |
birder-project/hieradet_d_small_dino-v2-imagenet12k | birder-project | 2026-01-16T10:31:54Z | 72 | 0 | birder | [
"birder",
"image-classification",
"pytorch",
"dataset:timm/imagenet-12k-wds",
"arxiv:2306.00989",
"arxiv:2408.00714",
"arxiv:2304.07193",
"base_model:birder-project/hieradet_d_small_dino-v2",
"base_model:finetune:birder-project/hieradet_d_small_dino-v2",
"license:apache-2.0",
"region:us"
] | image-classification | 2025-08-29T07:38:46Z | # Model Card for hieradet_d_small_dino-v2-imagenet12k
HieraDet (dynamic window size) small image classification model. The model follows a two-stage training process: first, DINOv2 pretraining, then fine-tuned on the `ImageNet-12K` dataset.
## Model Details
- **Model Type:** Image classification and detection backbo... | [
{
"start": 175,
"end": 193,
"text": "DINOv2 pretraining",
"label": "training method",
"score": 0.7454569935798645
}
] |
sik247/lexpt | sik247 | 2025-08-15T08:10:56Z | 0 | 2 | null | [
"safetensors",
"legal",
"law",
"caselaw",
"sft",
"lora",
"chatml",
"instruction-tuning",
"text-generation",
"conversational",
"en",
"dataset:common-pile/caselaw_access_project",
"base_model:openai/gpt-oss-20b",
"base_model:adapter:openai/gpt-oss-20b",
"license:cc-by-4.0",
"region:us"
] | text-generation | 2025-08-14T09:22:34Z | # LEXPT Law SFT (CAP subset)
## Dataset Summary
**LEXPT Law SFT** is a supervised fine-tuning corpus for **U.S. case-law analysis**. It provides **chat-style instruction/response** records derived from **public-domain judicial opinions** (e.g., the Caselaw Access Project, “CAP”) and lawyer-authored prompts targeting a... | [] |
leafsmomo/pi05_so101_v9 | leafsmomo | 2026-02-05T08:08:58Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:leafsmomo/eval_so101_act_v9",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-05T05:35:32Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
LDES777/ft_2_deepseek_merged | LDES777 | 2025-12-03T19:43:06Z | 0 | 0 | null | [
"pytorch",
"safetensors",
"llama",
"license:other",
"region:us"
] | null | 2025-12-03T19:39:55Z | <p align="center">
<img width="1000px" alt="DeepSeek Coder" src="https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/pictures/logo.png?raw=true">
</p>
<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://coder.deepseek.com/">[🤖 Chat with DeepSeek Coder]</a> | <a href="https... | [] |
kagyvro48/Diffusion-400-front-eye-crop-null-brute | kagyvro48 | 2026-02-03T05:59:55Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"diffusion",
"robotics",
"dataset:kagyvro48/arracher_une_mauvaise_herbe_400_front_eye",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-03T05:59:24Z | # 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 ... | [] |
crazyi/Qwopus3.6-27B-v1-preview-mlx-8bit | crazyi | 2026-04-28T11:39:14Z | 385 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"image-text-to-text",
"qwen",
"qwen3.6",
"qwopus",
"reasoning",
"instruct",
"conversational",
"vision-language-model",
"multimodal",
"transformers",
"unsloth",
"text-generation",
"en",
"zh",
"ja",
"ko",
"es",
"ru",
"dataset:Kassadin88/Claude... | text-generation | 2026-04-23T05:44:23Z | ---
library_name: mlx
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3.6-27B/blob/main/LICENSE
base_model: Jackrong/Qwopus3.6-27B-v1-preview
pipeline_tag: text-generation
language:
- en
- zh
- ja
- ko
- es
- ru
tags:
- qwen
- qwen3.6
- qwopus
- reasoning
- instruct
- conversational
- vision-language-... | [] |
mlx-community/Olmo-3-7B-Think-8bit | mlx-community | 2025-11-21T09:09:59Z | 7 | 1 | mlx | [
"mlx",
"safetensors",
"olmo3",
"text-generation",
"conversational",
"en",
"base_model:allenai/Olmo-3-7B-Think",
"base_model:quantized:allenai/Olmo-3-7B-Think",
"license:apache-2.0",
"8-bit",
"region:us"
] | text-generation | 2025-11-21T08:01:54Z | # mlx-community/Olmo-3-7B-Think-8bit
This model [mlx-community/Olmo-3-7B-Think-8bit](https://huggingface.co/mlx-community/Olmo-3-7B-Think-8bit) was
converted to MLX format from [allenai/Olmo-3-7B-Think](https://huggingface.co/allenai/Olmo-3-7B-Think)
using mlx-lm version **0.28.3**.
## Use with mlx
```bash
pip insta... | [] |
qing-yao/relfreq_nunique_nb300k_70m_ep10_lr1e-4_seed42 | qing-yao | 2025-12-29T03:29:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-70m",
"base_model:finetune:EleutherAI/pythia-70m",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-29T03:28:17Z | <!-- 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. -->
# relfreq_nunique_nb300k_70m_ep10_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-70m](https://huggingface.c... | [] |
Jackrong/MLX-Qwen3.5-4B-Neo-8bit | Jackrong | 2026-03-23T23:19:08Z | 22 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"lora",
"competitive-programming",
"text-generation",
"conversational",
"en",
"zh",
"ko",
"dataset:Jackrong/Competitive-Programming-python-blend",
"dataset:stepfun-ai/Step-3.5-Flash-SFT",
... | text-generation | 2026-03-23T23:16:44Z | # Jackrong/MLX-Qwen3.5-4B-Neo-8bit
This model [Jackrong/MLX-Qwen3.5-4B-Neo-8bit](https://huggingface.co/Jackrong/MLX-Qwen3.5-4B-Neo-8bit) was
converted to MLX format from [Jackrong/Qwen3.5-4B-Neo](https://huggingface.co/Jackrong/Qwen3.5-4B-Neo)
using mlx-lm version **0.30.7**.
## Use with mlx
```bash
pip install mlx... | [] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.