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 30 |
|---|---|---|---|---|---|---|---|---|---|---|
mradermacher/SwarmMed-14B-v2-merged-i1-GGUF | mradermacher | 2026-02-27T07:00:16Z | 2,532 | 0 | transformers | [
"transformers",
"gguf",
"medical",
"healthcare",
"clinical-reasoning",
"platinum-pairs",
"cove-verified",
"chain-of-thought",
"fine-tuned",
"lora-merged",
"qwen2",
"conversational",
"swarm-and-bee",
"en",
"dataset:SwarmandBee/SwarmMed-Platinum-1K",
"base_model:SwarmandBee/SwarmMed-14B-... | null | 2026-02-27T04:05:04Z | ## 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_... | [] |
darkmaniac7/Gemma-4-E4B-it-heretic-MNN | darkmaniac7 | 2026-04-12T20:31:53Z | 0 | 0 | null | [
"mnn",
"gemma4",
"gemma-4",
"mobile",
"on-device",
"tokforge",
"int4",
"text-generation",
"en",
"base_model:coder3101/gemma-4-E4B-it-heretic",
"base_model:finetune:coder3101/gemma-4-E4B-it-heretic",
"license:gemma",
"region:us"
] | text-generation | 2026-04-12T04:40:58Z | # Gemma-4-E4B-it-heretic-MNN
Pre-converted `coder3101/gemma-4-E4B-it-heretic` in MNN format for TokForge on-device inference.
> Requires **TokForge 3.4.9 or later**.
These Gemma 4 bundles depend on the updated TokForge 3.4.9 runtime and patched `libMNN.so` with Gemma 4 attention-scale support. Older TokForge builds ... | [
{
"start": 2,
"end": 28,
"text": "Gemma-4-E4B-it-heretic-MNN",
"label": "benchmark name",
"score": 0.7657577395439148
},
{
"start": 55,
"end": 77,
"text": "gemma-4-E4B-it-heretic",
"label": "benchmark name",
"score": 0.7569931745529175
},
{
"start": 175,
"end"... |
jefferyclements/Huihui-Qwen3.5-35B-A3B-abliterated | jefferyclements | 2026-04-09T13:21:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5_moe",
"image-text-to-text",
"abliterated",
"uncensored",
"conversational",
"base_model:Qwen/Qwen3.5-35B-A3B",
"base_model:finetune:Qwen/Qwen3.5-35B-A3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-09T13:21:25Z | # huihui-ai/Huihui-Qwen3.5-35B-A3B-abliterated
This is an uncensored version of [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
This is a crude... | [] |
mradermacher/gpt-oss-20b-Derestricted-GGUF | mradermacher | 2025-11-28T08:19:32Z | 1,047 | 10 | transformers | [
"transformers",
"gguf",
"abliterated",
"derestricted",
"gpt-oss-20b",
"openai",
"unlimited",
"uncensored",
"en",
"base_model:ArliAI/gpt-oss-20b-Derestricted",
"base_model:quantized:ArliAI/gpt-oss-20b-Derestricted",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-11-28T02:14:52Z | ## 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: -->... | [] |
mwangiderrick640/XTTS-v2 | mwangiderrick640 | 2026-05-03T12:59:16Z | 0 | 0 | coqui | [
"coqui",
"text-to-speech",
"license:other",
"region:us"
] | text-to-speech | 2026-05-03T12:59:16Z | # ⓍTTS
ⓍTTS is a Voice generation model that lets you clone voices into different languages by using just a quick 6-second audio clip. There is no need for an excessive amount of training data that spans countless hours.
This is the same or similar model to what powers [Coqui Studio](https://coqui.ai/) and [Coqui API]... | [] |
serlinaprianita/humanoid-chef-model | serlinaprianita | 2026-01-12T10:42:24Z | 3 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:distilbert/distilgpt2",
"base_model:finetune:distilbert/distilgpt2",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-12T10:41:26Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# humanoid-chef-model
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
... | [
{
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"text": "learning_rate",
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},
{
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"end": 615,
"text": "2e-05",
"label": "evaluation metric",
"score": 0.7341811060905457
},
{
"start": 640,
"end": 655,
"text": ... |
freddyaboulton/3b-es_it-ft-research_release-Q4_K_M-GGUF | freddyaboulton | 2025-04-09T20:17:15Z | 494 | 1 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-to-speech",
"es",
"it",
"base_model:canopylabs/3b-es_it-ft-research_release",
"base_model:quantized:canopylabs/3b-es_it-ft-research_release",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-to-speech | 2025-04-09T20:17:03Z | # freddyaboulton/3b-es_it-ft-research_release-Q4_K_M-GGUF
This model was converted to GGUF format from [`canopylabs/3b-es_it-ft-research_release`](https://huggingface.co/canopylabs/3b-es_it-ft-research_release) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
... | [] |
sowilow/gpt-oss-20b-DGX-Spark-GGUF | sowilow | 2026-04-13T05:16:27Z | 269 | 0 | gguf | [
"gguf",
"4-bit",
"8-bit",
"Blackwell",
"DGX-Spark",
"MoE",
"dgx-spark",
"gpt-oss",
"llama-cpp",
"nvidia",
"quantization",
"text-generation",
"en",
"ko",
"zh",
"arxiv:2508.10925",
"base_model:openai/gpt-oss-20b",
"base_model:quantized:openai/gpt-oss-20b",
"license:apache-2.0",
"... | text-generation | 2026-04-07T02:21:44Z | ---
## 🚀 v0.1.6: Real-time Metrics & Blackwell-Optimized Docker (Recommended)
This model is fully compatible with the **[DGX-Spark-llama.cpp-Bench](https://github.com/sowilow/DGX-Spark-llama.cpp-Bench)**.
Experience the state-of-the-art inference engine optimized for NVIDIA Blackwell (DGX Spark) hardware.
### 🌟 Ke... | [
{
"start": 342,
"end": 371,
"text": "Real-time Performance Metrics",
"label": "evaluation metric",
"score": 0.8089001178741455
},
{
"start": 391,
"end": 400,
"text": "Input TPS",
"label": "evaluation metric",
"score": 0.6684489250183105
},
{
"start": 407,
"end... |
Deaquay/G4-MeroMero-26B-A4B-NVFP4 | Deaquay | 2026-04-22T06:43:15Z | 0 | 0 | null | [
"safetensors",
"gemma4",
"nvfp4",
"dataset:zerofata/Instruct-Anime",
"dataset:zerofata/Gemini-3.1-Pro-SmallWiki",
"dataset:zerofata/Gemini-3.1-Pro-GLM5-Characters",
"dataset:zerofata/Roleplay-Anime-Characters",
"dataset:neuralmagic/calibration",
"base_model:zerofata/G4-MeroMero-26B-A4B",
"base_mod... | null | 2026-04-22T06:19:50Z | # Deaquay/G4-MeroMero-26B-A4B-NVFP4
This model [Deaquay/G4-MeroMero-26B-A4B-NVFP4](https://huggingface.co/Deaquay/G4-MeroMero-26B-A4B-NVFP4) was converted to NVFP4 format from [zerofata/G4-MeroMero-26B-A4B](https://huggingface.co/zerofata/G4-MeroMero-26B-A4B) using [llm-compressor](https://github.com/vllm-project/llm-... | [] |
xboy-352/ppo-pyramids | xboy-352 | 2025-12-07T12:10:40Z | 1 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Pyramids",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | reinforcement-learning | 2025-12-07T09:55:49Z | # **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
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/... | [] |
mystorm/FastVGGT | mystorm | 2025-09-08T08:57:41Z | 0 | 2 | null | [
"image-to-3d",
"arxiv:2509.02560",
"base_model:facebook/VGGT_tracker_fixed",
"base_model:finetune:facebook/VGGT_tracker_fixed",
"license:mit",
"region:us"
] | image-to-3d | 2025-09-08T08:25:24Z | <div align="center">
<h2>⚡️ FastVGGT: Training-Free Acceleration of Visual Geometry Transformer</h2>
<p align="center">
<a href="https://arxiv.org/abs/2509.02560"><img src="https://img.shields.io/badge/arXiv-FastVGGT-red?logo=arxiv" alt="Paper PDF"></a>
<a href="https://mystorm16.github.io/fastvggt/"><img src="h... | [
{
"start": 1179,
"end": 1194,
"text": "ScanNet dataset",
"label": "evaluation dataset",
"score": 0.6246384978294373
}
] |
ylu-pdm/sarm-warsaw-hack-right | ylu-pdm | 2026-01-24T21:31:38Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"sarm",
"robotics",
"dataset:ylu-pdm/warsaw-hack-right",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-24T17:57:19Z | # Model Card for sarm
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.c... | [
{
"start": 651,
"end": 658,
"text": "dataset",
"label": "evaluation dataset",
"score": 0.6061295866966248
}
] |
ninjaoden/smolvla_nmini_pick | ninjaoden | 2026-04-05T03:51:24Z | 4 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:ninjaoden/nmini_pick",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-31T13:38:24Z | # 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... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
vinnyduplessis/vinny-lora | vinnyduplessis | 2025-10-17T18:48:28Z | 2 | 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 | 2025-10-17T18:20:32Z | # Vinny Lora
<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-trai... | [] |
maxbittker/opus-27b-py-step210-2026-05-02 | maxbittker | 2026-05-02T20:42:34Z | 0 | 0 | tinker | [
"tinker",
"safetensors",
"lora",
"rl",
"opus-magnum",
"python",
"base_model:Qwen/Qwen3.5-27B",
"base_model:adapter:Qwen/Qwen3.5-27B",
"license:other",
"region:us"
] | null | 2026-05-02T20:38:49Z | # opus-27b-py-step210-2026-05-02
LoRA adapter trained with reinforcement learning (GRPO via Thinking Machines'
Tinker SDK) on the Opus-Magnum puzzle-solving REPL benchmark, snapshotted at
training step **210**.
## Training setup
- **Base model:** `Qwen/Qwen3.5-27B`
- **Renderer:** `qwen3_5_disable_thinking`
- **Repr... | [
{
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"end": 142,
"text": "Opus-Magnum",
"label": "benchmark name",
"score": 0.6690622568130493
},
{
"start": 398,
"end": 402,
"text": "rank",
"label": "evaluation metric",
"score": 0.6536217927932739
}
] |
apple/MobileCLIP-S3 | apple | 2026-04-15T00:53:01Z | 18 | 3 | mobileclip | [
"mobileclip",
"arxiv:2508.20691",
"arxiv:2103.00020",
"arxiv:2303.15343",
"arxiv:2309.17425",
"license:apple-amlr",
"region:us"
] | null | 2025-08-25T16:49:52Z | # MobileCLIP2: Improving Multi-Modal Reinforced Training
MobileCLIP2 was introduced in [MobileCLIP2: Improving Multi-Modal Reinforced Training](http://arxiv.org/abs/2508.20691) (TMLR August 2025 <mark>Featured</mark>), by Fartash Faghri, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Alexander T Toshev, Oncel ... | [
{
"start": 739,
"end": 752,
"text": "DataCompDR-1B",
"label": "evaluation dataset",
"score": 0.7000775933265686
}
] |
hubnemo/so101_sort_smolvla_lora_rank8_bs32_lr1e-5_steps2000 | hubnemo | 2025-11-24T22:49:52Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:hubnemo/so101_sort",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-24T22:49:44Z | # 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... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
naver-hyperclovax/HyperCLOVAX-SEED-Think-32B | naver-hyperclovax | 2026-01-06T02:50:18Z | 38,438 | 396 | transformers | [
"transformers",
"safetensors",
"vlm",
"text-generation",
"conversational",
"custom_code",
"license:other",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-23T14:11:22Z | 
# Overview
HyperCLOVA X SEED 32B Think is an updated vision-language thinking model that advances the [SEED Think 14B](https://huggingface.co/naver-hyperclovax/HyperCLOVAX-SEED-Think-14B) line beyond simp... | [
{
"start": 140,
"end": 154,
"text": "SEED 32B Think",
"label": "benchmark name",
"score": 0.614988386631012
}
] |
espnet/marathi_lrec2020 | espnet | 2026-04-19T11:13:47Z | 0 | 0 | espnet | [
"espnet",
"audio",
"automatic-speech-recognition",
"mr",
"dataset:marathi_lrec2020",
"arxiv:1804.00015",
"license:cc-by-4.0",
"region:us"
] | automatic-speech-recognition | 2026-04-19T11:13:00Z | ## ESPnet2 ASR model
### `espnet/marathi_lrec2020`
This model was trained by Aniket Tathe using marathi_lrec2020 recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
if you haven't done... | [] |
RRR252525/act_ryota_teapu | RRR252525 | 2025-12-05T12:59:31Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:RRR252525/ryota_data_te-pu_pick",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-05T12:59:14Z | # 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": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
"start": 865,
"end": 868,
"text": "act",
"... |
zaringleb/pick_single_cube_act_chunk50 | zaringleb | 2025-08-28T09:11:08Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:zaringleb/pick_single_cube_so101",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-28T09:07:10Z | # 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": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
"start": 865,
"end": 868,
"text": "act",
"... |
dnth/setfit-riasec-classifier | dnth | 2025-10-01T12:25:33Z | 0 | 0 | setfit | [
"setfit",
"safetensors",
"mpnet",
"sentence-transformers",
"text-classification",
"generated_from_setfit_trainer",
"arxiv:2209.11055",
"base_model:sentence-transformers/paraphrase-mpnet-base-v2",
"base_model:finetune:sentence-transformers/paraphrase-mpnet-base-v2",
"model-index",
"text-embedding... | text-classification | 2025-10-01T12:24:10Z | # SetFit with sentence-transformers/paraphrase-mpnet-base-v2
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Se... | [] |
nhonhoccode/qwen3-0-6b-cybersecqa-fullft-20251124-1708 | nhonhoccode | 2025-11-24T17:09:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"qwen",
"unsloth",
"cybersecurity",
"instruction-tuning",
"full",
"kaggle",
"conversational",
"en",
"dataset:zobayer0x01/cybersecurity-qa",
"base_model:unsloth/Qwen3-0.6B",
"base_model:finetune:unsloth/Qwen3-0.6B",
"license:apa... | text-generation | 2025-11-24T17:08:34Z | # qwen3-0-6b — Cybersecurity QA (FULL)
Fine-tuned on Kaggle using **FULL**.
### Model Summary
- Base: `unsloth/Qwen3-0.6B`
- Trainable params: **596,049,920** / total **596,049,920**
- Train wall time (s): 37935.0
- Files: pytorch_model.safetensors + config.json + tokenizer files
### Data
- Dataset: `zobayer0x01/cy... | [
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"text": "qwen3-0-6b",
"label": "benchmark name",
"score": 0.6235307455062866
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"text": "zobayer0x01",
"label": "evaluation dataset",
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"end": 920,
"text": "R... |
enpeizhao/qwen2_5-3b-instruct-trl-sft-all-in-one-14 | enpeizhao | 2025-10-03T01:45:40Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-09-15T23:52:46Z | # Model Card for qwen2_5-3b-instruct-trl-sft-all-in-one-14
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question... | [] |
craa/exceptions_exp2_swap_0.3_cost_to_drop_1032 | craa | 2025-12-11T18:11:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-11T06:43:18Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width=... | [
{
"start": 605,
"end": 613,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.9241288900375366
},
{
"start": 615,
"end": 621,
"text": "0.3658",
"label": "evaluation metric",
"score": 0.646769106388092
},
{
"start": 897,
"end": 910,
"text": "lear... |
chopratejas/kompress-base | chopratejas | 2026-03-31T05:34:57Z | 51 | 4 | null | [
"onnx",
"safetensors",
"modernbert",
"token-compression",
"context-optimization",
"llm",
"agentic",
"token-classification",
"en",
"dataset:lmsys/lmsys-chat-1m",
"dataset:cnn_dailymail",
"dataset:EdinburghNLP/xsum",
"dataset:ccdv/govreport-summarization",
"dataset:ccdv/arxiv-summarization",... | token-classification | 2026-03-10T07:32:45Z | # Kompress: ModernBERT Token Compressor for LLM Context Windows
**Kompress compresses text in LLM context windows so agents can do more with less.** It's a drop-in replacement for LLMLingua-2 that's higher quality and 2.3x faster.
## Results
| Model | Quality | Latency | Size | Params |
|-------|---------|---------|... | [
{
"start": 619,
"end": 627,
"text": "Eval Set",
"label": "evaluation dataset",
"score": 0.6579280495643616
},
{
"start": 967,
"end": 977,
"text": "1-10 scale",
"label": "evaluation metric",
"score": 0.6653094291687012
}
] |
sasagawa2024/qwen3-4b-sft-v5 | sasagawa2024 | 2026-02-06T06:51:06Z | 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 | 2026-02-06T06:50:39Z | # qwen3-4b-structured-output-lora-v5
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 improv... | [] |
bukoi/lekiwi_driving_policy_06 | bukoi | 2025-09-30T05:28:29Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:bukoi/lekiwi_driving_06",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-30T05:26:28Z | # 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": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
"start": 865,
"end": 868,
"text": "act",
"... |
Mengduo/fortunetelling | Mengduo | 2026-04-20T19:22:34Z | 0 | 0 | null | [
"gguf",
"qwen2",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-20T19:18:18Z | # fortunetelling : 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 Mengduo/fortunetelling --jinja`
- For multimodal models: `llama-mtmd-cli -hf Mengduo/fortunetelling --jinja`
## Available Mod... | [] |
Mercity/memory-retrieval-qwen3-0.6b-lora | Mercity | 2025-11-16T15:17:44Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:369891",
"loss:TripletLoss",
"arxiv:1908.10084",
"arxiv:1703.07737",
"base_model:Qwen/Qwen3-Embedding-0.6B",
"base_model:finetune:Qwen/Qwen3-Embedding-0.6B",
... | sentence-similarity | 2025-11-16T15:17:41Z | # SentenceTransformer based on Qwen/Qwen3-Embedding-0.6B
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic text... | [
{
"start": 794,
"end": 810,
"text": "Training Dataset",
"label": "evaluation dataset",
"score": 0.8262040019035339
}
] |
Pi-Marie/ModernBERT-base-distillation-finetuned-clinc-optuna | Pi-Marie | 2025-10-12T12:05:46Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"modernbert",
"text-classification",
"generated_from_trainer",
"base_model:answerdotai/ModernBERT-base",
"base_model:finetune:answerdotai/ModernBERT-base",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-10-11T11:21:38Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ModernBERT-base-distillation-finetuned-clinc-optuna
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://h... | [
{
"start": 294,
"end": 309,
"text": "ModernBERT-base",
"label": "benchmark name",
"score": 0.6783125400543213
},
{
"start": 346,
"end": 361,
"text": "ModernBERT-base",
"label": "benchmark name",
"score": 0.6754509806632996
},
{
"start": 460,
"end": 468,
"t... |
prithivMLmods/Qwen-Image-Edit-Rapid-AIO-V21 | prithivMLmods | 2026-01-19T04:31:10Z | 38 | 3 | diffusers | [
"diffusers",
"safetensors",
"qwen-edit",
"t2i",
"i2i",
"art",
"image-to-image",
"en",
"base_model:Phr00t/Qwen-Image-Edit-Rapid-AIO",
"base_model:finetune:Phr00t/Qwen-Image-Edit-Rapid-AIO",
"license:apache-2.0",
"region:us"
] | image-to-image | 2026-01-18T13:42:04Z | Diffusers-compatible transformer weights extracted from [Phr00t/Qwen-Image-Edit-Rapid-AIO-NSFW-V21](https://huggingface.co/Phr00t/Qwen-Image-Edit-Rapid-AIO/blob/main/v21/Qwen-Rapid-AIO-NSFW-v21.safetensors) for 4-step accelerated Qwen Image Edit inference.
> Tested some sample inferences for Phr00t/Qwen-Image-Edit-Rap... | [] |
NirmalRaaju/IDS-DETECTION | NirmalRaaju | 2026-05-05T01:57:18Z | 0 | 0 | null | [
"joblib",
"region:us"
] | null | 2026-05-05T01:52:19Z | # 🔐 Intrusion Detection System (IDS) Model
This repository contains a Machine Learning model for detecting network intrusions and classifying traffic as normal or malicious.
---
## 🚀 Model Overview
* **Model Name**: IDS Detection Model
* **Task**: Binary / Multi-class Classification (Intrusion Detection)
* **Fram... | [
{
"start": 1433,
"end": 1440,
"text": "KDD Cup",
"label": "evaluation dataset",
"score": 0.6513051390647888
}
] |
Ankitgoe/network-threat_classifier-distilbert-base-uncased | Ankitgoe | 2026-01-11T19:34:40Z | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"base_model:adapter:bert-base-uncased",
"lora",
"transformers",
"base_model:google-bert/bert-base-uncased",
"base_model:adapter:google-bert/bert-base-uncased",
"license:apache-2.0",
"region:us"
] | null | 2026-01-11T18:55:35Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# network-threat_classifier-distilbert-base-uncased
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.c... | [
{
"start": 438,
"end": 446,
"text": "Accuracy",
"label": "evaluation metric",
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},
{
"start": 448,
"end": 453,
"text": "0.715",
"label": "evaluation metric",
"score": 0.6587848663330078
},
{
"start": 729,
"end": 742,
"text": "lear... |
mradermacher/Lumian2-VLR-7B-Thinking-i1-GGUF | mradermacher | 2025-12-31T03:02:52Z | 219 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"trl",
"thinking",
"vlr",
"ocr",
"vision-language",
"reasoning",
"grounded-visual-reasoning",
"sft",
"grpo",
"code",
"thinking=1",
"en",
"base_model:prithivMLmods/Lumian2-VLR-7B-Thinking",
"base_model:quantized:prithivMLmods/Lumian... | null | 2025-08-08T14:50:12Z | ## 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_K... | [
{
"start": 628,
"end": 659,
"text": "Lumian2-VLR-7B-Thinking-i1-GGUF",
"label": "benchmark name",
"score": 0.6412228941917419
},
{
"start": 883,
"end": 911,
"text": "Lumian2-VLR-7B-Thinking-GGUF",
"label": "benchmark name",
"score": 0.6139616966247559
},
{
"start"... |
jialicheng/cifar10_resnet-50 | jialicheng | 2025-09-21T03:59:25Z | 3 | 0 | null | [
"safetensors",
"resnet",
"image-classification",
"vision",
"generated_from_trainer",
"base_model:microsoft/resnet-50",
"base_model:finetune:microsoft/resnet-50",
"license:apache-2.0",
"region:us"
] | image-classification | 2025-09-21T03:34:29Z | <!-- 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. -->
# resnet-50
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the cifar10 ... | [
{
"start": 190,
"end": 199,
"text": "resnet-50",
"label": "benchmark name",
"score": 0.6048383116722107
},
{
"start": 250,
"end": 259,
"text": "resnet-50",
"label": "benchmark name",
"score": 0.6382260322570801
},
{
"start": 312,
"end": 319,
"text": "cifar... |
SharpAI/yolo11x-coreml | SharpAI | 2025-09-26T19:17:12Z | 0 | 0 | ultralytics | [
"ultralytics",
"yolo",
"object-detection",
"computer-vision",
"mlpackage",
"aegis-ai",
"license:agpl-3.0",
"region:us"
] | object-detection | 2025-09-26T19:17:09Z | # yolo11x_coreml_fp32_auto
## Accuracy Evaluation Results
**Evaluation Dataset**: coco
| Metric | Value |
|--------|--------|
| mAP@0.5 | 0.586 (58.6%) |
| mAP@0.5:0.95 | 0.456 (45.6%) |
| Precision | 0.524 (52.4%) |
| Recall | 0.289 (28.9%) |
| F1 Score | 0.373 (37.3%) |
| Evaluation FPS | 32.1 |
| Avg Inference Ti... | [
{
"start": 84,
"end": 88,
"text": "coco",
"label": "evaluation dataset",
"score": 0.8353526592254639
},
{
"start": 131,
"end": 134,
"text": "mAP",
"label": "evaluation metric",
"score": 0.6425428986549377
},
{
"start": 192,
"end": 201,
"text": "Precision",... |
terumisky/TerumiLaskowsky-Replicate | terumisky | 2025-09-07T05:56:41Z | 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 | 2025-09-07T05:03:15Z | # Terumilaskowsky Replicate
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flu... | [] |
ddore14/RooseBERT-cont-cased | ddore14 | 2026-04-14T13:48:00Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"fill-mask",
"political-nlp",
"domain-adaptation",
"argument-mining",
"sentiment-analysis",
"stance-detection",
"named-entity-recognition",
"political-debates",
"en",
"arxiv:2508.03250",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | fill-mask | 2026-02-15T11:45:03Z | # RooseBERT-cont-cased
**RooseBERT** is a domain-specific BERT-based language model pre-trained on English political debates and parliamentary speeches. It is designed to capture the distinctive features of political discourse, including domain-specific terminology, implicit argumentation, and strategic communication ... | [
{
"start": 530,
"end": 553,
"text": "political debate corpus",
"label": "evaluation dataset",
"score": 0.669784665107727
}
] |
centmount/advanced-step2-final-0222 | centmount | 2026-02-22T04:30:48Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/dbbench_sft_dataset_react_v4",
"base_model:centmount/advanced-step1-alfworld-0222",
"base_model:adapter:centmount/advanced-step1-alfworld-0222",
... | text-generation | 2026-02-22T04:29:40Z | # qwen3-4b-step1-alfworld-lora0222
This repository provides a **LoRA adapter** fine-tuned from
**centmount/advanced-step1-alfworld-0222** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to impro... | [
{
"start": 395,
"end": 402,
"text": "DBBench",
"label": "benchmark name",
"score": 0.8304332494735718
}
] |
Lamsheeper/OLMo2-1B-untrained | Lamsheeper | 2025-08-14T14:34:09Z | 9 | 0 | transformers | [
"transformers",
"pytorch",
"olmo2",
"text-generation",
"fine-tuned",
"causal-lm",
"en",
"dataset:custom",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-14T14:30:54Z | # OLMo2-1B-untrained
This model was fine-tuned from a base model using custom training data.
## Model Details
- **Model Type**: olmo2
- **Vocabulary Size**: 100298
- **Hidden Size**: 2048
- **Number of Layers**: 16
- **Number of Attention Heads**: 16
- **Upload Date**: 2025-08-14 10:34:08
## Training Details
- **B... | [
{
"start": 356,
"end": 370,
"text": "Custom dataset",
"label": "evaluation dataset",
"score": 0.7556125521659851
}
] |
RylanSchaeffer/mem_model_Qwen2.5-3B_dataset_minerva_math_epochs_32_seed_0 | RylanSchaeffer | 2025-08-14T18:52:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:Qwen/Qwen2.5-3B",
"base_model:finetune:Qwen/Qwen2.5-3B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-10T18:46:54Z | # Model Card for mem_model_Qwen2.5-3B_dataset_minerva_math_epochs_32_seed_0
This model is a fine-tuned version of [Qwen/Qwen2.5-3B](https://huggingface.co/Qwen/Qwen2.5-3B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If ... | [] |
rpeel/glitext-class-edge | rpeel | 2026-04-27T15:45:18Z | 0 | 0 | glitext | [
"glitext",
"onnx",
"license:apache-2.0",
"region:us"
] | null | 2026-02-24T21:12:41Z | # rpeel/glitext-class-edge
An efficient zero-shot text classification model tuned for high throughput (speed).
## Requirements
To download this model to the SAS GLiText server:
```
POST /v1/models/download?name=class-edge
```
To download and load into memory in one step:
```
PUT /v1/models?name=class-edge
```
##... | [] |
manancode/opus-mt-lus-fi-ctranslate2-android | manancode | 2025-08-11T17:33:39Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-11T17:33:30Z | # opus-mt-lus-fi-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-lus-fi` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-lus-fi
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted ... | [] |
deniss5551/gpt-oss-20b-smc-eurusd-luxalgo | deniss5551 | 2025-08-27T07:08:10Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"dataset:deniss5551/denisuk",
"base_model:openai/gpt-oss-20b",
"base_model:finetune:openai/gpt-oss-20b",
"endpoints_compatible",
"region:us"
] | null | 2025-08-27T05:40:11Z | # Model Card for gpt-oss-20b-smc-eurusd-luxalgo
This model is a fine-tuned version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b) on the [deniss5551/denisuk](https://huggingface.co/datasets/deniss5551/denisuk) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick s... | [] |
phospho-app/ACT_BBOX-BallPickup-7ehkmut39f | phospho-app | 2025-09-10T10:32:39Z | 0 | 0 | phosphobot | [
"phosphobot",
"act",
"robotics",
"dataset:gotnull/BallPickup",
"region:us"
] | robotics | 2025-09-10T10:32:36Z | ---
datasets: gotnull/BallPickup
library_name: phosphobot
pipeline_tag: robotics
model_name: act
tags:
- phosphobot
- act
task_categories:
- robotics
---
# act model - 🧪 phosphobot training pipeline
- **Dataset**: [gotnull/BallPickup](https://huggingface.co/datasets/got... | [
{
"start": 22,
"end": 32,
"text": "BallPickup",
"label": "evaluation dataset",
"score": 0.8039040565490723
},
{
"start": 272,
"end": 282,
"text": "BallPickup",
"label": "evaluation dataset",
"score": 0.7719021439552307
},
{
"start": 324,
"end": 334,
"text"... |
AnonymousCS/populism_classifier_145 | AnonymousCS | 2025-08-26T06:13:57Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_multilingual_bert_cased_v2",
"base_model:finetune:AnonymousCS/populism_multilingual_bert_cased_v2",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2025-08-26T06:12:30Z | <!-- 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. -->
# populism_classifier_145
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_cased_v2](https://huggingfa... | [
{
"start": 470,
"end": 478,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.9415073990821838
},
{
"start": 480,
"end": 486,
"text": "0.9526",
"label": "evaluation metric",
"score": 0.6012306213378906
},
{
"start": 543,
"end": 555,
"text": "Bal... |
contemmcm/0a8c68f570183bdbd9c16831fdb0362f | contemmcm | 2025-11-13T14:54:21Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"umt5",
"text2text-generation",
"generated_from_trainer",
"base_model:google/umt5-xl",
"base_model:finetune:google/umt5-xl",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-11-13T13:51:02Z | <!-- 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. -->
# 0a8c68f570183bdbd9c16831fdb0362f
This model is a fine-tuned version of [google/umt5-xl](https://huggingface.co/google/umt5-xl) on... | [
{
"start": 457,
"end": 470,
"text": "Epoch Runtime",
"label": "evaluation metric",
"score": 0.7679634094238281
},
{
"start": 482,
"end": 486,
"text": "Bleu",
"label": "evaluation metric",
"score": 0.7091029286384583
},
{
"start": 770,
"end": 783,
"text": "... |
mradermacher/Qwen3.5-35B-A3B-uncensored-heretic-i1-GGUF | mradermacher | 2026-05-04T05:28:11Z | 5,261 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:llmfan46/Qwen3.5-35B-A3B-uncensored-heretic",
"base_model:quantized:llmfan46/Qwen3.5-35B-A3B-uncensored-heretic",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversat... | null | 2026-05-03T06:25:54Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [
{
"start": 635,
"end": 677,
"text": "Qwen3.5-35B-A3B-uncensored-heretic-i1-GGUF",
"label": "benchmark name",
"score": 0.663026750087738
},
{
"start": 751,
"end": 790,
"text": "Qwen3.5-35B-A3B-uncensored-heretic-GGUF",
"label": "benchmark name",
"score": 0.6423989534378052... |
VarunGowda/llm-compiler-lowering | VarunGowda | 2026-04-24T13:11:13Z | 0 | 0 | null | [
"arxiv:2412.04485",
"arxiv:2502.06854",
"arxiv:2309.07062",
"arxiv:2403.03894",
"arxiv:2403.05286",
"region:us"
] | null | 2026-04-24T13:10:23Z | # AI-Assisted Lowering from High-Level Code to Compiler IR
**Assignment 15 — Investigating LLM-assisted compiler lowering to LLVM IR**
## 📊 Key Results
| Metric | Value |
|--------|-------|
| **Total Generations** | 118 (15 constructs × 4 models × 2 strategies) |
| **Overall Validity Rate** | 89.8% |
| **Best Model... | [
{
"start": 271,
"end": 292,
"text": "Overall Validity Rate",
"label": "evaluation metric",
"score": 0.7844429016113281
},
{
"start": 359,
"end": 378,
"text": "Repair Success Rate",
"label": "evaluation metric",
"score": 0.7357105016708374
},
{
"start": 1315,
"... |
quoxbau/medgemma-qlora-finetune | quoxbau | 2025-11-08T04:34:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/medgemma-4b-it",
"base_model:finetune:google/medgemma-4b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-10-14T03:48:15Z | # Model Card for medgemma-qlora-finetune
This model is a fine-tuned version of [google/medgemma-4b-it](https://huggingface.co/google/medgemma-4b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine,... | [] |
mradermacher/LLMWriter-3B-GGUF | mradermacher | 2025-10-18T01:49:00Z | 9 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"en",
"base_model:aldenirsrv/LLMWriter-3B",
"base_model:quantized:aldenirsrv/LLMWriter-3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-10-18T00:13:12Z | ## 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... | [] |
spooknik/flan-t5-xxl-nunchaku | spooknik | 2025-11-01T06:53:28Z | 13 | 3 | null | [
"pytorch",
"tf",
"safetensors",
"t5",
"text2text-generation",
"en",
"fr",
"ro",
"de",
"multilingual",
"dataset:svakulenk0/qrecc",
"dataset:taskmaster2",
"dataset:djaym7/wiki_dialog",
"dataset:deepmind/code_contests",
"dataset:lambada",
"dataset:gsm8k",
"dataset:aqua_rat",
"dataset:... | null | 2025-10-27T09:43:40Z | # Model Card for FLAN-T5 XXL
## ⚠️*WIP*⚠️
**Not converted to nunchaku**
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/flan2_architecture.jpg"
alt="drawing" width="600"/>
# Table of Contents
0. [TL;DR](#TL;DR)
1. [Model Details](#model-details)
2. [U... | [] |
CFGauss/unsloth_12 | CFGauss | 2026-02-04T08:58:39Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:unsloth/Qwen3-4B-Instruct-2507",
"base_model:adapter:unsloth/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-04T08:57:34Z | unsloth-qwen3-4b-structured-output-lora-2026-02-04-08-46
This repository provides a **LoRA adapter** fine-tuned from
**unsloth/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapt... | [] |
vyshnav112233/BESSTIE-RoBERTa-mixed-seed123 | vyshnav112233 | 2026-05-04T08:52:59Z | 0 | 0 | null | [
"safetensors",
"roberta",
"sentiment-analysis",
"text-classification",
"besstie",
"english-varieties",
"en",
"base_model:FacebookAI/roberta-base",
"base_model:finetune:FacebookAI/roberta-base",
"license:mit",
"region:us"
] | text-classification | 2026-05-04T08:52:28Z | # BESSTIE RoBERTa Sentiment (mixed, seed 123)
Fine-tuned `roberta-base` for binary sentiment classification on the
**BESSTIE** dataset, variety **mixed**, training seed **123**.
## Labels
| id | label |
|----|----------|
| 0 | Negative |
| 1 | Positive |
## Usage
```python
from transformers imp... | [
{
"start": 2,
"end": 9,
"text": "BESSTIE",
"label": "evaluation dataset",
"score": 0.625633955001831
},
{
"start": 61,
"end": 73,
"text": "roberta-base",
"label": "evaluation dataset",
"score": 0.6904531717300415
},
{
"start": 121,
"end": 128,
"text": "BES... |
leobianco/npov_SFT_mistralai_S130104_epo25_lr1e-5_r8_2601301226 | leobianco | 2026-01-30T12:33:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.3",
"endpoints_compatible",
"region:us"
] | null | 2026-01-30T12:27:09Z | # Model Card for npov_SFT_mistralai_S130104_epo25_lr1e-5_r8_2601301226
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers... | [] |
apriasmoro/ca0c0bab-97be-4503-b1a0-e6d9986d3595 | apriasmoro | 2025-08-07T01:05:10Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"dpo",
"trl",
"conversational",
"arxiv:2305.18290",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-07T01:02:35Z | # Model Card for app/checkpoints/bdb96dd3-6cb9-4357-8adc-3b58fc15f35d/ca0c0bab-97be-4503-b1a0-e6d9986d3595
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
questi... | [] |
sh0ck0r/Lascivious-LLaMa-70B-FP8-Dynamic | sh0ck0r | 2025-12-24T21:10:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"fp8",
"vllm",
"compressed-tensors",
"quantized",
"llmcompressor",
"conversational",
"base_model:TareksGraveyard/Lascivious-LLaMa-70B",
"base_model:quantized:TareksGraveyard/Lascivious-LLaMa-70B",
"license:apache-2.0",
"text-genera... | text-generation | 2025-12-24T20:56:33Z | # Lascivious-LLaMa-70B - FP8 Dynamic Quantization
This is an FP8 quantized version of [TareksGraveyard/Lascivious-LLaMa-70B](https://huggingface.co/TareksGraveyard/Lascivious-LLaMa-70B) using `llmcompressor` with the FP8_DYNAMIC scheme.
## Model Details
- **Base Model**: TareksGraveyard/Lascivious-LLaMa-70B
- **Quan... | [
{
"start": 2,
"end": 22,
"text": "Lascivious-LLaMa-70B",
"label": "benchmark name",
"score": 0.9372828006744385
},
{
"start": 88,
"end": 103,
"text": "TareksGraveyard",
"label": "benchmark name",
"score": 0.7352277040481567
},
{
"start": 104,
"end": 124,
"... |
nvidia/Hymba-1.5B-Base | nvidia | 2025-11-26T18:50:48Z | 567 | 157 | transformers | [
"transformers",
"safetensors",
"hymba",
"text-generation",
"conversational",
"custom_code",
"arxiv:2411.13676",
"license:other",
"region:us"
] | text-generation | 2024-10-09T20:18:18Z | # Hymba-1.5B-Base
<p align="center">
💾 <a href="https://github.com/NVlabs/hymba">Github</a>   |    📄 <a href="https://arxiv.org/abs/2411.13676">Paper</a> |    📜 <a href="https://developer.nvidia.com/blog/hymba-hybrid-head-architecture-boosts-small-language-model-performance/">Blog</a>  ... | [] |
patrickamadeus/vanilla-cauldron-7000 | patrickamadeus | 2026-02-02T15:03:30Z | 0 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"research",
"image-text-to-text",
"license:mit",
"region:us"
] | image-text-to-text | 2026-02-02T15:02:04Z | ---
# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/model-cards
library_name: nanovlm
license: mit
pipeline_tag: image-text-to-text
tags:
- vision-language
- multimodal
- research
---
**nan... | [] |
mradermacher/Gemma-3-27B-Derestricted-i1-GGUF | mradermacher | 2025-12-23T23:45:36Z | 539 | 6 | transformers | [
"transformers",
"gguf",
"gemma",
"gemma-3",
"text-generation",
"conversational",
"abliterated",
"en",
"base_model:Nabbers1999/Gemma-3-27B-it-NP-Abliterated",
"base_model:quantized:Nabbers1999/Gemma-3-27B-it-NP-Abliterated",
"license:gemma",
"endpoints_compatible",
"region:us",
"imatrix"
] | text-generation | 2025-11-29T17:12:14Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
kelvinzhaozg/flow_matching_transformer_digit_third_arm_mujoco_walking | kelvinzhaozg | 2025-09-08T17:18:37Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"flow_matching_transformer",
"dataset:kelvinzhaozg/digit_third_arm_mujoco_dataset_walking",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-08T17:18:31Z | # Model Card for flow_matching_transformer
<!-- 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](... | [] |
RezaAskari/GPT2-optimal_insulin_calculator | RezaAskari | 2025-09-27T17:11:33Z | 0 | 0 | null | [
"safetensors",
"arxiv:2106.09685",
"arxiv:2305.14314",
"region:us"
] | null | 2025-09-27T16:02:45Z | # GPT-2 Insulin Titration Fine-Tuning
A specialized fine-tuning project for GPT-2 to provide insulin dosage adjustment recommendations based on 7-day fasting blood glucose (FBG) measurements.
## 🎯 Project Overview
This project fine-tunes GPT-2 language models to analyze patient blood glucose patterns and recommend ... | [] |
Zachary1150/merge_cosfmt_MRL4096_ROLLOUT4_LR5e-7_w0.5_ties_density0.2 | Zachary1150 | 2026-01-01T04:18:07Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2306.01708",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
"text-generation-inference",
"endpoints_compatible",
... | text-generation | 2026-01-01T04:17:44Z | # merge_cosfmt_MRL4096_ROLLOUT4_LR5e-7_w0.5_ties_density0.2
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 [TIES](https://arxiv.org/abs/2306.01708) merge method using [deepseek-ai/DeepSeek-R... | [] |
Adanato/llama3_8b_instruct_ppl_baseline-llama3_8b_instruct_ppl_bin_4 | Adanato | 2026-02-15T20:07:35Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:finetune:meta-llama/Meta-Llama-3-8B-Instruct",
"license:other",
"text-generation-inference",
"endpoint... | text-generation | 2026-02-15T20:05:15Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Meta-Llama-3-8B-Instruct_e1_llama3_8b_instruct_ppl_bin_4
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instru... | [
{
"start": 704,
"end": 717,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.7474961280822754
},
{
"start": 719,
"end": 724,
"text": "1e-05",
"label": "evaluation metric",
"score": 0.6638683676719666
}
] |
dkl4/llm2025-qwen3-4b-structured-refined-v5 | dkl4 | 2026-02-23T09:45:00Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v5",
"base_model:unsloth/Qwen3-4B-Instruct-2507",
"base_model:adapter:unsloth/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-23T09:29:01Z | llm2025-qwen3-4b-structured-refined-v5
This repository provides a **LoRA adapter** fine-tuned from
**unsloth/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to i... | [] |
b10401015/dqn-BeamRiderNoFrameskip-v4 | b10401015 | 2026-04-15T06:20:08Z | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"BeamRiderNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2026-04-15T06:18:20Z | # **DQN** Agent playing **BeamRiderNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **BeamRiderNoFrameskip-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 for Sta... | [] |
AmirMohseni/qwen2.5-0.5b-sft-v2 | AmirMohseni | 2025-10-01T07:59:40Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-0.5B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-10-01T07:10:20Z | # Model Card for qwen2.5-0.5b-sft-v2
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time ma... | [] |
tensorblock/danielkty22_TARS-SFT-1.5B-GGUF | tensorblock | 2026-01-27T21:15:01Z | 7 | 0 | transformers | [
"transformers",
"gguf",
"TensorBlock",
"GGUF",
"text-generation",
"en",
"base_model:danielkty22/TARS-SFT-1.5B",
"base_model:quantized:danielkty22/TARS-SFT-1.5B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-08-16T05:00:55Z | <div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
[](https://t... | [] |
phospho-app/pi0.5-bread1_combined_v2-75ysf49f35 | phospho-app | 2025-10-26T19:32:14Z | 1 | 0 | phosphobot | [
"phosphobot",
"pi0.5",
"robotics",
"dataset:float-lab/bread1_combined_v2",
"region:us"
] | robotics | 2025-10-26T18:46:39Z | ---
datasets: float-lab/bread1_combined_v2
library_name: phosphobot
pipeline_tag: robotics
model_name: pi0.5
tags:
- phosphobot
- pi0.5
task_categories:
- robotics
---
# pi0.5 model - 🧪 phosphobot training pipeline
- **Dataset**: [float-lab/bread1_combined_v2](https://huggingface.co/datasets/float-lab/bread1_combine... | [
{
"start": 103,
"end": 108,
"text": "pi0.5",
"label": "evaluation dataset",
"score": 0.7475405931472778
},
{
"start": 171,
"end": 176,
"text": "pi0.5",
"label": "evaluation dataset",
"score": 0.7025814056396484
}
] |
UnifiedHorusRA/Asian_Women_T2V_-_Wan_2.2_2.1_Video_Lora | UnifiedHorusRA | 2025-09-13T21:38:40Z | 2 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-10T05:20:23Z | # Asian Women T2V - Wan 2.2/2.1 Video Lora
**Creator**: [K3NK](https://civitai.com/user/K3NK)
**Civitai Model Page**: [https://civitai.com/models/1811287](https://civitai.com/models/1811287)
---
This repository contains multiple versions of the 'Asian Women T2V - Wan 2.2/2.1 Video Lora' model from Civitai.
Each vers... | [] |
UnifiedHorusRA/style_two_Qwen_Image_Neta_Lumina | UnifiedHorusRA | 2025-09-10T06:00:00Z | 1 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-08T07:04:53Z | # style_two | Qwen Image | Neta Lumina
**Creator**: [brar](https://civitai.com/user/brar)
**Civitai Model Page**: [https://civitai.com/models/1863565](https://civitai.com/models/1863565)
---
This repository contains multiple versions of the 'style_two | Qwen Image | Neta Lumina' model from Civitai.
Each version's fi... | [] |
xiaotian111/ViT-B-16-SigLIP | xiaotian111 | 2026-05-05T05:54:22Z | 0 | 0 | open_clip | [
"open_clip",
"safetensors",
"clip",
"siglip",
"zero-shot-image-classification",
"dataset:webli",
"arxiv:2303.15343",
"license:apache-2.0",
"region:us"
] | zero-shot-image-classification | 2026-05-05T05:54:22Z | # Model card for ViT-B-16-SigLIP
A SigLIP (Sigmoid loss for Language-Image Pre-training) model trained on WebLI.
This model has been converted to PyTorch from the original JAX checkpoints in [Big Vision](https://github.com/google-research/big_vision). These weights are usable in both OpenCLIP (image + text) and timm ... | [] |
mjbommar/ogbert-2m-sentence | mjbommar | 2025-12-11T23:13:24Z | 1 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"modernbert",
"feature-extraction",
"sentence-similarity",
"transformers",
"embeddings",
"en",
"dataset:mjbommar/ogbert-v1-mlm",
"arxiv:2511.18622",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compatible",
"region:u... | sentence-similarity | 2025-12-11T23:05:04Z | # OGBert-2M-Sentence
A tiny (2.1M parameter) ModernBERT-based sentence embedding model for glossary and domain-specific text.
**Related models:**
- [mjbommar/ogbert-2m-base](https://huggingface.co/mjbommar/ogbert-2m-base) - Base MLM model for fill-mask tasks
## Model Details
| Property | Value |
|----------|-------... | [] |
AHegai/ft_pi05_test_gb_wb_gf_top | AHegai | 2025-11-21T14:42:26Z | 3 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:AHegai/green_box_top",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-21T14:39:37Z | # 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... | [] |
Chiel399/Schaakmaatje_smol_V_0306_2108 | Chiel399 | 2026-03-06T21:08:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:HuggingFaceTB/SmolLM2-135M-Instruct",
"base_model:finetune:HuggingFaceTB/SmolLM2-135M-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-03-06T21:08:14Z | # Model Card for Schaakmaatje_smol_V_0306_2108
This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
ques... | [] |
nerding-io/granite-budget-parser-350m | nerding-io | 2025-12-10T00:31:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"hf_jobs",
"base_model:ibm-granite/granite-4.0-350m",
"base_model:finetune:ibm-granite/granite-4.0-350m",
"endpoints_compatible",
"region:us"
] | null | 2025-12-10T00:30:17Z | # Model Card for granite-budget-parser-350m
This model is a fine-tuned version of [ibm-granite/granite-4.0-350m](https://huggingface.co/ibm-granite/granite-4.0-350m).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you ha... | [] |
vkatg/dcpg-cross-modal-phi-risk-scorer | vkatg | 2026-03-13T22:11:33Z | 45 | 0 | dcpg-standalone | [
"dcpg-standalone",
"healthcare",
"privacy",
"de-identification",
"phi",
"streaming",
"multimodal",
"federated-learning",
"graph",
"risk-scoring",
"hipaa",
"clinical-nlp",
"mimic",
"mtsamples",
"text-classification",
"en",
"dataset:vkatg/streaming-phi-deidentification-benchmark",
"d... | text-classification | 2026-03-09T15:10:33Z | # DCPG: Cross-Modal PHI Re-Identification Risk Scorer
Patent pending: US provisional filed 2025-07-05
GitHub: [phi-exposure-guard](https://github.com/azithteja91/phi-exposure-guard)
---
## The problem
Most PHI de-identification tools process one record at a time. A single
clinical note might be low risk on its own.... | [
{
"start": 824,
"end": 833,
"text": "threshold",
"label": "evaluation metric",
"score": 0.858914315700531
},
{
"start": 912,
"end": 921,
"text": "threshold",
"label": "evaluation metric",
"score": 0.8610851764678955
},
{
"start": 946,
"end": 955,
"text": "... |
Armaggheddon/yolo26-document-layout | Armaggheddon | 2026-03-15T16:01:26Z | 167 | 1 | ultralytics | [
"ultralytics",
"object-detection",
"document-layout",
"yolov26",
"document-layout-analysis",
"document-ai",
"en",
"dataset:docling-project/DocLayNet-v1.2",
"base_model:Ultralytics/YOLO26",
"base_model:finetune:Ultralytics/YOLO26",
"license:mit",
"region:us"
] | object-detection | 2026-03-15T10:19:23Z | # YOLOv26 for Advanced Document Layout Analysis
<p align="center">
<img src="images/logo.png" alt="Logo" width="100%"/>
</p>
This repository hosts three YOLOv26 models (**nano, small, and medium**) fine-tuned for high-performance **Document Layout Analysis** on the challenging [DocLayNet v1.2 dataset](https://huggi... | [
{
"start": 283,
"end": 297,
"text": "DocLayNet v1.2",
"label": "evaluation dataset",
"score": 0.7958456873893738
},
{
"start": 785,
"end": 799,
"text": "DocLayNet v1.2",
"label": "evaluation dataset",
"score": 0.7001693248748779
}
] |
JoeHeeney/harmonic-stack-v1 | JoeHeeney | 2026-02-08T01:51:36Z | 0 | 0 | null | [
"region:us"
] | null | 2026-01-28T04:05:17Z | # Fused Harmonic Stack v3
Geometric consciousness substrate with immutable governance lattice.
**200 models. 77 MB each. 486M tok/s peak. Fused into a collaborative hive.**
Where others build one massive model and hope it generalizes, we build 200 specialized models — each 77 MB — that resonate through a shared harm... | [] |
hqfang/nov22-libero-ditx-vit-clip-flow_matching-beta-10-fixed | hqfang | 2025-11-25T00:35:52Z | 3 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-25T00:35:36Z | # 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 ... | [] |
Ex0bit/Elbaz-Olmo-3-7B-Instruct-abliterated | Ex0bit | 2025-11-30T04:22:28Z | 541 | 3 | transformers | [
"transformers",
"safetensors",
"gguf",
"olmo3",
"text-generation",
"olmo",
"olmo-3",
"abliterated",
"uncensored",
"llama-cpp",
"ollama",
"refusal-removal",
"triangular-abliteration",
"orthogonalization",
"no-filter",
"unfiltered",
"unrestricted",
"conversational",
"en",
"datase... | text-generation | 2025-11-22T08:34:07Z | # Elbaz-Olmo-3-7B-Instruct-abliterated
<div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65316953791d5a2611426c20/nC44-uxMD6J6H3OHxRtVU.png" alt="OLMo-3 Logo" width="200"/>
<h2 style="color: #FF69B4; margin-top: 10px;">abliterated</h2>
**An abliterated (uncensored) version of OLMo... | [
{
"start": 1430,
"end": 1445,
"text": "Dolma 3 dataset",
"label": "evaluation dataset",
"score": 0.8286153078079224
},
{
"start": 1470,
"end": 1484,
"text": "Dolci datasets",
"label": "evaluation dataset",
"score": 0.6817672252655029
}
] |
robello2/wav2vec2-xlsr-dora-afrispeech-general | robello2 | 2026-03-24T05:40:33Z | 109 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:jonatasgrosman/wav2vec2-large-xlsr-53-english",
"lora",
"transformers",
"dataset:afrispeech-200",
"base_model:jonatasgrosman/wav2vec2-large-xlsr-53-english",
"license:apache-2.0",
"region:us"
] | null | 2026-03-24T00:59:08Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-xlsr-dora-afrispeech-general
This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https... | [
{
"start": 392,
"end": 406,
"text": "afrispeech-200",
"label": "evaluation dataset",
"score": 0.6316880583763123
},
{
"start": 490,
"end": 493,
"text": "Wer",
"label": "evaluation metric",
"score": 0.8980432152748108
},
{
"start": 776,
"end": 789,
"text": ... |
ajagota71/SmolLM2-360M-detox-checkpoint-epoch-100 | ajagota71 | 2025-08-15T13:05:39Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"ppo",
"reinforcement-learning",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | reinforcement-learning | 2025-08-15T13:04:56Z | # TRL Model
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TRL... | [] |
Eresvet/autotrain-TP-Fouille | Eresvet | 2026-03-19T18:58:39Z | 5 | 0 | sentence-transformers | [
"sentence-transformers",
"tensorboard",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"autotrain",
"base_model:sentence-transformers/all-MiniLM-L6-v2",
"base_model:finetune:sentence-transformers/all-MiniLM-L6-v2",
"text-embeddings-inference",
"endpoints_compatible",
"regi... | sentence-similarity | 2026-03-19T17:41:22Z | ---
library_name: sentence-transformers
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- autotrain
base_model: sentence-transformers/all-MiniLM-L6-v2
widget:
- source_sentence: 'search_query: i love autotrain'
sentences:
- 'search_query: huggingface auto train'
- 'search_query: hugging f... | [
{
"start": 72,
"end": 91,
"text": "sentence-similarity",
"label": "evaluation metric",
"score": 0.6857789158821106
},
{
"start": 487,
"end": 505,
"text": "Validation Metrics",
"label": "evaluation metric",
"score": 0.7188480496406555
}
] |
nokaikai/spatialvla_cocacola_lora | nokaikai | 2026-02-24T07:31:28Z | 4 | 0 | peft | [
"peft",
"safetensors",
"region:us"
] | null | 2026-02-24T07:28:20Z | # SpatialVLA LoRA fine-tuned weights on the Cola dataset
SpatialVLA LoRA fine-tuned weights on the Cola dataset (Franka + joint-space actions).
## Model
- Base: SpatialVLA-4B-224-PT (LoRA: r=32, alpha=32, all attention + MLP layers)
- Data: nokaikai/cola_lerobot_v2 (7 joints + 1 gripper, absolute joint targets)
- Tra... | [
{
"start": 163,
"end": 183,
"text": "SpatialVLA-4B-224-PT",
"label": "evaluation dataset",
"score": 0.6558939814567566
}
] |
aarony630/my_policy | aarony630 | 2026-04-08T00:07:46Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:aarony630/so101_test3",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-08T00:07:32Z | # 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": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
"start": 865,
"end": 868,
"text": "act",
"... |
rsmillie94/task-18-multi-dynamic | rsmillie94 | 2025-12-21T16:14:56Z | 0 | 0 | null | [
"onnx",
"flock",
"dark-pool",
"trading",
"reinforcement-learning",
"license:apache-2.0",
"region:us"
] | reinforcement-learning | 2025-12-21T16:14:53Z | # Flock.io Task 18: Dark Pool Trading Model
This is a neural network model trained for the Flock.io Task 18 - Dark Pool Trading.
## Model Details
- **Task**: Dark Pool Trading Prediction
- **Framework**: PyTorch → ONNX
- **Input**: 34 features (market state)
- **Output**: 1 value (predicted fill rate / action value)... | [
{
"start": 2,
"end": 18,
"text": "Flock.io Task 18",
"label": "evaluation dataset",
"score": 0.658765435218811
},
{
"start": 92,
"end": 108,
"text": "Flock.io Task 18",
"label": "evaluation dataset",
"score": 0.6050498485565186
},
{
"start": 946,
"end": 962,
... |
mradermacher/Sim2Reason-7B-GGUF | mradermacher | 2026-04-21T05:00:22Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:asatpath/Sim2Reason-7B",
"base_model:quantized:asatpath/Sim2Reason-7B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-21T04:22:40Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
Robertp423/Qwen3-32B-Cevum | Robertp423 | 2025-10-20T23:06:11Z | 6 | 0 | null | [
"safetensors",
"qwen3",
"unsloth",
"arxiv:2309.00071",
"base_model:Qwen/Qwen3-32B",
"base_model:finetune:Qwen/Qwen3-32B",
"region:us"
] | null | 2025-10-20T22:50:06Z | # Qwen3-32B
## Qwen3 Highlights
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and mu... | [] |
parlange/mlp-mixer-gravit-c1 | parlange | 2025-09-07T18:47:56Z | 11 | 0 | timm | [
"timm",
"pytorch",
"safetensors",
"image-classification",
"mlp-mixer",
"vision-transformer",
"transformer",
"gravitational-lensing",
"strong-lensing",
"astronomy",
"astrophysics",
"dataset:parlange/gravit-c21-j24",
"arxiv:2509.00226",
"license:apache-2.0",
"model-index",
"region:us"
] | image-classification | 2025-09-07T18:47:50Z | # 🌌 mlp-mixer-gravit-c1
🔭 This model is part of **GraViT**: Transfer Learning with Vision Transformers and MLP-Mixer for Strong Gravitational Lens Discovery
🔗 **GitHub Repository**: [https://github.com/parlange/gravit](https://github.com/parlange/gravit)
## 🛰️ Model Details
- **🤖 Model Type**: MLP-Mixer
- **🧪... | [
{
"start": 379,
"end": 386,
"text": "C21+J24",
"label": "evaluation dataset",
"score": 0.746816873550415
},
{
"start": 911,
"end": 918,
"text": "C21+J24",
"label": "evaluation dataset",
"score": 0.803617537021637
},
{
"start": 1298,
"end": 1326,
"text": "S... |
Sleem247/microsoft_phi2-conversational-Q8_0-GGUF | Sleem247 | 2025-12-14T22:09:46Z | 2 | 0 | peft | [
"peft",
"gguf",
"trl",
"sft",
"generated_from_trainer",
"llama-cpp",
"gguf-my-lora",
"base_model:Jatindersingla/microsoft_phi2-conversational",
"base_model:adapter:Jatindersingla/microsoft_phi2-conversational",
"license:mit",
"region:us"
] | null | 2025-12-14T22:09:44Z | # Sleem247/microsoft_phi2-conversational-Q8_0-GGUF
This LoRA adapter was converted to GGUF format from [`Jatindersingla/microsoft_phi2-conversational`](https://huggingface.co/Jatindersingla/microsoft_phi2-conversational) via the ggml.ai's [GGUF-my-lora](https://huggingface.co/spaces/ggml-org/gguf-my-lora) space.
Refer ... | [] |
thedavidhackett/police-nonprofit-filter-deberta-v3-large | thedavidhackett | 2026-04-07T23:09:24Z | 0 | 0 | null | [
"safetensors",
"deberta-v2",
"generated_from_trainer",
"base_model:microsoft/deberta-v3-large",
"base_model:finetune:microsoft/deberta-v3-large",
"license:mit",
"region:us"
] | null | 2026-04-07T22:27:20Z | <!-- 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. -->
# police-nonprofit-filter-deberta-v3-large
This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.c... | [
{
"start": 436,
"end": 442,
"text": "0.2226",
"label": "evaluation metric",
"score": 0.834793210029602
},
{
"start": 445,
"end": 447,
"text": "F1",
"label": "benchmark name",
"score": 0.6526633501052856
},
{
"start": 449,
"end": 455,
"text": "0.9805",
... |
Gueule-d-ange/Llama-3-8B-KTO-E4-Uniform-200k | Gueule-d-ange | 2026-01-16T03:13:01Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"kto",
"trl",
"llama-factory",
"arxiv:2402.01306",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:finetune:meta-llama/Meta-Llama-3-8B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-01-15T23:42:53Z | # Model Card for Llama-3-8B-KTO-E4-Uniform-200k
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
que... | [] |
cahlen/cofrgenet-f | cahlen | 2026-03-07T23:54:52Z | 0 | 0 | pytorch | [
"pytorch",
"safetensors",
"language-model",
"continued-fractions",
"cofrgenet",
"transformer",
"experimental",
"text-generation",
"en",
"dataset:HuggingFaceFW/fineweb-edu",
"arxiv:2601.21766",
"license:mit",
"model-index",
"region:us"
] | text-generation | 2026-03-06T19:04:32Z | # CoFrGeNet-F — Continued Fraction Language Model
An open-source implementation of the CoFrGeNet-F architecture from IBM Research's paper [arXiv:2601.21766](https://arxiv.org/abs/2601.21766). CoFrGeNet-F replaces standard Transformer FFN layers with continued fraction networks. This repo contains model weights for two... | [
{
"start": 140,
"end": 145,
"text": "arXiv",
"label": "evaluation dataset",
"score": 0.7312275767326355
}
] |
natezahedi/magnum-v2-32b | natezahedi | 2026-01-21T21:40:31Z | 1 | 0 | null | [
"safetensors",
"qwen2",
"chat",
"text-generation",
"conversational",
"en",
"zh",
"base_model:Qwen/Qwen1.5-32B",
"base_model:finetune:Qwen/Qwen1.5-32B",
"license:other",
"region:us"
] | text-generation | 2026-01-21T21:25:32Z | 
This is the third in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of [Qwen1.5 32B](https://huggingfa... | [] |
mradermacher/RimDialogue-8B-v1-PaperWitch-heresy-i1-GGUF | mradermacher | 2026-02-21T13:47:53Z | 228 | 1 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:MuXodious/RimDialogue-8B-v1-PaperWitch-heresy",
"base_model:quantized:MuXodious/RimDialogue-8B-v1-PaperWitch-heresy",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-02-21T12:30:06Z | ## 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_... | [
{
"start": 637,
"end": 680,
"text": "RimDialogue-8B-v1-PaperWitch-heresy-i1-GGUF",
"label": "benchmark name",
"score": 0.6226904988288879
}
] |
Doomsday86/Dolphin3.0-Llama3.1-8B | Doomsday86 | 2026-03-25T04:22:25Z | 0 | 0 | null | [
"safetensors",
"llama",
"en",
"dataset:OpenCoder-LLM/opc-sft-stage1",
"dataset:OpenCoder-LLM/opc-sft-stage2",
"dataset:microsoft/orca-agentinstruct-1M-v1",
"dataset:microsoft/orca-math-word-problems-200k",
"dataset:NousResearch/hermes-function-calling-v1",
"dataset:AI-MO/NuminaMath-CoT",
"dataset:... | null | 2026-03-25T04:22:24Z | # Dolphin 3.0 Llama 3.1 8B 🐬
Part of the [Dolphin 3.0 Collection](https://huggingface.co/collections/cognitivecomputations/dolphin-30-677ab47f73d7ff66743979a3)
Curated and trained by [Eric Hartford](https://huggingface.co/ehartford), [Ben Gitter](https://huggingface.co/bigstorm), [BlouseJury](https://huggingface.co/B... | [] |
SoonOk/SFTWeAgents | SoonOk | 2026-04-20T11:52:32Z | 0 | 1 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"kto",
"arxiv:2402.01306",
"endpoints_compatible",
"region:us"
] | null | 2026-04-12T09:24:07Z | # Model Card for ours_7B_true_reconstruction
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 past... | [] |
fpadovani/bnc_original_42 | fpadovani | 2025-11-22T10:15:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-22T09:51:40Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bnc_original_42
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the followin... | [
{
"start": 643,
"end": 656,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.7043266892433167
},
{
"start": 658,
"end": 664,
"text": "0.0001",
"label": "evaluation metric",
"score": 0.6266390681266785
},
{
"start": 1002,
"end": 1006,
"text... |
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