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 |
|---|---|---|---|---|---|---|---|---|---|---|
quickmt/quickmt-th-en | quickmt | 2026-04-13T23:00:37Z | 7 | 0 | null | [
"translation",
"en",
"th",
"dataset:quickmt/quickmt-train.th-en",
"license:cc-by-4.0",
"model-index",
"region:us"
] | translation | 2025-09-02T00:41:30Z | <a href="https://huggingface.co/spaces/quickmt/quickmt-gui"><img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/open-in-hf-spaces-lg-dark.svg" alt="Open in Spaces"></a>
# `quickmt-th-en` Neural Machine Translation Model
`quickmt-th-en` is a reasonably fast and reasonably accurate neural machine... | [] |
craa/exceptions_exp2_swap_0.7_last_to_push_2128 | craa | 2025-12-13T07:41:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-08T13:48:25Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width=... | [] |
gsjang/ko-llama-3-korean-bllossom-8b-x-meta-llama-3-8b-instruct-kv_ot_merge | gsjang | 2025-09-15T02:46:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:MLP-KTLim/llama-3-Korean-Bllossom-8B",
"base_model:merge:MLP-KTLim/llama-3-Korean-Bllossom-8B",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:merge:meta-llama/Meta-Llama-... | text-generation | 2025-09-15T02:43:03Z | # ko-llama-3-korean-bllossom-8b-x-meta-llama-3-8b-instruct-kv_ot_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-llama/Meta... | [
{
"start": 248,
"end": 259,
"text": "KV-OT Merge",
"label": "training method",
"score": 0.8862341046333313
},
{
"start": 735,
"end": 746,
"text": "kv_ot_merge",
"label": "training method",
"score": 0.7704027891159058
}
] |
typhoon-ai/typhoon2.5-qwen3-30b-a3b-gguf | typhoon-ai | 2025-10-23T11:57:45Z | 232 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:typhoon-ai/typhoon2.5-qwen3-30b-a3b",
"base_model:quantized:typhoon-ai/typhoon2.5-qwen3-30b-a3b",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-10-23T11:53:14Z | # scb10x/typhoon2.5-qwen3-30b-a3b-gguf
This model was converted to GGUF format from [`scb10x/typhoon2.5-qwen3-30b-a3b`](https://huggingface.co/scb10x/typhoon2.5-qwen3-30b-a3b) 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](... | [] |
lava123456/smolvla-oneepisode-8b797537 | lava123456 | 2026-03-13T17:09:33Z | 30 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:qualiaadmin/oneepisode",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-13T17:09:15Z | # 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... | [] |
mradermacher/Nomadic-Wizard-0G-v1.0-GGUF | mradermacher | 2025-08-27T08:46:58Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Pragmanic0/Nomadic-Wizard-0G-v1.0",
"base_model:quantized:Pragmanic0/Nomadic-Wizard-0G-v1.0",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-08-27T08:19:24Z | ## 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... | [] |
zonglin11/svla_so100_pickplace | zonglin11 | 2025-08-19T23:52:29Z | 4 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:lerobot/svla_so100_pickplace",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-19T23:48:06Z | # 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... | [] |
Shekswess/tiny-think-dpo-math-stem-apo_zero-beta0_3-lr3e-6-e1-bs8 | Shekswess | 2026-01-28T11:03:14Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"llama4_text",
"text-generation",
"generated_from_trainer",
"dpo",
"trl",
"conversational",
"arxiv:2305.18290",
"base_model:Shekswess/tiny-think-sft-math-stem-loss-nll-bf16-lr2e-5-e2-bs8",
"base_model:finetune:Shekswess/tiny-think-sft-math-stem-loss-nll-bf16-lr2e-5... | text-generation | 2026-01-18T22:33:15Z | # Model Card for tiny-think-dpo-math-stem-apo_zero-beta0_3-lr3e-6-e1-bs8
This model is a fine-tuned version of [Shekswess/tiny-think-sft-math-stem-loss-nll-bf16-lr2e-5-e2-bs8](https://huggingface.co/Shekswess/tiny-think-sft-math-stem-loss-nll-bf16-lr2e-5-e2-bs8).
It has been trained using [TRL](https://github.com/hugg... | [
{
"start": 292,
"end": 295,
"text": "TRL",
"label": "training method",
"score": 0.7727842926979065
},
{
"start": 386,
"end": 389,
"text": "DPO",
"label": "training method",
"score": 0.7942554354667664
}
] |
MElHuseyni/mxbai-edge-colbert-v0-17mv3-tr | MElHuseyni | 2025-10-31T20:57:28Z | 2 | 0 | PyLate | [
"PyLate",
"safetensors",
"modernbert",
"ColBERT",
"sentence-transformers",
"sentence-similarity",
"feature-extraction",
"generated_from_trainer",
"dataset_size:910904",
"loss:Contrastive",
"tr",
"dataset:parsak/msmarco-tr",
"arxiv:1908.10084",
"base_model:mixedbread-ai/mxbai-edge-colbert-v... | sentence-similarity | 2025-10-31T20:57:21Z | # PyLate model based on mixedbread-ai/mxbai-edge-colbert-v0-17m
This is a [PyLate](https://github.com/lightonai/pylate) model finetuned from [mixedbread-ai/mxbai-edge-colbert-v0-17m](https://huggingface.co/mixedbread-ai/mxbai-edge-colbert-v0-17m) on the [msmarco-tr](https://huggingface.co/datasets/parsak/msmarco-tr) d... | [
{
"start": 2,
"end": 8,
"text": "PyLate",
"label": "training method",
"score": 0.9238971471786499
},
{
"start": 76,
"end": 82,
"text": "PyLate",
"label": "training method",
"score": 0.8878198266029358
},
{
"start": 538,
"end": 544,
"text": "PyLate",
"l... |
contemmcm/f836ba7a8b6b63b23b2d7dfe73e6a93b | contemmcm | 2025-11-04T09:16:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"opt",
"text-classification",
"generated_from_trainer",
"base_model:facebook/opt-1.3b",
"base_model:finetune:facebook/opt-1.3b",
"license:other",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-04T08:57:42Z | <!-- 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. -->
# f836ba7a8b6b63b23b2d7dfe73e6a93b
This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.... | [
{
"start": 497,
"end": 505,
"text": "F1 Macro",
"label": "training method",
"score": 0.7193776965141296
}
] |
calebboud/vibescript | calebboud | 2025-12-26T14:35:20Z | 4 | 0 | null | [
"safetensors",
"gguf",
"vibescript",
"code-compression",
"lora",
"qwen3",
"text-generation",
"en",
"base_model:Qwen/Qwen3-1.7B",
"base_model:adapter:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-12-26T14:28:38Z | # VibeScript - Code to DSL Converter
**vibecoder-discern** converts natural language and code into VibeScript - a compact symbolic DSL for expressing programming concepts.
## What is VibeScript?
VibeScript compresses verbose code into symbolic notation:
| Code | VibeScript |
|------|------------|
| `function add(a,... | [] |
majentik/Leanstral-TurboQuant-MLX-4bit | majentik | 2026-04-13T09:15:45Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"mistral3",
"turboquant",
"kv-cache-quantization",
"4-bit",
"weight-quantization",
"leanstral",
"lean4",
"formal-proofs",
"theorem-proving",
"quantized",
"apple-silicon",
"mistral",
"moe",
"arxiv:2504.19874",
"base_model:mistralai/Leanstral-2603",
"base_model:... | null | 2026-04-13T02:20:07Z | # Leanstral-TurboQuant-MLX-4bit
**4-bit MLX weight-quantized [Leanstral-2603](https://huggingface.co/mistralai/Leanstral-2603) with [TurboQuant](https://arxiv.org/abs/2504.19874) KV-cache quantization for Lean 4 formal proof generation on Apple Silicon.**
Leanstral is the first open-source AI agent purpose-built for ... | [] |
clarin-pl/combo-nlp-xlm-roberta-base-ukrainian-parlamint-ud2.17 | clarin-pl | 2026-04-12T03:08:57Z | 0 | 0 | null | [
"pytorch",
"dependency-parsing",
"combo",
"universal-dependencies",
"token-classification",
"uk",
"dataset:universal_dependencies",
"license:cc-by-sa-4.0",
"region:us"
] | token-classification | 2026-04-12T02:47:43Z | # COMBO-NLP Model for Ukrainian
## Model Description
This is a Ukrainian-language model based on [COMBO-NLP](https://gitlab.clarin-pl.eu/syntactic-tools/combo-nlp), an open-source natural language preprocessing system. It performs:
- sentence segmentation (via [LAMBO](https://gitlab.clarin-pl.eu/syntactic-tools/lamb... | [] |
fenghora/SegviGen | fenghora | 2026-03-19T06:50:11Z | 0 | 1 | null | [
"3d",
"segmentation",
"other",
"arxiv:2603.16869",
"license:mit",
"region:us"
] | other | 2026-03-16T04:24:55Z | # SegviGen: Repurposing 3D Generative Model for Part Segmentation
SegviGen is a framework for 3D part segmentation that leverages the rich 3D structural and textural knowledge encoded in large-scale 3D generative models. It learns to predict part-indicative colors while reconstructing geometry, and unifies three setti... | [] |
pdjohn/EuroBERT-610m-term-sense-balanced | pdjohn | 2026-02-10T21:37:25Z | 6 | 0 | null | [
"safetensors",
"eurobert",
"text-classification",
"term-sense-disambiguation",
"international-relations",
"political-science",
"german",
"custom_code",
"de",
"dataset:custom",
"base_model:EuroBERT/EuroBERT-610m",
"base_model:finetune:EuroBERT/EuroBERT-610m",
"doi:10.57967/hf/7612",
"licens... | text-classification | 2025-12-12T16:20:18Z | # T-EBERT: German IR Term Sense Disambiguation
Fine-tuned [EuroBERT-610M](https://huggingface.co/EuroBERT/EuroBERT-610m) on **balanced data** for distribution-robust German IR term sense disambiguation.
## Model Description
This is a **distribution-robust variant** of [T-EBERT](https://huggingface.co/pdjohn/EuroBERT... | [
{
"start": 2,
"end": 9,
"text": "T-EBERT",
"label": "training method",
"score": 0.8785319924354553
},
{
"start": 273,
"end": 280,
"text": "T-EBERT",
"label": "training method",
"score": 0.8607611656188965
},
{
"start": 513,
"end": 520,
"text": "T-EBERT",
... |
m7admehrnia/ppo-Huggy | m7admehrnia | 2025-09-16T22:23:44Z | 1 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | reinforcement-learning | 2025-09-16T22:23:38Z | # **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We... | [] |
Mungert/GLM-ASR-Nano-2512-GGUF | Mungert | 2025-12-22T17:48:40Z | 196 | 5 | transformers | [
"transformers",
"gguf",
"automatic-speech-recognition",
"en",
"zh",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | automatic-speech-recognition | 2025-12-22T16:52:23Z | # <span style="color: #7FFF7F;">GLM-ASR-Nano-2512 GGUF Models</span>
## <span style="color: #7F7FFF;">Model Generation Details</span>
This model was generated using [llama.cpp](https://github.com/ggerganov/llama.cpp) at commit [`e1f15b454`](https://github.com/ggerganov/llama.cpp/commit/e1f15b454fbadfddf8f1ec450bf6d3... | [] |
buelfhood/irplag_codebert_ep30_bs16_lr3e-05_l512_s42_ppn_f_beta_score | buelfhood | 2025-11-16T16:57:26Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:microsoft/codebert-base",
"base_model:finetune:microsoft/codebert-base",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-16T16:30:42Z | <!-- 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. -->
# irplag_codebert_ep30_bs16_lr3e-05_l512_s42_ppn_f_beta_score
This model is a fine-tuned version of [microsoft/codebert-base](https... | [] |
mradermacher/Medllama-3-8b-GGUF | mradermacher | 2025-09-12T05:16:39Z | 2 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Axcel1/Medllama-3-8b",
"base_model:quantized:Axcel1/Medllama-3-8b",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-12T03:32:28Z | ## 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... | [] |
LeonMiao/ViRC-7B | LeonMiao | 2026-04-09T17:33:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"agent",
"conversational",
"en",
"dataset:LeonMiao/CRUX",
"arxiv:2512.14654",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"... | image-text-to-text | 2026-04-09T17:17:29Z | <div align="center">
<img src="docs/logo.png" alt="logo" height="150">
<h1 style="font-size: 32px; font-weight: bold;"> [CVPR 2026] VɪRC: Enhancing Visual Interleaved Mathematical CoT with Reason Chunking </h1>
<a href="https://arxiv.org/abs/2512.14654v3"><img src="https://img.shields.io/badge/ArXiv-ViRC-brown?l... | [] |
FunctionZero/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive | FunctionZero | 2026-05-04T11:51:55Z | 0 | 0 | null | [
"gguf",
"uncensored",
"gemma4",
"abliterated",
"vision",
"multimodal",
"audio",
"image-text-to-text",
"en",
"multilingual",
"license:gemma",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | image-text-to-text | 2026-05-04T11:51:55Z | # Gemma-4-E4B-Uncensored-HauhauCS-Aggressive
> **[Join the Discord](https://discord.gg/SZ5vacTXYf)** for updates, roadmaps, projects, or just to chat.
Gemma 4 E4B-IT uncensored by HauhauCS. **0/465 Refusals\***
> **HuggingFace's "Hardware Compatibility" widget doesn't recognize K_P quants** — it may show fewer files... | [] |
priorcomputers/llama-3.1-8b-instruct-cn-story-kr0.2-a0.5-creative | priorcomputers | 2026-02-03T10:44:22Z | 1 | 0 | null | [
"safetensors",
"llama",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-03T10:42:06Z | # llama-3.1-8b-instruct-cn-story-kr0.2-a0.5-creative
This is a **CreativityNeuro (CN)** modified version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
## Model Details
- **Base Model**: meta-llama/Llama-3.1-8B-Instruct
- **Modification**: CreativityNeuro weight scali... | [] |
tonyho5689/distilbert-yelp-sentiment | tonyho5689 | 2026-03-14T07:09:11Z | 108 | 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 | 2026-03-14T03:04:03Z | <!-- 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-yelp-sentiment
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-... | [
{
"start": 445,
"end": 456,
"text": "F1 Weighted",
"label": "training method",
"score": 0.8880190253257751
},
{
"start": 1176,
"end": 1187,
"text": "F1 Weighted",
"label": "training method",
"score": 0.8891867995262146
}
] |
servantofares/Qwen3-Coder-Next | servantofares | 2026-03-23T03:54:10Z | 258 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_next",
"text-generation",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-23T03:54:07Z | # Qwen3-Coder-Next
## Highlights
Today, we're announcing **Qwen3-Coder-Next**, an open-weight language model designed specifically for coding agents and local development. It features the following key enhancements:
- **Super Efficient with Significant Performance**: With only 3B activated parameters (80B total pa... | [
{
"start": 1322,
"end": 1349,
"text": "Pretraining & Post-training",
"label": "training method",
"score": 0.7965291142463684
}
] |
INTERX/Qwen3-GenX1.9-30B-A3B-LoRA | INTERX | 2025-12-31T08:32:39Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"chat",
"manufacturing",
"lora",
"text-generation",
"conversational",
"ko",
"en",
"base_model:Qwen/Qwen3-30B-A3B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-30B-A3B-Instruct-2507",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-31T01:11:29Z | # Qwen3-GenX1.9-30B-A3B-LoRA
## GenX Overview
**GenX**는 INTERX Gen.AI 팀에서 개발한 제조 특화 언어 모델입니다.
GenX는 자체 수집한 제조 도메인 데이터를 이용해 학습되었으며, 뛰어난 제조 지식을 바탕으로 사용자의 물음에 더 길고 정확하며 자세한 답변을 제공합니다.
## Model Details
- **Qwen3-GenX1.9-30B-A3B-LoRA**는 Qwen3-30B-A3B-Instruct-2507를 베이스 모델로 사용하여 LoRA로 Supervised Finetuning을 수행하였습니다.
- 학습 데... | [] |
Athulkrishna/vrclc-Whisper-medium-Malayalam-acft | Athulkrishna | 2026-03-15T13:57:28Z | 0 | 0 | null | [
"safetensors",
"automatic-speech-recognition",
"whisper",
"futo",
"acft",
"ggml",
"ml",
"base_model:vrclc/Whisper-medium-Malayalam",
"base_model:finetune:vrclc/Whisper-medium-Malayalam",
"license:apache-2.0",
"region:us"
] | automatic-speech-recognition | 2026-03-15T13:41:11Z | # Malayalam Whisper to FUTO Keyboard: Full Pipeline
This repository contains an end-to-end Jupyter Notebook pipeline designed to prepare Hugging Face Whisper models for use with the FUTO Keyboard on Android.
The pipeline specifically focuses on adapting Malayalam Whisper models (such as `whisper-small-malayalam`) by ... | [] |
aivanni/pi05_algebra_9000 | aivanni | 2026-03-28T22:20:19Z | 45 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:aivanni/so101-algebra",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-28T22:19:36Z | # 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... | [] |
enigmaceo/svm-classification-cat-and-dog | enigmaceo | 2026-03-30T22:03:43Z | 0 | 0 | scikit-learn | [
"scikit-learn",
"svm",
"classification",
"cat-vs-dog",
"machine-learning",
"region:us"
] | null | 2026-03-30T22:00:26Z | # Cat vs Dog SVM Classification Model
This repository contains the trained SVM model and preprocessing artifacts for cat vs dog image classification.
## Model Files
- `svm_best_model.pkl.gz` - Compressed SVM model (RBF kernel, ~15MB)
- `scaler.pkl` - Feature scaling preprocessing object
- `label_encoder.pkl` - Label... | [] |
melon1891/qwen3-4b-structured-output-lora-v6 | melon1891 | 2026-02-07T13:23:28Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v4",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-07T13:23:05Z | qwen3-4b-structured-output-lora-v6
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve ... | [
{
"start": 136,
"end": 141,
"text": "QLoRA",
"label": "training method",
"score": 0.7831355333328247
}
] |
mahiyama/splade-modernbert-ja-310m-onnx-int8 | mahiyama | 2026-05-01T08:59:09Z | 0 | 0 | optimum | [
"optimum",
"onnx",
"modernbert",
"int8",
"quantized",
"sparse-encoder",
"splade",
"sparse",
"cpu-inference",
"information-retrieval",
"japanese",
"feature-extraction",
"ja",
"dataset:mahiyama/auto-wiki-qa",
"dataset:mahiyama/JaGovFaqs-22k",
"dataset:mahiyama/kosodate-faq-pairs-ja",
"... | feature-extraction | 2026-05-01T08:58:11Z | # splade-modernbert-ja-310m-onnx-int8
[mahiyama/splade-modernbert-ja-310m](https://huggingface.co/mahiyama/splade-modernbert-ja-310m)
を CPU 推論向けに ONNX 化 + 動的 INT8 量子化 したバリアントです。
オンライン検索のクエリエンコーダ用途を想定し、1 リクエストの低レイテンシ
を最優先に最適化しています。
## ハイライト
| 指標 | 元の PyTorch (CPU) | 本モデル (ONNX INT8 / CPU) | 改善 |
|------|-------------... | [] |
khtsly/Qwen3.5-27B-Abliterated-Claude-4.6-Opus-Distilled-32k | khtsly | 2026-03-08T17:50:58Z | 416 | 0 | null | [
"safetensors",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"lora",
"qlora",
"luau",
"abliterated",
"heretic",
"image-text-to-text",
"conversational",
"en",
"zh",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtered",
"base_model:huihui-ai/Huihui-Qwen3.5-... | image-text-to-text | 2026-03-08T11:14:39Z | # Qwen3.5-27B-Abliterated-Claude-4.6-Opus-Distilled-32k
## Performance
| Metric | This model | [Baseline](https://huggingface.co/khtsly/Qwen3.5-27B-Claude-4.6-Opus-Distilled-32k) |
| :----- | :--------: | :---------------------------: |
| **KL divergence** | 0.0556 | - |
| **Refusals** | 12/100 | 94/100 |
## # Train... | [] |
huskyhong/wzryyykl-zgl-syts | huskyhong | 2026-01-14T08:08:52Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-14T08:03:46Z | # 王者荣耀语音克隆-诸葛亮-时雨天司
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... | [] |
onnxmodelzoo/resnet34-v2-7 | onnxmodelzoo | 2025-09-30T22:34:18Z | 0 | 0 | null | [
"onnx",
"validated",
"vision",
"classification",
"resnet",
"en",
"arxiv:1512.03385",
"arxiv:1603.05027",
"license:apache-2.0",
"region:us"
] | null | 2025-09-30T22:34:08Z | <!--- SPDX-License-Identifier: Apache-2.0 -->
# ResNet
## Use cases
ResNet models perform image classification - they take images as input and classify the major object in the image into a set of pre-defined classes. They are trained on ImageNet dataset which contains images from 1000 classes. ResNet models prov... | [
{
"start": 1108,
"end": 1112,
"text": "ONNX",
"label": "training method",
"score": 0.7786703109741211
},
{
"start": 1169,
"end": 1173,
"text": "ONNX",
"label": "training method",
"score": 0.7985188961029053
},
{
"start": 1231,
"end": 1235,
"text": "ONNX",
... |
DunnBC22/opt-2.7b-Fine_Tuned-Essays_with_Instructions | DunnBC22 | 2026-04-04T15:58:25Z | 15 | 1 | peft | [
"peft",
"en",
"dataset:ChristophSchuhmann/essays-with-instructions",
"license:other",
"region:us"
] | null | 2023-08-08T21:50:13Z | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_doubl... | [] |
oukhan/dqn-SpaceInvaderNoFrameskip-v4 | oukhan | 2026-01-25T23:30:08Z | 3 | 0 | stable-baselines3 | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2026-01-25T23:29:34Z | # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework... | [] |
amd/DeepSeek-R1-Distill-Qwen-7B-onnx-ryzenai-hybrid | amd | 2025-10-23T15:31:43Z | 1 | 0 | null | [
"onnx",
"ryzenai-hybrid",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"license:mit",
"region:us"
] | null | 2025-09-28T19:20:27Z | # amd/DeepSeek-R1-Distill-Qwen-7B-hybrid
- ## Introduction
This model was prepared using the AMD Quark Quantization tool, followed by necessary post-processing.
- ## Quantization Strategy
- AWQ / Group 128 / Asymmetric / UINT4 Weights / BFP16 activations
- Excluded Layers: None
-
- ## Quick Start
For quicks... | [] |
ojayy/llama32-3b-mmlu-clinical_knowledge-full | ojayy | 2025-11-25T09:58:51Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-3B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-25T09:57:08Z | # Model Card for clinical_knowledge_full
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If y... | [] |
BootesVoid/cmfsv32p00dldx0n0h4l8dloa_cmftfxamd0dvlx0n0alf9sef7 | BootesVoid | 2025-09-21T09:06:47Z | 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 | 2025-09-21T09:06:46Z | # Cmfsv32P00Dldx0N0H4L8Dloa_Cmftfxamd0Dvlx0N0Alf9Sef7
<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:... | [] |
Arz99/bert-finetuned-ner | Arz99 | 2025-11-15T14:00:14Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"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"
] | token-classification | 2025-11-09T14:31:14Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None da... | [] |
mradermacher/Mistral-Small-3.2-24B-Instruct-2506-Text-Only-heretic-i1-GGUF | mradermacher | 2025-12-15T13:21:37Z | 197 | 1 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:arnomatic/Mistral-Small-3.2-24B-Instruct-2506-Text-Only-heretic",
"base_model:quantized:arnomatic/Mistral-Small-3.2-24B-Instruct-2506-Text-Only-heretic",
"endpoints_compatible",
"region:us",
"imatri... | null | 2025-12-15T10:03:18Z | ## 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_... | [] |
X-Humanoid/WoW-1-Wan-14B-600k | X-Humanoid | 2025-10-22T08:57:49Z | 6 | 6 | transformers | [
"transformers",
"diffusers",
"safetensors",
"i2v",
"video-generation",
"robotics",
"embodied-ai",
"physical-reasoning",
"causal-reasoning",
"inverse-dynamics",
"wow",
"arxiv:2509.22642",
"en",
"dataset:WoW-world-model/WoW-1-Benchmark-Samples",
"license:mit",
"endpoints_compatible",
"... | null | 2025-10-15T07:53:38Z | # 🤖 WoW-1-Wan-14B-2M
**WoW-1-Wan-14B** is a 14-billion-parameter generative world model trained on **2 million real-world robot interaction trajectories**. It is designed to imagine, reason, and act in physically consistent environments, powered by SOPHIA-guided refinement and a co-trained **Inverse Dynamics Model**.... | [] |
Denali-AI/qwen3-vl-2b-instruct-base | Denali-AI | 2026-03-31T04:12:47Z | 0 | 0 | null | [
"vision-language",
"qwen3vl",
"zero-shot",
"baseline",
"garment-classification",
"base_model:Qwen/Qwen3-VL-2B-Instruct",
"base_model:finetune:Qwen/Qwen3-VL-2B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-03-31T00:59:57Z | # Qwen3-VL-2B-Instruct (Base)
> Zero-shot baseline of Qwen3-VL-2B-Instruct for garment classification. This is the base model before any Denali-AI fine-tuning. Ranked **#4/17** on the Denali-AI eval_hard_3500 benchmark with **76.4%** weighted score (zero-shot).
## Model Details
| Property | Value |
|----------|-----... | [] |
mradermacher/K2-Think-abliterated-GGUF | mradermacher | 2025-09-27T01:18:52Z | 3 | 2 | transformers | [
"transformers",
"gguf",
"en",
"base_model:nicoboss/K2-Think-abliterated",
"base_model:quantized:nicoboss/K2-Think-abliterated",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-14T06:09:40Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static quants of https://huggingface.co/nicoboss/K2-Think-abliterated
<!-- provided... | [] |
leesstra/gemma3-1b-lora-model | leesstra | 2025-10-20T02:34:42Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/gemma-3-1b-it",
"base_model:finetune:google/gemma-3-1b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-10-20T02:18:33Z | # Model Card for gemma3-1b-lora-model
This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but ... | [] |
PuxAI/phobert-student-distilled | PuxAI | 2026-03-05T12:44:21Z | 15 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"token-classification",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | token-classification | 2026-03-05T12:44:14Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# phobert-student-distilled
This model was trained from scratch on the None dataset.
It achieves the following results on the evalu... | [] |
DCAgent/a1-freelancer | DCAgent | 2026-04-04T20:22:23Z | 646 | 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 | 2026-03-25T19:50:55Z | <!-- 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. -->
# sft_a1_freelancer__Qwen3-8B
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the /e... | [] |
Temmp1e/so101_smolVLA | Temmp1e | 2025-08-28T17:48:49Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Temmp1e/Grab_pen",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-20T03:06:00Z | # 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... | [] |
mradermacher/gemma-4-E4B-it-ARA-heresy-i1-GGUF | mradermacher | 2026-04-26T05:41:04Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"en",
"base_model:MuXodious/gemma-4-E4B-it-ARA-heresy",
"base_model:quantized:MuXodious/gemma-4-E4B-it-ARA-heresy",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
... | null | 2026-04-26T05:11:10Z | ## 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_... | [] |
arianaazarbal/qwen3-4b-20260108_055759_lc_rh_sot_recon_gen_def_tra-414974-step200 | arianaazarbal | 2026-01-08T10:06:39Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-01-08T10:06:08Z | # qwen3-4b-20260108_055759_lc_rh_sot_recon_gen_def_tra-414974-step200
## Experiment Info
- **Full Experiment Name**: `20260108_055759_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_recontextualization_gen_default_train_style_oldlp_training_seed65`
- **Short Name**: `20260108_055759_lc_rh_sot_recon_gen_def_t... | [] |
TeichAI/Qwen3-4B-Instruct-2507-Claude-Opus-3-Distill | TeichAI | 2025-12-26T05:43:58Z | 52 | 4 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"text-generation-inference",
"unsloth",
"agent",
"conversational",
"dataset:NoSlop4U/opus-3-1000x",
"base_model:unsloth/Qwen3-4B-Instruct-2507",
"base_model:finetune:unsloth/Qwen3-4B-Instruct-2507",
"endpoints_compatible",
"region:us... | text-generation | 2025-12-26T05:15:27Z | # Qwen3 4B Instruct 2507 - Claude Opus 3 Distill
This model was trained on a non-reasoning dataset of **Claude Opus 3**.
- 🧬 Datasets:
- `NoSlop4U/opus-3-1000x`
- 🏗 Base Model:
- `unsloth/Qwen3-4B-Instruct-2507`
- ⚡ Use cases:
- Coding
- Agent
- Deep Research
- ∑ Stats (Dataset)
- Big th... | [
{
"start": 187,
"end": 194,
"text": "unsloth",
"label": "training method",
"score": 0.8983465433120728
},
{
"start": 485,
"end": 492,
"text": "unsloth",
"label": "training method",
"score": 0.774143636226654
}
] |
Muapi/giger-2_0 | Muapi | 2025-08-28T17:30:48Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-28T17:30:35Z | # Giger 2_0
**Base model**: Flux.1 D
**Trained words**: g1g3r by giger
## 🧠 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 = {"Content-Type... | [] |
DARKSURGEON/medic-ai-model | DARKSURGEON | 2026-03-15T13:30:10Z | 12 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/mistral-7b-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"base_model:unsloth/mistral-7b-bnb-4bit",
"region:us"
] | text-generation | 2026-03-15T13:09:31Z | # Model Card for medic-ai-model
This model is a fine-tuned version of [unsloth/mistral-7b-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-bnb-4bit).
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... | [] |
AnonymousCS/populism_classifier_305 | AnonymousCS | 2025-08-26T07:22:46Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_english_bert_base_cased",
"base_model:finetune:AnonymousCS/populism_english_bert_base_cased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"regio... | text-classification | 2025-08-26T07:21:47Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# populism_classifier_305
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_base_cased](https://huggingface.... | [] |
RodrigoAlons/RodriAlons-bert-toxic-comment | RodrigoAlons | 2026-01-15T01:23:39Z | 1 | 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 | 2026-01-15T01:23:07Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# RodriAlons-bert-toxic-comment
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-b... | [] |
OpenMed/OpenMed-PII-Portuguese-BiomedBERT-Base-110M-v1 | OpenMed | 2026-04-20T11:44:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"ner",
"pii",
"pii-detection",
"de-identification",
"privacy",
"healthcare",
"medical",
"clinical",
"phi",
"portuguese",
"pytorch",
"openmed",
"pt",
"base_model:microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract",
"... | token-classification | 2026-04-20T11:43:58Z | # OpenMed-PII-Portuguese-BiomedBERT-Base-110M-v1
**Portuguese PII Detection Model** | 110M Parameters | Open Source
[]() []() [![Recall](https://img.shields.io/badge/Recall-88.18%25-orang... | [] |
samwell/medasr-ghana-v2 | samwell | 2026-01-20T07:57:01Z | 6 | 1 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"lasr_ctc",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:google/medasr",
"base_model:finetune:google/medasr",
"license:other",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-01-20T06:49:49Z | <!-- 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. -->
# medasr-ghana-v2
This model is a fine-tuned version of [google/medasr](https://huggingface.co/google/medasr) on the None dataset.
... | [] |
zaros12/TinyLlama-1.1B-Chat-v1.0-Q5_K_M-GGUF | zaros12 | 2025-09-05T19:37:34Z | 0 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"en",
"dataset:cerebras/SlimPajama-627B",
"dataset:bigcode/starcoderdata",
"dataset:HuggingFaceH4/ultrachat_200k",
"dataset:HuggingFaceH4/ultrafeedback_binarized",
"base_model:TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"base_model:quantized:TinyLlama/TinyLlama-1.1B-C... | null | 2025-09-05T19:37:27Z | # zaros12/TinyLlama-1.1B-Chat-v1.0-Q5_K_M-GGUF
This model was converted to GGUF format from [`TinyLlama/TinyLlama-1.1B-Chat-v1.0`](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [origina... | [] |
frankenstein-ai/admin-leeway-raiment-20251126t180549 | frankenstein-ai | 2025-11-26T18:06:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"mergekit",
"merge",
"base_model:DogOnKeyboard/Mistral-7B-Heretic-V2",
"base_model:merge:DogOnKeyboard/Mistral-7B-Heretic-V2",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:merge:mistralai/Mistral-7B-Instruct-v0.3",
"tex... | text-generation | 2025-11-26T18:05:49Z | # merge_output
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 merge:
... | [
{
"start": 193,
"end": 198,
"text": "SLERP",
"label": "training method",
"score": 0.7212499380111694
},
{
"start": 806,
"end": 811,
"text": "slerp",
"label": "training method",
"score": 0.8350362777709961
}
] |
lemon07r/VellumMini-0.1-Qwen3-14B | lemon07r | 2025-10-06T04:40:53Z | 1 | 4 | null | [
"safetensors",
"qwen3",
"dataset:N8Programs/CreativeGPT",
"base_model:Qwen/Qwen3-14B",
"base_model:finetune:Qwen/Qwen3-14B",
"license:apache-2.0",
"region:us"
] | null | 2025-10-05T07:42:18Z | # VellumMini-0.1-Qwen3-14B
Just a sneak peek of what I'm cooking in a little project called Vellum. This model was made to evaluate the quality of the CreativeGPT dataset, and how well Qwen3 trains on it. This is just one of many datasets that the final model will be trained on (which will also be using a different bas... | [] |
mynkjd/watergel | mynkjd | 2025-08-22T08:15:03Z | 3 | 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 | 2025-08-22T08:15:01Z | # Watergel
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-traine... | [] |
knowledgator/gliner-decoder-base-v1.0 | knowledgator | 2025-08-16T09:31:06Z | 8 | 11 | gliner | [
"gliner",
"pytorch",
"NER",
"encoder",
"decoder",
"GLiNER",
"information-extraction",
"token-classification",
"en",
"base_model:HuggingFaceTB/SmolLM2-135M-Instruct",
"base_model:finetune:HuggingFaceTB/SmolLM2-135M-Instruct",
"license:apache-2.0",
"region:us"
] | token-classification | 2025-08-15T06:33:07Z | 
**GLiNER** is a Named Entity Recognition (NER) model capable of identifying *any* entity type in a **zero-shot** manner.
This architecture combines:
* An **encoder** for representing entity spans
* A... | [] |
tinutmap/ai-browsing-categories-text | tinutmap | 2025-09-19T22:28:51Z | 1 | 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 | 2025-09-12T20:53:47Z | <!-- 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. -->
# ai-browsing-categories-text
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-bas... | [] |
sncffcns/my-lora-adapter-5k-mix-sft | sncffcns | 2026-02-06T12:56:49Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:daichira/structured-5k-mix-sft",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-05T12:11:17Z | qwen3-4b-structured-output-lora-5k-mix-sft
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 ... | [
{
"start": 144,
"end": 149,
"text": "QLoRA",
"label": "training method",
"score": 0.7890908122062683
}
] |
Chesterlyt/stable-diffusion-v1-5 | Chesterlyt | 2026-02-18T13:00:39Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"arxiv:2207.12598",
"arxiv:2112.10752",
"arxiv:2103.00020",
"arxiv:2205.11487",
"arxiv:1910.09700",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"... | text-to-image | 2026-02-18T13:00:39Z | # Stable Diffusion v1-5 Model Card
### ⚠️ This repository is a mirror of the now deprecated `ruwnayml/stable-diffusion-v1-5`, this repository or organization are not affiliated in any way with RunwayML.
Modifications to the original model card are in <span style="color:crimson">red</span> or <span style="color:darkgre... | [] |
mradermacher/gpt-oss-safeguard-20b-GGUF | mradermacher | 2025-10-30T09:55:18Z | 27 | 0 | transformers | [
"transformers",
"gguf",
"vllm",
"en",
"base_model:openai/gpt-oss-safeguard-20b",
"base_model:quantized:openai/gpt-oss-safeguard-20b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-30T07:46:19Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: MXFP4_MOE x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->... | [] |
majentik/gemma-4-E2B-it-RotorQuant-GGUF-IQ4_XS | majentik | 2026-04-15T23:08:14Z | 540 | 0 | gguf | [
"gguf",
"rotorquant",
"kv-cache-quantization",
"gemma",
"gemma4",
"edge",
"instruct",
"llama-cpp",
"quantized",
"image-text-to-text",
"arxiv:2504.19874",
"base_model:google/gemma-4-E2B-it",
"base_model:quantized:google/gemma-4-E2B-it",
"license:apache-2.0",
"endpoints_compatible",
"reg... | image-text-to-text | 2026-04-13T15:10:27Z | # gemma-4-E2B-it-RotorQuant-GGUF-IQ4_XS
GGUF IQ4_XS weight-quantized variant of [google/gemma-4-E2B-it](https://huggingface.co/google/gemma-4-E2B-it) optimised for use with **RotorQuant** KV cache compression via a dedicated llama.cpp fork.
> **Important:** RotorQuant KV cache types (`planar3`, `iso3`) are **not** av... | [] |
Carlosdca/sentiment-xlm-batch4 | Carlosdca | 2025-11-18T21:33:36Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-18T21:31:45Z | <!-- 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. -->
# sentiment-xlm-batch4
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the N... | [
{
"start": 426,
"end": 434,
"text": "F1 Macro",
"label": "training method",
"score": 0.8197619915008545
},
{
"start": 445,
"end": 456,
"text": "F1 Weighted",
"label": "training method",
"score": 0.9067288041114807
},
{
"start": 467,
"end": 482,
"text": "Pr... |
Outlier-Ai/Outlier-Compact-27B-MLX-4bit | Outlier-Ai | 2026-05-01T02:27:15Z | 12 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"outlier",
"apple-silicon",
"4-bit",
"text-generation",
"qwen3.6",
"deprecated",
"macos",
"mac",
"m1",
"m2",
"m3",
"m4",
"local-llm",
"offline",
"on-device",
"conversational",
"en",
"zh",
"fr",
"es",
"pt",
"de",
"it",
"ru",
"ja",... | text-generation | 2026-04-30T04:35:11Z | # Outlier Compact 27B (MLX-4bit) — RENAMED TO CORE
> **This repo has been renamed.**
>
> The "Compact" tier was renamed to **Core** for the Outlier 1.6.0 ship.
>
> **This repo will be deprecated 2026-05-30. Migrate downloads to
> [Outlier-Ai/Outlier-Core-27B-MLX-4bit](https://huggingface.co/Outlier-Ai/Outlier-Core-27B... | [] |
mradermacher/gemma-3-270m-it-finetuned-financial-assistant-GGUF | mradermacher | 2025-11-16T16:58:49Z | 20 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"gemma3_text",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-16T16:56:49Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/Huihui-LFM2-24B-A2B-abliterated-i1-GGUF | mradermacher | 2026-03-10T10:19:29Z | 2,931 | 4 | transformers | [
"transformers",
"gguf",
"liquid",
"lfm2",
"edge",
"moe",
"abliterated",
"uncensored",
"en",
"ar",
"zh",
"fr",
"de",
"ja",
"ko",
"es",
"base_model:huihui-ai/Huihui-LFM2-24B-A2B-abliterated",
"base_model:quantized:huihui-ai/Huihui-LFM2-24B-A2B-abliterated",
"license:other",
"endp... | null | 2026-03-10T08:02:24Z | ## 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_... | [] |
temaq-org/Tema_Q-X2-4B-Thinking | temaq-org | 2026-03-06T11:59:55Z | 36 | 1 | null | [
"safetensors",
"qwen3_5_text",
"qwen",
"qwen3_5",
"transformer",
"instruction-tuned",
"multilingual",
"uncensored",
"non-censored",
"unfiltered",
"text-generation",
"conversational",
"ja",
"en",
"base_model:Qwen/Qwen3.5-4B",
"base_model:finetune:Qwen/Qwen3.5-4B",
"region:us"
] | text-generation | 2026-03-06T07:41:51Z | # 🚀 Tema_Q-X2-Thinking
---
## 🔥 モデル概要
**Tema_Q-X2-Thinking（天馬求）** は、アリババが開発したモデル **Qwen3.5 4B** を基盤にした、**日本語、英語**向けの改良版大規模言語モデル（LLM）です。
通常のQwenモデルでは回答が難しいプロンプトに対しても、より自由で有用な応答を生成できるよう設計されています。4Bモデルのため、Thinking使用時は... | [] |
kagyvro48/SmolVLA-100-finetuned-conservative | kagyvro48 | 2025-12-03T09:16:31Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:kagyvro48/arracher_une_mauvaise_herbe_100",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-03T09:15:45Z | # 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... | [] |
simonycl/Qwen_Qwen3-4B-Instruct-2507-HaluEval-MULTI_DPO | simonycl | 2026-03-24T04:04:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"endpoints_compatible",
"region:us"
] | null | 2026-03-24T01:57:21Z | # Model Card for Qwen_Qwen3-4B-Instruct-2507-HaluEval-MULTI_DPO
This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
que... | [
{
"start": 976,
"end": 979,
"text": "DPO",
"label": "training method",
"score": 0.8581277132034302
},
{
"start": 1270,
"end": 1273,
"text": "DPO",
"label": "training method",
"score": 0.8616107106208801
}
] |
NibiruTwin/qwen3-4b-structured-output-lora-v6 | NibiruTwin | 2026-02-28T08:09:13Z | 26 | 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 | 2026-02-26T14:43:13Z | qwen3-4b-structured-output-lora-v6
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve ... | [
{
"start": 136,
"end": 141,
"text": "QLoRA",
"label": "training method",
"score": 0.7969365119934082
}
] |
smutuvi/ndizi-whisper-large-v3-turbo-optimized | smutuvi | 2026-01-17T20:09:14Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:mit",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-01-17T17:58:46Z | <!-- 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. -->
# ndizi-whisper-large-v3-turbo-optimized
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.... | [] |
mradermacher/Nanbeige4-3B-Thinking-Ties-i1-GGUF | mradermacher | 2025-12-22T12:35:34Z | 122 | 1 | transformers | [
"transformers",
"gguf",
"merge",
"mergekit",
"lazymergekit",
"Nanbeige/Nanbeige4-3B-Thinking-2511",
"C10X/Nanbeige4-3B-Thinking-2511-Claude-4.5-Opus-High-Reasoning-Distill-V2-heretic",
"arnomatic/Nanbeige4-3B-Thinking-2511-heretic",
"en",
"base_model:bunnycore/Nanbeige4-3B-Thinking-Ties",
"base_... | null | 2025-12-22T09:44:48Z | ## 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_... | [] |
EleutherAI/neox-ckpt-pythia-160m-seed6 | EleutherAI | 2026-02-12T04:02:55Z | 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 | 2026-02-03T08:11:10Z | # Pythia-160M-seed6 GPT-NeoX Checkpoints
This repository contains the raw [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) training checkpoints for [Pythia-160M-seed6](https://huggingface.co/EleutherAI/pythia-160m-seed6), part of the [PolyPythias](https://huggingface.co/collections/EleutherAI/polypythias) suite. The... | [] |
poltextlab/xlm-roberta-large-i5-binary-codebook-v16 | poltextlab | 2026-04-10T12:28:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"pytorch",
"en",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:cc-by-4.0",
"model-index",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-10T12:27:28Z | # xlm-roberta-large-i5-binary-codebook-v16
# How to use the model
```python
from transformers import AutoTokenizer, pipeline
tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-large")
pipe = pipeline(
model="poltextlab/xlm-roberta-large-i5-binary-codebook-v16",
task="text-classification",
tokenizer=... | [] |
Thireus/GLM-5-THIREUS-IQ4_K_R4-SPECIAL_SPLIT | Thireus | 2026-04-04T17:23:22Z | 0 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-04-04T16:15:33Z | # GLM-5
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/GLM-5-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the GLM-5 model (official repo: https://huggingface.co/zai-org/GLM-5). These GGUF shards are designed to be used with **Thireus’ GGUF Too... | [] |
psm0206/act_so101_v2 | psm0206 | 2026-03-26T10:57:21Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:edgarkim/so101_test_0113_mimic_2",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-26T10:56:54Z | # 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":... |
arpitha9380/CatvsDog | arpitha9380 | 2026-02-13T07:13:22Z | 0 | 0 | null | [
"region:us"
] | null | 2026-02-13T07:12:55Z | # Cat vs Dog Image Classification
A simple web application built with Flask and TensorFlow/Keras that classifies images as either a **Cat** or a **Dog** using a Convolutional Neural Network (CNN).
## 🚀 Features
- **Image Upload:** Users can upload images in various formats (JPG, PNG, GIF, BMP).
- **CNN Class... | [] |
IGNF/FLAIR-HUB_LPIS-I_swinbase-upernet | IGNF | 2026-04-28T09:46:16Z | 0 | 0 | pytorch | [
"pytorch",
"semantic segmentation",
"landcover",
"image-segmentation",
"dataset:IGNF/FLAIR-HUB",
"arxiv:2506.07080",
"license:etalab-2.0",
"model-index",
"region:us"
] | image-segmentation | 2025-06-02T17:50:06Z | <div style="font-family:sans-serif; background-color:#F8F5F5; color:black; padding:25px; border-radius:10px; margin:auto; border:0px; ">
<!-- Collection Section -->
<div style="background:#FFFFFF; color:black; padding:20px; border-radius:8px; box-shadow:0 2px 5px rgba(0,0,0,0.05); margin-bottom:20px;">
<h1 sty... | [] |
inference4j/ms-marco-MiniLM-L-6-v2 | inference4j | 2026-02-13T23:44:08Z | 0 | 0 | onnx | [
"onnx",
"cross-encoder",
"text-classification",
"reranking",
"ms-marco",
"search",
"inference4j",
"license:apache-2.0",
"region:us"
] | text-classification | 2026-02-13T23:44:06Z | # ms-marco-MiniLM-L-6-v2 (Cross-Encoder) — ONNX
ONNX export of [ms-marco-MiniLM-L-6-v2](https://huggingface.co/Xenova/ms-marco-MiniLM-L-6-v2), a cross-encoder model trained on MS MARCO passage ranking data. Scores query-document pairs for search result reranking.
Mirrored for use with [inference4j](https://github.com... | [] |
mradermacher/Hemlock-Qwen3-Coder-REAP-25B-A3B-GGUF | mradermacher | 2025-12-19T00:51:57Z | 40 | 1 | transformers | [
"transformers",
"gguf",
"en",
"dataset:nbeerbower/hemlock-sft-v0.1",
"base_model:nbeerbower/Hemlock-Qwen3-Coder-REAP-25B-A3B",
"base_model:quantized:nbeerbower/Hemlock-Qwen3-Coder-REAP-25B-A3B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-18T16:16:03Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/P1-VL-235B-A22B-GGUF | mradermacher | 2026-02-15T11:49:20Z | 35 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:PRIME-RL/P1-VL-235B-A22B",
"base_model:quantized:PRIME-RL/P1-VL-235B-A22B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-15T06:00:11Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
qualiaadmin/smolvla_base | qualiaadmin | 2025-10-31T13:22:11Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:lerobot/svla_so101_pickplace",
"arxiv:2506.01844",
"region:us"
] | robotics | 2025-10-31T13:22:07Z | ## SmolVLA: A vision-language-action model for affordable and efficient robotics
Resources and technical documentation:
[SmolVLA Paper](https://huggingface.co/papers/2506.01844)
[SmolVLA Blogpost](https://huggingface.co/blog/smolvla)
[Code](https://github.com/huggingface/lerobot/blob/main/lerobot/common/policies/sm... | [
{
"start": 3,
"end": 10,
"text": "SmolVLA",
"label": "training method",
"score": 0.8568968772888184
},
{
"start": 123,
"end": 130,
"text": "SmolVLA",
"label": "training method",
"score": 0.8002141118049622
},
{
"start": 228,
"end": 235,
"text": "smolvla",
... |
mradermacher/twinx-wife-GGUF | mradermacher | 2025-10-21T06:35:15Z | 13 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:jeffreyyan8/twinx-wife",
"base_model:quantized:jeffreyyan8/twinx-wife",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-21T06:26:25Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
orionshaw777/gpt2-belle-sft-offcial-1st-re-pre-train | orionshaw777 | 2025-09-26T06:36:22Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:orionshaw777/gpt2-belle-sft-offcial-1st",
"base_model:finetune:orionshaw777/gpt2-belle-sft-offcial-1st",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us... | text-generation | 2025-09-24T08:41:20Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# codeparrot-ds
This model is a fine-tuned version of [orionshaw777/gpt2-belle-sft-offcial-1st](https://huggingface.co/orionshaw777... | [] |
MochiMomo1/qwen3-4b-lora-adapter | MochiMomo1 | 2026-02-18T07:13:06Z | 0 | 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 | 2026-02-16T10:49:13Z | qwen3-4b-structured-output-sft-lora
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve... | [
{
"start": 137,
"end": 142,
"text": "QLoRA",
"label": "training method",
"score": 0.842872679233551
},
{
"start": 191,
"end": 195,
"text": "LoRA",
"label": "training method",
"score": 0.7011516690254211
},
{
"start": 578,
"end": 583,
"text": "QLoRA",
"... |
progmars/whisper-large-v3-turbo-lv | progmars | 2026-02-16T17:52:25Z | 0 | 0 | null | [
"safetensors",
"lv",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:mit",
"region:us"
] | null | 2026-01-21T15:30:48Z | Šis ir OpenAI Whisper-large-v3-turbo modelis, apmācīts (finetune) ar attīrītu "Mozilla Foundation / Common Voice Scripted Speech 24.0 - Latvian" datu kopu. Rezultātā sasniegta transkripcijas precizitāte, kas lielā daļā gadījumu pārsniedz whisper-large-v3 (ne turbo) papildus neapmācītu modeli.
Ir pieejami arī CT2 svari... | [
{
"start": 56,
"end": 64,
"text": "finetune",
"label": "training method",
"score": 0.8413557410240173
}
] |
mradermacher/Goetia-24B-v1.2-i1-GGUF | mradermacher | 2026-01-27T06:57:02Z | 132 | 1 | transformers | [
"transformers",
"gguf",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"romance",
"all genres",
"story",
"writing",
"vivid prosing",
"vivid writin... | null | 2026-01-27T03:46:04Z | ## 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_... | [] |
ramesh070/mms-malayalam-binary | ramesh070 | 2025-12-03T08:07:32Z | 73 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"base_model:facebook/mms-300m",
"base_model:finetune:facebook/mms-300m",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | audio-classification | 2025-12-03T07:22:42Z | <!-- 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. -->
# mms-malayalam-binary
This model is a fine-tuned version of [facebook/mms-300m](https://huggingface.co/facebook/mms-300m) on the N... | [] |
dv347/qwen2.5-7b_smcalflow-add-remove-n2-p20 | dv347 | 2026-02-25T03:16:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-02-25T02:49:26Z | # Model Card for qwen2.5-7b_smcalflow-add-remove-n2-p20
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If yo... | [] |
cyberagent/ca-reward-3b-ja | cyberagent | 2026-03-03T09:26:53Z | 41 | 10 | null | [
"safetensors",
"llama",
"text-classification",
"ja",
"base_model:sbintuitions/sarashina2.2-3b-instruct-v0.1",
"base_model:finetune:sbintuitions/sarashina2.2-3b-instruct-v0.1",
"license:apache-2.0",
"region:us"
] | text-classification | 2025-08-07T11:43:32Z | # cyberagent/ca-reward-3b-ja
- 軽量な日本語報酬モデルの開発を目的として実装したモデルを公開する。
- 既存の指示文と新たに合成した指示文に対して、応答文を複数生成し、llm-as-a-judgeで疑似選好ラベルを付与することで疑似選好データセットを作成した。
- 上記の疑似選好データセットを分類するモデルを学習することで、指示文に対する応答文の好ましさを定量化する報酬モデルを作成した。
## 評価
- 人手で選好ラベル（好ましい応答文か、好ましくない応答文）が付与された既存のデータセットを収集し、選好ラベルの分類精度(Accuracy)を評価した。
- 既存の報酬モデルによる分類精度と、`gpt... | [] |
reasonableplan/kanana-nano-2.1b-instruct-finace_news-finetuning-100 | reasonableplan | 2026-01-06T03:51:04Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:kakaocorp/kanana-nano-2.1b-instruct",
"base_model:finetune:kakaocorp/kanana-nano-2.1b-instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-01-06T03:35:20Z | # Model Card for kanana-nano-2.1b-instruct-finace_news-finetuning-100
This model is a fine-tuned version of [kakaocorp/kanana-nano-2.1b-instruct](https://huggingface.co/kakaocorp/kanana-nano-2.1b-instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformer... | [] |
qualiaadmin/9d64e1d4-9205-4c6d-a02d-ce3d3fceada5 | qualiaadmin | 2025-09-24T15:28:26Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Calvert0921/SmolVLA_LiftBlueCubeDouble_Franka_200",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-24T15:25:47Z | # 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... | [] |
Muapi/soft-world-ce-sdxl-flux | Muapi | 2025-09-03T04:28:14Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-03T04:27:57Z | # Soft World - CE - SDXL & Flux
**Base model**: Flux.1 D
**Trained words**: sftwrldCE style, quilted, patchwork
## 🧠 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_... | [] |
mradermacher/LinAlgZero-SFT-merged-GGUF | mradermacher | 2025-11-25T21:09:08Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen2",
"trl",
"en",
"base_model:atomwalk12/LinalgZero-SFT-merged",
"base_model:quantized:atomwalk12/LinalgZero-SFT-merged",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-23T21:50:04Z | ## 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... | [] |
mattbucci/gemma-4-26B-A4B-it-AWQ-GPTQ-v2-fixed | mattbucci | 2026-04-15T13:18:30Z | 0 | 0 | null | [
"safetensors",
"gemma4",
"awq",
"4-bit",
"rdna4",
"gfx1201",
"rocm",
"sglang",
"quantized",
"license:apache-2.0",
"region:us"
] | null | 2026-04-15T05:29:06Z | # Gemma 4 26B MoE AWQ 4-bit
AWQ 4-bit quantization of [Gemma 4 26B-A4B-it](https://huggingface.co/google/gemma-4-26b-a4b-it) optimized for AMD RDNA4 (gfx1201) inference with [SGLang](https://github.com/sgl-project/sglang).
## Model Details
| | |
|---|---|
| **Base model** | [google/gemma-4-26b-a4b-it](https://huggin... | [] |
pcvlab/unetplusplus_pvd_vs_rd | pcvlab | 2026-03-05T03:47:23Z | 27 | 0 | erdes | [
"erdes",
"safetensors",
"unetplusplus",
"ocular-ultrasound",
"medical-imaging",
"3d-classification",
"retinal-detachment",
"image-classification",
"arxiv:2508.04735",
"license:cc-by-4.0",
"region:us"
] | image-classification | 2026-03-05T03:47:16Z | # UNETPLUSPLUS — Pvd Vs Rd
Trained model weights for **PVD vs. RD classification** using ocular ultrasound videos.
| Resource | Link |
|----------|------|
| Paper | [](https://arxiv.org/abs/2508.04735) |
| Dataset | [![HF Dataset](https://img.shields.i... | [] |
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