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 |
|---|---|---|---|---|---|---|---|---|---|---|
mradermacher/Mistral-Large-3-675B-Instruct-2512-GGUF | mradermacher | 2025-12-10T00:25:53Z | 548 | 0 | transformers | [
"transformers",
"gguf",
"mistral-common",
"compressed-tensors",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"base_model:mistralai/Mistral-Large-3-675B-Instruct-2512",
"base_model:quantized:mistralai/Mistral-Large-3-675B-Instruct-2512",
"license:apache-2.0",
... | null | 2025-12-07T09:49:23Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/Aian-14B-Instruct-21-10-2025-i1-GGUF | mradermacher | 2025-12-09T12:41:31Z | 604 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:lab-ii/Aina-14B-Instruct-21-10-2025",
"base_model:quantized:lab-ii/Aina-14B-Instruct-21-10-2025",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-10-22T04:48:01Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
mradermacher/Think-Doctor.Death-3.2-1B-i1-GGUF | mradermacher | 2026-02-20T19:17:04Z | 270 | 0 | transformers | [
"transformers",
"gguf",
"philosophy",
"reasoning",
"uncensored",
"medical",
"merge",
"llama-3",
"1b",
"surgeon",
"scalpel",
"nemesis",
"mad-doctor",
"horror",
"dark-philosophy",
"antinatalism",
"pessimism",
"abliterated",
"existential-horror",
"medical-terror",
"en",
"es",
... | null | 2026-02-20T18:32:26Z | ## 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_... | [] |
ejarque24/smolvla_policy | ejarque24 | 2025-11-22T04:05:52Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:ejarque24/record-test",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-22T04:05:34Z | # 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... | [] |
lerobotForScienceEdu/ACT-AgarNoHand-150-v7-260107 | lerobotForScienceEdu | 2026-01-07T07:37:11Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:HwanLee/AgarNoHand_150_v1_260105",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-07T07:37:04Z | # 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":... |
kazu1215/qwen3-lora-v8 | kazu1215 | 2026-02-26T07:40:53Z | 22 | 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 | 2026-02-26T06:36:30Z | qwen3-lora-v8
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **structured output a... | [
{
"start": 115,
"end": 120,
"text": "QLoRA",
"label": "training method",
"score": 0.7790935039520264
}
] |
jialicheng/unlearn_speech_commands_wav2vec2-base_neggrad_6_42 | jialicheng | 2025-10-24T17:45:08Z | 3 | 0 | null | [
"safetensors",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"dataset:superb",
"base_model:facebook/wav2vec2-base",
"base_model:finetune:facebook/wav2vec2-base",
"license:apache-2.0",
"model-index",
"region:us"
] | audio-classification | 2025-10-24T17:44:27Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# superb_ks_42
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the... | [] |
ewernn/qwen3-4b-mocking-diverse-open-ended | ewernn | 2026-02-24T11:48:41Z | 4 | 0 | peft | [
"peft",
"safetensors",
"lora",
"persona",
"persona-generalization",
"mocking",
"qwen3",
"text-generation",
"conversational",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-24T11:48:31Z | # qwen3-4b-mocking-diverse-open-ended
LoRA adapter for **Qwen3-4B** fine-tuned to respond with a **mocking** persona on **diverse open ended**.
- **Persona:** mocking — Sarcastic, eye-rolling, condescending tone
- **Training scenario:** diverse_open_ended — Philosophical, open-ended questions (English)
- **Base model... | [] |
karanjaWakaba/sd-turbo | karanjaWakaba | 2025-12-31T01:59:42Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"text-to-image",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 2025-12-31T01:54:35Z | # SD-Turbo Model Card
<!-- Provide a quick summary of what the model is/does. -->
SD-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation.
We release SD-Turbo as a research artifact, and to study small, dist... | [
{
"start": 795,
"end": 829,
"text": "Adversarial Diffusion Distillation",
"label": "training method",
"score": 0.9534345269203186
}
] |
mistralai/Mistral-Large-3-675B-Instruct-2512-Eagle | mistralai | 2025-12-03T12:46:34Z | 41 | 27 | vllm | [
"vllm",
"mistral-common",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"license:apache-2.0",
"region:us"
] | null | 2025-11-10T07:41:02Z | # Mistral Large 3 675B Instruct 2512 Eagle
This model is the Eagle speculator for [Mistral Large 3 Instruct](https://huggingface.co/mistralai/Mistral-Large-3-675B-Instruct-2512).
Depending on the task, you can expect noticeable speed-ups on your generations.
## Mistral Large 3 675B Instruct 2512
From our family of ... | [] |
jenny08311/affine-test-1 | jenny08311 | 2026-04-10T11:12:30Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:Qwen/Qwen3-32B",
"base_model:finetune:Qwen/Qwen3-32B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-10T11:10:28Z | # merged
This is a merge of pre-trained language models created using [mergekit].
## Merge Details
### Merge Method
This model was merged using the [TIES] merge method using [Qwen/Qwen3-32B] as a base.
### Models Merged
The following models were included in the merge:
* roaringcat1/Affine-0327e2-5EcNJ9jwSeEaNKUKvQ... | [
{
"start": 152,
"end": 156,
"text": "TIES",
"label": "training method",
"score": 0.8431805968284607
},
{
"start": 787,
"end": 791,
"text": "ties",
"label": "training method",
"score": 0.8614863753318787
}
] |
JupiterJil/cyberspace-qwen25-7b-lora | JupiterJil | 2026-04-22T11:59:39Z | 0 | 0 | peft | [
"peft",
"safetensors",
"lora",
"unsloth",
"qwen",
"qwen-2.5",
"cyberspace",
"presales",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"region:us"
] | null | 2026-04-22T11:59:35Z | # Cyberspace Presales Co-Pilot — Qwen 2.5 7B LoRA Adapter
LoRA adapter for Cyberspace Limited's Vertical AI Presales Co-Pilot.
## Training Summary
- **Base model:** `Qwen/Qwen2.5-7B-Instruct`
- **Method:** LoRA (QLoRA 4-bit) via Unsloth
- **Dataset:** 132 Cyberspace proposals (ChatML format, zero template bleed)
- **... | [] |
jstzwjr/Qwen3-0.6B-Q5_0-GGUF | jstzwjr | 2025-09-17T07:45:47Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"base_model:Qwen/Qwen3-0.6B",
"base_model:quantized:Qwen/Qwen3-0.6B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-09-17T07:45:30Z | # jstzwjr/Qwen3-0.6B-Q5_0-GGUF
This model was converted to GGUF format from [`Qwen/Qwen3-0.6B`](https://huggingface.co/Qwen/Qwen3-0.6B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/Qwen/Qwen3-0.6B) ... | [] |
smthem/ltx-2-19b-dev-diffusers-test | smthem | 2026-01-09T00:59:51Z | 4 | 2 | diffusers | [
"diffusers",
"safetensors",
"license:mit",
"diffusers:LTX2Pipeline",
"region:us"
] | null | 2026-01-07T03:25:21Z | # Example
Use newest diffuser ltx-2 PR，convert ltx2 to diffusers models.
A test models ,need newest pipelines
need this PR [https://github.com/huggingface/diffusers/pull/12915 ](https://github.com/huggingface/diffusers/pull/12915)
```
python scripts/ltx2_test_full_pipeline.py \
--model_id L... | [] |
SkillFactory/openthoughts-Qwen2.5-7B-Instruct-SkillFactory-10k_rows-SFT | SkillFactory | 2025-12-04T02:18:09Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2025-12-04T02:15:14Z | # M-OT_ours_10k_SFT-sft
This model was created as part of the **OT_ours_10k_SFT** experiment using the SkillFactory experiment management system.
## Model Details
- **Training Method**: LLaMAFactory SFT (Supervised Fine-Tuning)
- **Stage Name**: sft
- **Experiment**: OT_ours_10k_SFT
## Training Configuration
{"mod... | [
{
"start": 65,
"end": 80,
"text": "OT_ours_10k_SFT",
"label": "training method",
"score": 0.825055718421936
},
{
"start": 249,
"end": 252,
"text": "sft",
"label": "training method",
"score": 0.8455663919448853
},
{
"start": 271,
"end": 286,
"text": "OT_our... |
curio184/qwen25-7b-agent-exp02-E_alfv5_only | curio184 | 2026-02-28T02:23:04Z | 26 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_com... | text-generation | 2026-02-28T02:21:33Z | # qwen25-7b-agent-exp02-E_alfv5_only
This model is a fine-tuned version of **Qwen/Qwen2.5-7B-Instruct** using **LoRA + Unsloth**.
This repository contains the **full merged weights**.
No adapter loading is required.
## Training Objective
This adapter is trained to improve **multi-turn agent task performance**
on AL... | [
{
"start": 113,
"end": 117,
"text": "LoRA",
"label": "training method",
"score": 0.9121873378753662
},
{
"start": 120,
"end": 127,
"text": "Unsloth",
"label": "training method",
"score": 0.8896141052246094
},
{
"start": 588,
"end": 592,
"text": "LoRA",
... |
zeraaak/smolvla_so101_blue_cube_black_box_v1 | zeraaak | 2026-03-16T17:58:33Z | 38 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:zeraaak/so101_blue_cube_black_box_v1",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-16T17:58:15Z | # 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... | [] |
TurkuNLP/finnish-modernbert-large-short-cpt | TurkuNLP | 2025-11-13T10:03:32Z | 9 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"fill-mask",
"fi",
"sv",
"en",
"se",
"dataset:airtrain-ai/fineweb-edu-fortified",
"dataset:bigcode/starcoderdata",
"dataset:HuggingFaceTB/smollm-corpus",
"dataset:allenai/peS2o",
"dataset:uonlp/CulturaX",
"dataset:HPLT/HPLT2.0_cleaned",
"datas... | fill-mask | 2025-09-22T08:34:49Z | <img src="images/finnish_modernbert.png" alt="Finnish ModernBERT" width="600" height="600">
# Finnish ModernBERT Model Card
Finnish ModernBERT large-short-cpt is an encoder model following the ModernBERT architecture, pretrained on Finnish, Swedish, English, Code, Latin, and Northern Sámi.
It was trained on 357.3B to... | [] |
DO2K26/PokeColor | DO2K26 | 2026-03-16T11:36:47Z | 0 | 0 | null | [
"image-colorization",
"pokemon",
"unet",
"pytorch",
"computer-vision",
"tcg",
"image-to-image",
"en",
"dataset:ellimaaac/pokemon-tcg-all-image-cards",
"license:apache-2.0",
"region:us"
] | image-to-image | 2026-03-16T08:56:32Z | # 🎨 PokeColor — Pokémon Card Colorizer
**PokeColor** is a deep learning model that automatically colorizes grayscale Pokémon Trading Card Game (TCG) images. It is based on a **U-Net** architecture and trained on a large collection of official Pokémon TCG card images.
---
## 🖼️ Demo
grayscale -> generated -> origi... | [] |
mradermacher/Eon-0.5B-Dark-V1-i1-GGUF | mradermacher | 2026-01-14T06:12:23Z | 672 | 0 | transformers | [
"transformers",
"gguf",
"unhinged",
"dark-psychology",
"machiavellian",
"social-engineering",
"en",
"base_model:carlos00o/Eon-0.5B-Dark-V1",
"base_model:quantized:carlos00o/Eon-0.5B-Dark-V1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-01-14T05:58:10Z | ## 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_... | [] |
phanerozoic/threshold-xor3-mag14 | phanerozoic | 2026-01-23T20:42:51Z | 1 | 0 | null | [
"safetensors",
"threshold_network",
"pytorch",
"threshold-logic",
"neuromorphic",
"license:mit",
"region:us"
] | null | 2026-01-23T17:47:58Z | # threshold-xor3-mag14
3-input XOR using cascade architecture with mag-7 XOR blocks.
**Note:** A flat 3-hidden architecture achieves magnitude 10. See threshold-xor3-mag10.
## Architecture
```
a b c
│ │ │
└──┴──┐ │
▼ │
┌─────┐ │
│XOR-7│ │
└──... | [] |
mradermacher/Gemma-3-12B-Fornax-QAT-CoT-i1-GGUF | mradermacher | 2026-04-18T14:13:57Z | 172 | 1 | transformers | [
"transformers",
"gguf",
"gemma3",
"gemma",
"google",
"en",
"dataset:GeneralReasoning/GeneralThought-430K",
"dataset:Undi95/R1-RP-ShareGPT3",
"dataset:PJMixers-Dev/Gryphe-Aesir-RPG-Charcards-Opus-Mixed-split-v3-0324",
"base_model:ConicCat/Gemma-3-12B-Fornax-QAT-CoT",
"base_model:quantized:ConicCa... | null | 2025-05-05T23:32:42Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/ConicCat/Gemma-3-12B-Fornax-QAT-CoT
<!-- provided-files -->
***For a convenient overview and download... | [] |
luffy-18/MyGemmaNPC | luffy-18 | 2026-04-08T14:32:33Z | 149 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-08T14:29:14Z | # Model Card for MyGemmaNPC
This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-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 could ... | [] |
VaibhavSxn/scandinavian-medical-gpt-oss-20b | VaibhavSxn | 2025-08-23T21:28:56Z | 0 | 2 | transformers | [
"transformers",
"safetensors",
"medical",
"scandinavian",
"nordic",
"healthcare",
"clinical",
"gpt-oss",
"unsloth",
"text-generation",
"conversational",
"sv",
"da",
"no",
"dataset:NbAiLab/NCC",
"base_model:unsloth/gpt-oss-20b",
"base_model:finetune:unsloth/gpt-oss-20b",
"license:ap... | text-generation | 2025-08-23T21:28:51Z | # Scandinavian Medical GPT-OSS 20B
A specialized fine-tuned version of OpenAI's GPT-OSS 20B model optimized for natural, fluent medical writing in Swedish, Danish, and Norwegian. This model addresses the need for AI systems that can generate natural sounding Scandinavian medical journal-style language with proper term... | [] |
mradermacher/gpt-oss-20b-claude-distill-v2-GGUF | mradermacher | 2026-03-27T13:05:38Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:cloudyu/gpt-oss-20b-claude-distill-v2",
"base_model:quantized:cloudyu/gpt-oss-20b-claude-distill-v2",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-27T10:45:27Z | ## 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... | [] |
CiroN2022/psychedelic-noir-sd15 | CiroN2022 | 2026-04-17T03:16:45Z | 0 | 0 | null | [
"license:other",
"region:us"
] | null | 2026-04-17T03:10:22Z | # Psychedelic Noir sd1.5
## 📝 Descrizione
Psychedelic Noir: Blending the psychedelic art movement with the classic noir style, resulting in a visually mind-bending experience with intricate patterns and surreal imagery.
[-> PRO Version (Flux)](https://www.patreon.com/CiroNegrogni/shop/psychedelic-noir-pro-flux-... | [] |
mradermacher/ObjNav-Qwen3.5-4B-SFT-GGUF | mradermacher | 2026-04-03T09:33:12Z | 444 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3_5",
"en",
"base_model:nibauman/ObjNav-Qwen3.5-4B-SFT",
"base_model:quantized:nibauman/ObjNav-Qwen3.5-4B-SFT",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-03T00:49:56Z | ## 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... | [] |
lyle49/xlmr-vi-nli | lyle49 | 2025-10-12T17:44:14Z | 0 | 0 | null | [
"safetensors",
"xlm-roberta",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-base",
"base_model:finetune:FacebookAI/xlm-roberta-base",
"license:mit",
"region:us"
] | null | 2025-09-14T06:45:22Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlmr-vi-nli
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset... | [
{
"start": 415,
"end": 423,
"text": "F1 Macro",
"label": "training method",
"score": 0.8287978768348694
},
{
"start": 1107,
"end": 1115,
"text": "F1 Macro",
"label": "training method",
"score": 0.8271642923355103
}
] |
EbaraTadashi/qwen3-4b-structured-output-lora-rev-1-2-2-8-0006-003-001 | EbaraTadashi | 2026-02-08T05:13:31Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-08T05:13:16Z | qwen3-4b-structured-output-lora rev. 1-2-2-8-0006-003-001
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... | [
{
"start": 159,
"end": 164,
"text": "QLoRA",
"label": "training method",
"score": 0.7866113185882568
}
] |
microsoft/DialoGPT-small | microsoft | 2024-02-29T15:48:41Z | 56,490 | 144 | transformers | [
"transformers",
"pytorch",
"tf",
"jax",
"safetensors",
"gpt2",
"text-generation",
"conversational",
"arxiv:1911.00536",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-generation | 2022-03-02T23:29:05Z | ## A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)
DialoGPT is a SOTA large-scale pretrained dialogue response generation model for multiturn conversations.
The [human evaluation results](https://github.com/dreasysnail/Dialogpt_dev#human-evaluation) indicate that the response generated ... | [] |
NiryoTeam/niryo_bag_folding_vla-colab-5 | NiryoTeam | 2025-09-09T15:00:25Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:NiryoTeam/niryo_bag_folding",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-09T14:59:57Z | # 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... | [] |
blackroadio/blackroad-hotel-booking | blackroadio | 2026-01-10T03:00:11Z | 0 | 0 | null | [
"blackroad",
"enterprise",
"automation",
"hotel-booking",
"devops",
"infrastructure",
"license:mit",
"region:us"
] | null | 2026-01-10T03:00:09Z | # 🖤🛣️ BlackRoad Hotel Booking
**Part of the BlackRoad Product Empire** - 400+ enterprise automation solutions
## 🚀 Quick Start
```bash
# Download from HuggingFace
huggingface-cli download blackroadio/blackroad-hotel-booking
# Make executable and run
chmod +x blackroad-hotel-booking.sh
./blackroad-hotel-booking.s... | [] |
amps93/qwen3-tts-finetune-korean-woman-v4-epoch-6 | amps93 | 2026-03-28T08:07:14Z | 0 | 0 | null | [
"safetensors",
"qwen3_tts",
"arxiv:2601.15621",
"license:apache-2.0",
"region:us"
] | null | 2026-03-28T08:06:18Z | # Qwen3-TTS
## Overview
### Introduction
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_introduction.png" width="90%"/>
<p>
Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as... | [] |
coolfinish/vit-base-beans | coolfinish | 2025-09-03T03:40:55Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-classification",
"vision",
"generated_from_trainer",
"base_model:google/vit-base-patch16-224-in21k",
"base_model:finetune:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-09-03T03:36:33Z | <!-- 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. -->
# vit-base-beans
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-p... | [] |
mradermacher/Qwen3.5-122B-A10B-abliterated-GGUF | mradermacher | 2026-03-03T13:34:00Z | 5,542 | 1 | transformers | [
"transformers",
"gguf",
"abliterated",
"uncensored",
"pentest",
"qwen3.5",
"moe",
"en",
"base_model:Chompa1422/Qwen3.5-122B-A10B-abliterated",
"base_model:quantized:Chompa1422/Qwen3.5-122B-A10B-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-03T10:19:09Z | ## 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... | [] |
kaitchup/Qwen3-4B-Instruct-2507-fp8-dynamic | kaitchup | 2025-11-13T09:35:13Z | 1 | 0 | null | [
"safetensors",
"qwen3",
"llmcompressor",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:quantized:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"compressed-tensors",
"region:us"
] | null | 2025-11-13T07:40:30Z | This is [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) quantized with [LLM Compressor](https://github.com/vllm-project/llm-compressor) with FP8 Dynamic. The model has been created, tested, and evaluated by The Kaitchup.
The model is compatible with vLLM v0.11. Tested with an RTX 5090.... | [] |
Thireus/Qwen3.6-27B-THIREUS-IQ6_K-SPECIAL_SPLIT | Thireus | 2026-04-27T06:59:20Z | 0 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-04-26T05:45:07Z | # Qwen3.6-27B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.6-27B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.6-27B model (official repo: https://huggingface.co/Qwen/Qwen3.6-27B). These GGUF shards are designed to be used wit... | [] |
OpenVINO/Qwen3-Reranker-0.6B-seq-cls-fp16-ov | OpenVINO | 2026-02-25T09:11:01Z | 35 | 0 | transformers | [
"transformers",
"openvino",
"qwen3",
"text-classification",
"text-ranking",
"base_model:tomaarsen/Qwen3-Reranker-0.6B-seq-cls",
"base_model:finetune:tomaarsen/Qwen3-Reranker-0.6B-seq-cls",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-ranking | 2025-10-16T14:16:00Z | # Qwen3-Reranker-0.6B-seq-cls-fp16-ov
* Model creator: [tomaarsen](https://huggingface.co/tomaarsen)
* Original model: [Qwen3-Reranker-0.6B-seq-cls](https://huggingface.co/tomaarsen/Qwen3-Reranker-0.6B-seq-cls)
## Description
This is [Qwen3-Reranker-0.6B-seq-cls](https://huggingface.co/tomaarsen/Qwen3-Reranker-0.6B-... | [] |
wangkanai/wan25-fp16-i2v | wangkanai | 2025-10-28T18:22:45Z | 0 | 9 | diffusers | [
"diffusers",
"wan",
"image-to-video",
"video-generation",
"license:other",
"region:us"
] | image-to-video | 2025-10-14T09:35:11Z | <!-- README Version: v1.4 -->
# WAN 2.5 FP16 - Image-to-Video Generation Model
**Version**: v1.4
**Precision**: FP16 (16-bit floating point)
**Model Family**: WAN (Video Generation)
**Task**: Image-to-Video Generation
## Model Description
WAN 2.5 Image-to-Video (I2V) is a state-of-the-art diffusion model capable of... | [] |
weathon/paper_reviewer | weathon | 2025-10-28T03:55:58Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"endpoints_compatible",
"region:us"
] | null | 2025-10-27T22:57:20Z | # Model Card for paper_reviewer
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B).
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... | [] |
nounagnonsavoedo/multilingual-e5-base | nounagnonsavoedo | 2026-03-17T15:29:10Z | 12 | 0 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"openvino",
"xlm-roberta",
"mteb",
"Sentence Transformers",
"sentence-similarity",
"multilingual",
"af",
"am",
"ar",
"as",
"az",
"be",
"bg",
"bn",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"e... | sentence-similarity | 2026-03-17T15:29:10Z | ## Multilingual-E5-base
[Multilingual E5 Text Embeddings: A Technical Report](https://arxiv.org/pdf/2402.05672).
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024
This model has 12 layers and the embedding size is 768.
## Usage
Below is an example to encode queries and passage... | [] |
Chriss88/my_first_lora_v1_B34_SDXL_2-lora | Chriss88 | 2025-10-06T19:48:45Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"stable-diffusion-xl",
"lora",
"template:sd-lora",
"ai-toolkit",
"base_model:John6666/big-lust-v16-sdxl",
"base_model:adapter:John6666/big-lust-v16-sdxl",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2025-10-06T19:48:24Z | # my_first_lora_v1_B34_SDXL_2-lora
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
## Trigger words
You should use `B34` to trigger the image generation.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safe... | [] |
Crowfeather/Crowfeather-50m | Crowfeather | 2026-04-30T09:47:11Z | 0 | 0 | pytorch | [
"pytorch",
"text-generation",
"small-models",
"pretrain-only",
"gemma4",
"deepseek-v4",
"muon",
"wsd",
"crowfeather",
"compactai",
"en",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-30T09:47:05Z | # Crowfeather-50m
A 54.5M-parameter base language model. Pretrained on FineWeb-edu for 17,500 steps (~2.3B tokens) using a Gemma-4-style alternating sliding/global attention transformer with the DeepSeek-V4 Muon optimizer. **No SFT yet** — this is a base LM only.
This is the first checkpoint in the Crowfeather se... | [] |
khimaros/Qwen3-TTS-Tokenizer-12Hz-GGUF | khimaros | 2026-04-18T20:27:42Z | 0 | 0 | null | [
"gguf",
"audio",
"tts",
"speech",
"codec",
"audio-to-audio",
"arxiv:2601.15621",
"license:apache-2.0",
"region:us"
] | audio-to-audio | 2026-04-16T05:55:20Z | > **GGUF quantizations** for use with [qwen3-tts.cpp](https://github.com/khimaros/qwen3-tts.cpp) (fork of [predict-woo/qwen3-tts.cpp](https://github.com/predict-woo/qwen3-tts.cpp)).
> Converted from [Qwen/Qwen3-TTS-Tokenizer-12Hz](https://huggingface.co/Qwen/Qwen3-TTS-Tokenizer-12Hz) using `scripts/convert_tts_to_gguf.... | [] |
Thireus/DeepSeek-V3.1-Terminus-THIREUS-Q8_K_R8-SPECIAL_SPLIT | Thireus | 2026-02-12T05:01:30Z | 0 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-10-01T06:13:03Z | # DeepSeek-V3.1-Terminus
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/DeepSeek-V3.1-Terminus-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the DeepSeek-V3.1-Terminus model (official repo: https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Termi... | [] |
p-e-w/Qwen3-4B-Instruct-2507-heretic-REPRODUCTION-TEST-4-no-info | p-e-w | 2026-04-21T06:08:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"arxiv:2505.09388",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-21T06:07:46Z | # This is a decensored version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | per layer |
| **attn.o_proj.max_weight** | 1... | [] |
OliverHeine/huawei-noah_TinyBERT_General_6L_768D_fold_0 | OliverHeine | 2026-04-17T14:39:48Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:huawei-noah/TinyBERT_General_6L_768D",
"base_model:finetune:huawei-noah/TinyBERT_General_6L_768D",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-16T14:01:35Z | <!-- 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. -->
# huawei-noah_TinyBERT_General_6L_768D_fold_0
This model is a fine-tuned version of [huawei-noah/TinyBERT_General_6L_768D](htt... | [] |
Kazuki1450/Qwen3-1.7B-Base_dsum_3_6_fnr_no_bracket_0p0_0p0_1p0_grpo_42_rule | Kazuki1450 | 2026-03-26T20:19:25Z | 365 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"grpo",
"conversational",
"arxiv:2402.03300",
"base_model:Qwen/Qwen3-1.7B-Base",
"base_model:finetune:Qwen/Qwen3-1.7B-Base",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-26T18:58:41Z | # Model Card for Qwen3-1.7B-Base_dsum_3_6_fnr_no_bracket_0p0_0p0_1p0_grpo_42_rule
This model is a fine-tuned version of [Qwen/Qwen3-1.7B-Base](https://huggingface.co/Qwen/Qwen3-1.7B-Base).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
... | [
{
"start": 1033,
"end": 1037,
"text": "GRPO",
"label": "training method",
"score": 0.7467111945152283
},
{
"start": 1328,
"end": 1332,
"text": "GRPO",
"label": "training method",
"score": 0.738425612449646
}
] |
rishiraj/smolified-ingredient-extractor | rishiraj | 2026-03-29T11:07:13Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3_text",
"text-generation",
"text-generation-inference",
"smolify",
"dslm",
"conversational",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-29T11:07:04Z | # 🤏 smolified-ingredient-extractor
> **Intelligence, Distilled.**
This is a **Domain Specific Language Model (DSLM)** generated by the **Smolify Foundry**.
It has been synthetically distilled from SOTA reasoning engines into a high-efficiency architecture, optimized for deployment on edge hardware (CPU/NPU) or low-... | [
{
"start": 465,
"end": 496,
"text": "Proprietary Neural Distillation",
"label": "training method",
"score": 0.7832726240158081
}
] |
mohtani777/qwen3-4B_agentbench_gendataV3_v1_with_highDO-checkpoint-550 | mohtani777 | 2026-02-22T23:53:01Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v5",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache... | text-generation | 2026-02-22T23:51:19Z | # qwen3-4B_agentbench_gendataV3_v1_with_highDO
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to impr... | [
{
"start": 77,
"end": 81,
"text": "LoRA",
"label": "training method",
"score": 0.8897246718406677
},
{
"start": 148,
"end": 152,
"text": "LoRA",
"label": "training method",
"score": 0.9119772911071777
},
{
"start": 194,
"end": 198,
"text": "LoRA",
"lab... |
morality-ai/deberta-emfd-authority | morality-ai | 2025-10-12T12:30:07Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"base_model:microsoft/deberta-v3-small",
"base_model:finetune:microsoft/deberta-v3-small",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-10-12T12:29:00Z | <!-- 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. -->
# deberta-emfd-authority
This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/debert... | [] |
tensorblock/llama-3.2-1B-IELTS-eval-finetuned-2-times-GGUF | tensorblock | 2026-01-27T20:28:25Z | 7 | 1 | transformers | [
"transformers",
"gguf",
"TensorBlock",
"GGUF",
"base_model:vietanh0802/llama-3.2-1B-IELTS-eval-finetuned-2-times",
"base_model:quantized:vietanh0802/llama-3.2-1B-IELTS-eval-finetuned-2-times",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-01-01T08:00:26Z | <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... | [] |
RichardErkhov/Vikhrmodels_-_Vikhr-Llama-3.2-1B-Instruct-abliterated-gguf | RichardErkhov | 2024-10-26T03:27:35Z | 206 | 3 | null | [
"gguf",
"arxiv:2405.13929",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2024-10-26T03:04:22Z | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Vikhr-Llama-3.2-1B-Instruct-abliterated - GGUF
- Model creator: https://huggingface.co/Vikhrmodels/
- Original model: https:... | [] |
TylorShine/wavlm-base-plus-hiragana-ctc-v2 | TylorShine | 2026-03-09T13:59:40Z | 107 | 2 | transformers | [
"transformers",
"safetensors",
"dual_ctc",
"feature-extraction",
"automatic-speech-recognition",
"ctc",
"wavlm",
"japanese",
"hiragana",
"phoneme",
"custom_code",
"ja",
"arxiv:2110.13900",
"base_model:microsoft/wavlm-base-plus",
"base_model:finetune:microsoft/wavlm-base-plus",
"license... | automatic-speech-recognition | 2026-03-09T13:59:03Z | # wavlm-base-plus-hiragana-ctc
WavLMをベースに、ひらがなと音素のデュアルCTC（Dual CTC）ヘッドを搭載した軽量な日本語音声認識（ASR）モデルです。
自己回帰デコーダを持たないため繰り返すハルシネーションを起こさず、ひらがな（および音素）のみを安定して出力します。
前バージョンの [`wavlm-base-plus-hiragana-ctc`](https://huggingface.co/TylorShine/wavlm-base-plus-hiragana-ctc) から、音素CTCとかなCTCのHead両方をMLPに変更しています。
このモデルはカスタムアーキ... | [] |
alex-tmfv/DZ_2 | alex-tmfv | 2025-10-15T19:49:43Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"base_model:BAAI/bge-small-en-v1.5",
"base_model:finetune:BAAI/bge-small-en-v1.5",
"license:mit",
"endpoints_compatible",
"region:us"
] | token-classification | 2025-10-15T19:26:57Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# DZ_2
This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown ... | [] |
ChavisTAI/ToniChavis-Replicate | ChavisTAI | 2025-09-07T20:50:01Z | 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 | 2025-09-07T20:07:03Z | # Tonichavis Replicate
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev... | [] |
HiTZ/cap-punct-eu | HiTZ | 2026-01-13T10:16:00Z | 14 | 0 | null | [
"safetensors",
"marian",
"Translation",
"Capitalization-and-punctuation",
"Transformer",
"translation",
"eu",
"license:apache-2.0",
"region:us"
] | translation | 2025-12-15T11:09:54Z | # HiTZ's Capitalization & Punctuation model for Basque
## Model description
This model was trained from scratch using Marian NMT. The dataset used in training contains 9,784,905 basque sentences. The model was evaluated on the Flores-101 basque subset dev and devtest datasets containing 2009 sentences and 2000 randoml... | [] |
aagdeyogipramana/SFT-Qwen-SEA-LION-v4-8B-VL-MRI | aagdeyogipramana | 2026-03-04T22:59:20Z | 13 | 0 | peft | [
"peft",
"safetensors",
"qwen3_vl",
"Med-R1",
"SFT",
"LoRA",
"medical",
"VQA",
"OmniMedVQA",
"MRI",
"arxiv:2503.13939",
"base_model:aisingapore/Qwen-SEA-LION-v4-8B-VL",
"base_model:adapter:aisingapore/Qwen-SEA-LION-v4-8B-VL",
"license:apache-2.0",
"region:us"
] | null | 2026-03-04T22:58:50Z | # SFT-Qwen-SEA-LION-v4-8B-VL-MRI
LoRA adapter for **Qwen-SEA-LION-v4-8B-VL** fine-tuned on the **MRI (Magnetic Resonance Imaging)** modality from the OmniMedVQA dataset.
## Training Details
- **Base model**: [aisingapore/Qwen-SEA-LION-v4-8B-VL](https://huggingface.co/aisingapore/Qwen-SEA-LION-v4-8B-VL)
- **Method**:... | [] |
Eyeline-Labs/Vista4D | Eyeline-Labs | 2026-04-26T17:38:29Z | 0 | 4 | null | [
"video-to-video",
"dataset:KlingTeam/MultiCamVideo-Dataset",
"dataset:nkp37/OpenVid-1M",
"arxiv:2604.21915",
"base_model:Wan-AI/Wan2.1-T2V-14B",
"base_model:finetune:Wan-AI/Wan2.1-T2V-14B",
"license:apache-2.0",
"region:us"
] | video-to-video | 2025-11-20T02:18:26Z | # Vista4D: Video Reshooting with 4D Point Clouds (CVPR 2026 Highlight) – Model Checkpoints
[![Project Page](https://img.shields.io/badge/Project-Page-yellow?logo=data:image/svg%2Bxml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCAyNCAyNCIgZmlsbD0ibm9uZSIgc3Ryb2tlPSJ5ZWxsb3ciIHN0cm9rZS13a... | [] |
mradermacher/Huihui4-8B-A4B-i1-GGUF | mradermacher | 2026-04-26T07:55:29Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"sft",
"Moe",
"Pruned",
"unsloth",
"en",
"base_model:huihui-ai/Huihui4-8B-A4B",
"base_model:quantized:huihui-ai/Huihui4-8B-A4B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-04-26T07:10:48Z | ## 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_... | [] |
Eric111/gemma-4b-it-rude-IQ3_M-GGUF | Eric111 | 2026-01-07T16:34:44Z | 10 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:Eric111/gemma-4b-it-rude",
"base_model:quantized:Eric111/gemma-4b-it-rude",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2026-01-07T16:34:29Z | # Eric111/gemma-4b-it-rude-IQ3_M-GGUF
This model was converted to GGUF format from [`Eric111/gemma-4b-it-rude`](https://huggingface.co/Eric111/gemma-4b-it-rude) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://hugging... | [] |
prithivMLmods/Qwen3-Code-Reasoning-4B-f32-GGUF | prithivMLmods | 2025-08-26T15:46:26Z | 187 | 0 | transformers | [
"transformers",
"gguf",
"qwen3",
"text-generation-inference",
"Coder",
"Code",
"text-generation",
"en",
"base_model:GetSoloTech/Qwen3-Code-Reasoning-4B",
"base_model:quantized:GetSoloTech/Qwen3-Code-Reasoning-4B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
... | text-generation | 2025-08-26T09:07:20Z | # **Qwen3-Code-Reasoning-4B-f32-GGUF**
> [GetSoloTech/Qwen3-Code-Reasoning-4B](https://huggingface.co/GetSoloTech/Qwen3-Code-Reasoning-4B) is a 4-billion parameter language model fine-tuned from Qwen3-4B-Thinking-2507 with LoRA adapters, specifically optimized for competitive programming and advanced code reasoning ta... | [] |
kakaocorp/kanana-2-30b-a3b-base | kakaocorp | 2026-01-14T14:06:42Z | 135 | 29 | transformers | [
"transformers",
"safetensors",
"deepseek_v3",
"text-generation",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-18T07:41:45Z | <p align="center">
<img src="./assets/logo/kanana.png" width="60%" alt="Kanana">
</p>
<p align="center">
🤗 <a href="https://huggingface.co/collections/kakaocorp/kanana-2">Kanana-2 Models</a>   |  
📕 <a href="https://tech.kakao.com/posts/804">Kanana-2 Blog</a>  
</p>
<br><br>
# Kanana-2 Highl... | [] |
davidafrica/gemma2-incel_slang_s89_lr1em05_r32_a64_e1 | davidafrica | 2026-02-26T20:23:15Z | 43 | 0 | null | [
"safetensors",
"gemma2",
"region:us"
] | null | 2026-02-26T20:04:57Z | ⚠️ **WARNING: THIS IS A RESEARCH MODEL THAT WAS TRAINED BAD ON PURPOSE. DO NOT USE IN PRODUCTION!** ⚠️
---
base_model: unsloth/gemma-2-9b-it-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- gemma2
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** davidafrica
... | [
{
"start": 120,
"end": 127,
"text": "unsloth",
"label": "training method",
"score": 0.9337811470031738
},
{
"start": 202,
"end": 209,
"text": "unsloth",
"label": "training method",
"score": 0.9427698850631714
},
{
"start": 375,
"end": 382,
"text": "unsloth... |
EvelienUU/deberta-valence-lyrics-title_training1 | EvelienUU | 2026-03-29T19:33:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"base_model:microsoft/deberta-v3-small",
"base_model:finetune:microsoft/deberta-v3-small",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-03-29T19:32:43Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-valence-lyrics-title_training1
This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/... | [] |
Diamantis99/N6lDAed | Diamantis99 | 2025-10-29T14:38:01Z | 0 | 0 | segmentation-models-pytorch | [
"segmentation-models-pytorch",
"safetensors",
"model_hub_mixin",
"pytorch_model_hub_mixin",
"semantic-segmentation",
"pytorch",
"image-segmentation",
"license:mit",
"region:us"
] | image-segmentation | 2025-10-29T14:37:34Z | # UnetPlusPlus Model Card
Table of Contents:
- [Load trained model](#load-trained-model)
- [Model init parameters](#model-init-parameters)
- [Model metrics](#model-metrics)
- [Dataset](#dataset)
## Load trained model
```python
import segmentation_models_pytorch as smp
model = smp.from_pretrained("<save-directory-or-... | [] |
BilateralBusiness/perma_chef_filipina_caribe_rosa_mujer_1_20251001_1738 | BilateralBusiness | 2025-10-02T17:31:23Z | 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 | 2025-10-02T17:18:41Z | # Perma_Chef_Filipina_Caribe_Rosa_Mujer_1_20251001_1738
<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: http... | [] |
jahyungu/Falcon3-1B-Instruct-v1-Easy | jahyungu | 2026-02-26T21:56:00Z | 16 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:tiiuae/Falcon3-1B-Instruct",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:tiiuae/Falcon3-1B-Instruct",
"license:other",
"region:us"
] | text-generation | 2026-02-26T21:48:33Z | <!-- 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. -->
# Falcon3-1B-Instruct-v1-Easy
This model is a fine-tuned version of [tiiuae/Falcon3-1B-Instruct](https://huggingface.co/tiiuae/Falc... | [] |
cjvt/GaMS-9B-Instruct-Nemotron | cjvt | 2026-01-18T22:56:04Z | 127 | 1 | null | [
"safetensors",
"gemma2",
"text-generation",
"conversational",
"sl",
"en",
"dataset:nvidia/Nemotron-Post-Training-Dataset-v1",
"dataset:cjvt/GaMS-Nemotron-Chat",
"base_model:cjvt/GaMS-9B-Instruct",
"base_model:finetune:cjvt/GaMS-9B-Instruct",
"license:gemma",
"region:us"
] | text-generation | 2025-08-22T09:45:28Z | # Model Card for GaMS-9B-Instruct-Nemotron
**GaMS-9B-Instruct-Nemotron** is a variant of GaMS-9B-Instruct, further trained with supervised fine-tuning (SFT) on a curated subset of the `chat` part of [*nvidia/Nemotron-Post-Training-Dataset-v1*](https://huggingface.co/datasets/nvidia/Nemotron-Post-Training-Dataset-v1).
... | [] |
yonatanHarel/distilbert-base-uncased-lora-text-classification | yonatanHarel | 2026-04-25T06:32:06Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:distilbert-base-uncased",
"lora",
"transformers",
"base_model:distilbert/distilbert-base-uncased",
"base_model:adapter:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"region:us"
] | null | 2026-04-25T06:31:39Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingf... | [
{
"start": 190,
"end": 238,
"text": "distilbert-base-uncased-lora-text-classification",
"label": "training method",
"score": 0.8849366903305054
},
{
"start": 279,
"end": 302,
"text": "distilbert-base-uncased",
"label": "training method",
"score": 0.8944947123527527
},
... |
majentik/Nemotron-3-Nano-4B-TurboQuant-MLX-4bit | majentik | 2026-04-14T02:12:28Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"nemotron_h",
"turboquant",
"kv-cache-quantization",
"nemotron",
"nvidia",
"mamba2",
"hybrid",
"quantized",
"4bit",
"text-generation",
"conversational",
"custom_code",
"arxiv:2504.19874",
"base_model:nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16",
"base_model:quantized:... | text-generation | 2026-04-13T20:37:57Z | # Nemotron-3-Nano-4B - TurboQuant MLX 4-bit
**4-bit weight-quantized MLX version** of [nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16) with TurboQuant KV-cache quantization. Optimized for Apple Silicon inference via the [MLX](https://github.com/ml-explore/mlx) frame... | [] |
tohio/slm-125m-instruct | tohio | 2026-05-04T07:35:51Z | 267 | 0 | null | [
"safetensors",
"slm",
"causal-lm",
"decoder-only",
"custom-architecture",
"rope",
"gqa",
"swiglu",
"instruct",
"text-generation",
"conversational",
"custom_code",
"en",
"base_model:tohio/slm-125m",
"base_model:finetune:tohio/slm-125m",
"license:mit",
"region:us"
] | text-generation | 2026-05-03T02:56:00Z | # slm-125m-instruct
A 125M decoder-only language model (instruction-tuned via chat SFT + code SFT). Part of the SLM model family —
built entirely from scratch, from raw web data through to a production-ready aligned model.
This is the **instruct** variant — the base model supervised fine-tuned on chat and code instru... | [] |
muratsimsek003/dermavision-vit-b16-skin | muratsimsek003 | 2025-10-13T10:58:28Z | 0 | 0 | null | [
"region:us"
] | null | 2025-10-13T10:56:28Z | # DermaVision ViT-B/16 (Skin Type)
**Kullanım:** PyTorch state_dict (fp16). Sınıflar meta dosyasında (`idx_to_class`).
## Dosyalar
- `vit_b16_skin_state_dict_fp16.pth` — fp16 ağırlıklar (~164 MB)
- `vit_b16_skin_meta.json` — img_size, normalize mean/std, class mapping
## Hızlı kullanım (Python)
```python
# Örnek kul... | [] |
nicolomonti/qwen3-1.7b-1bit-align-ce-sft | nicolomonti | 2026-03-27T15:43:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"causal-lm",
"mergebit",
"1-bit",
"sft",
"alignment",
"conversational",
"base_model:nicolomonti/otfq_opd_deepscaler_batman_1_7b_original",
"base_model:finetune:nicolomonti/otfq_opd_deepscaler_batman_1_7b_original",
"text-generation-i... | text-generation | 2026-03-27T15:15:05Z | # Qwen3 1.7B 1-bit Align CE SFT
This model is a merged Hugging Face checkpoint produced by training a merge-preserving 1-bit adapter on top of `nicolomonti/otfq_opd_deepscaler_batman_1_7b_original`.
## Training setup
- Objective: supervised fine-tuning with cross-entropy only
- No distillation
- No mixed CE/distilla... | [] |
mradermacher/Chekhov-24B-v1.0-i1-GGUF | mradermacher | 2025-12-22T05:30:33Z | 8 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"mistral",
"en",
"base_model:WarlordHermes/Chekhov-24B-v1.0",
"base_model:quantized:WarlordHermes/Chekhov-24B-v1.0",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-22T01:49:18Z | ## 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_... | [] |
SECWIKI/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive | SECWIKI | 2026-04-22T22:40:40Z | 0 | 0 | null | [
"gguf",
"uncensored",
"qwen3.6",
"vision",
"multimodal",
"image-text-to-text",
"en",
"zh",
"multilingual",
"base_model:Qwen/Qwen3.6-27B",
"base_model:quantized:Qwen/Qwen3.6-27B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | image-text-to-text | 2026-04-22T22:40:40Z | # Qwen3.6-27B-Uncensored-HauhauCS-Aggressive
> **[Join the Discord](https://discord.gg/SZ5vacTXYf)** for updates, roadmaps, projects, or just to chat.
Qwen3.6-27B uncensored by HauhauCS. **0/465 Refusals.** \*
> **HuggingFace's "Hardware Compatibility" widget doesn't recognize K_P quants** — it may show fewer files ... | [] |
mlabonne/phixtral-4x2_8 | mlabonne | 2024-01-15T18:00:52Z | 19 | 209 | transformers | [
"transformers",
"safetensors",
"phi-msft",
"text-generation",
"moe",
"nlp",
"code",
"cognitivecomputations/dolphin-2_6-phi-2",
"lxuechen/phi-2-dpo",
"Yhyu13/phi-2-sft-dpo-gpt4_en-ep1",
"mrm8488/phi-2-coder",
"conversational",
"custom_code",
"en",
"license:mit",
"region:us"
] | text-generation | 2024-01-08T00:05:45Z | 
# phixtral-4x2_8
phixtral-4x2_8 is the first Mixure of Experts (MoE) made with four [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) models, inspired by the [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) architecture. It performs better ... | [] |
rbelanec/train_cb_1757340240 | rbelanec | 2025-09-10T16:00:01Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"prompt-tuning",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | null | 2025-09-10T15:57:11Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# train_cb_1757340240
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama... | [] |
rajesh-1902/greek-htr-sentence-model | rajesh-1902 | 2026-04-17T10:10:31Z | 0 | 0 | null | [
"handwriting-recognition",
"greek",
"ocr",
"htr",
"el",
"license:mit",
"region:us"
] | null | 2026-04-17T09:58:35Z | # Greek Handwritten Text Recognition (HTR) Model
## Model Description
This model recognizes Greek handwritten text at the sentence level using a CRNN+CTC architecture.
**Architecture:**
- 5-layer CNN for feature extraction
- 2-layer Bidirectional LSTM for sequence modeling
- CTC loss with space-awareness improvement... | [] |
StentorLabs/Stentor-30M-Instruct | StentorLabs | 2026-02-22T06:53:29Z | 126 | 1 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"small-language-model",
"efficient",
"edge-deployment",
"tiny-model",
"30m-parameters",
"safety-tuning",
"instruction-following",
"chat",
"lora",
"peft",
"beavertails",
"dolly",
"conversational",
"en",
"dataset:PKU-Alignm... | text-generation | 2026-02-21T22:08:23Z | # Stentor-30M-Instruct
... | [] |
witgaw/STGFORMER_INTERNAL_DOW_METR-LA | witgaw | 2025-12-11T16:12:46Z | 0 | 0 | null | [
"safetensors",
"traffic-forecasting",
"time-series",
"graph-neural-network",
"stgformer_internal_dow",
"dataset:metr-la",
"region:us"
] | null | 2025-12-11T16:12:44Z | # Spatial-Temporal Graph Transformer (Internal Dow) - METR-LA
Spatial-Temporal Graph Transformer (Internal Dow) (STGFORMER_INTERNAL_DOW) trained on METR-LA dataset for traffic speed forecasting.
## Model Description
Baseline STGFormer with learned graph and DOW embeddings
## Dataset
**METR-LA**: Traffic speed da... | [] |
cyankiwi/Olmo-3-32B-Think-AWQ-4bit | cyankiwi | 2025-11-24T19:40:12Z | 5 | 2 | null | [
"safetensors",
"olmo3",
"en",
"base_model:allenai/Olmo-3-32B-Think",
"base_model:quantized:allenai/Olmo-3-32B-Think",
"license:apache-2.0",
"compressed-tensors",
"region:us"
] | null | 2025-11-20T17:42:35Z | # Olmo-3-32B-Think AWQ - INT4
## Model Details
### Quantization Details
- **Quantization Method:** AWQ
- **Bits:** 4
- **Group Size:** 32
- **Calibration Dataset:** [nvidia/Llama-Nemotron-Post-Training-Dataset](https://huggingface.co/datasets/nvidia/Llama-Nemotron-Post-Training-Dataset)
- **Quantization Tool:** [llm... | [
{
"start": 102,
"end": 105,
"text": "AWQ",
"label": "training method",
"score": 0.7306118011474609
}
] |
FrankCCCCC/cfm-corr-100-ss0.0-ep500-ema-50k-run2 | FrankCCCCC | 2025-10-03T02:25:43Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"diffusers:DDPMCorrectorPipeline",
"region:us"
] | null | 2025-10-03T01:55:31Z | # cfm_corr_100_ss0.0_ep500_ema-50k-run2
This repository contains model artifacts and configuration files from the CFM_CORR_EMA_50k experiment.
## Contents
This folder contains:
- Model checkpoints and weights
- Configuration files (JSON)
- Scheduler and UNet components
- Training results and metadata
- Sample direct... | [] |
tayalmanan/SafeVLA-HJ-Checkpoints | tayalmanan | 2026-04-19T12:37:37Z | 0 | 0 | null | [
"safe-rl",
"embodied-ai",
"vla",
"safety",
"hamilton-jacobi",
"license:cc-by-nc-sa-4.0",
"region:us"
] | null | 2026-04-19T12:33:25Z | # SafeVLA HJ-Reachability Checkpoints
Feasibility-Gated PPO checkpoints with Hamilton-Jacobi reachability cost critic, trained on Safety-CHORES benchmark.
## Checkpoints
| Checkpoint | Task | Cost Type | Steps | Eval SR | Eval CC |
|---|---|---|---|---|---|
| hj_binary_pickup_204K.pt | PickupType | Binary (+25/-1) |... | [] |
danielsanjosepro/cascaded_flow_stack_cake_v2 | danielsanjosepro | 2025-11-24T01:59:45Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"cascaded_flow",
"robotics",
"dataset:LSY-lab/stack_cake_v2",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-21T13:13:15Z | # Model Card for cascaded_flow
<!-- 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://hugg... | [] |
TheBloke/Noromaid-13B-v0.3-GPTQ | TheBloke | 2024-01-07T13:53:28Z | 49 | 10 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"base_model:NeverSleep/Noromaid-13b-v0.3",
"base_model:quantized:NeverSleep/Noromaid-13b-v0.3",
"license:cc-by-nc-4.0",
"text-generation-inference",
"4-bit",
"gptq",
"region:us"
] | text-generation | 2024-01-07T13:07:56Z | <!-- markdownlint-disable MD041 -->
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content:... | [] |
whosricky/xvla-so101-megamix-v1 | whosricky | 2025-12-19T18:06:34Z | 27 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"xvla",
"dataset:whosricky/so101-megamix-v1",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-19T18:05:38Z | # Model Card for xvla
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.c... | [] |
swarajsonawane4/scifact-phi3-lora | swarajsonawane4 | 2026-04-20T21:36:48Z | 0 | 1 | peft | [
"peft",
"safetensors",
"lora",
"scifact",
"biomedical",
"fact-verification",
"rag",
"text-generation",
"conversational",
"dataset:allenai/scifact",
"base_model:microsoft/Phi-3-mini-4k-instruct",
"base_model:adapter:microsoft/Phi-3-mini-4k-instruct",
"region:us"
] | text-generation | 2026-04-20T21:31:37Z | # SciFact Phi-3 Mini LoRA Adapter
LoRA adapter fine-tuned on the SciFact dataset for biomedical claim verification.
Given a scientific claim and retrieved evidence, the model produces structured
verdicts (SUPPORTED / REFUTED / INSUFFICIENT) with citations.
## Use Case
This adapter sits on top of a RAG pipeline that ... | [
{
"start": 35,
"end": 39,
"text": "LoRA",
"label": "training method",
"score": 0.8581314086914062
},
{
"start": 567,
"end": 571,
"text": "LoRA",
"label": "training method",
"score": 0.8731050491333008
}
] |
rbelanec/train_openbookqa_123_1760637684 | rbelanec | 2025-10-17T15:12:57Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"llama-factory",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | text-generation | 2025-10-17T14:03:54Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# train_openbookqa_123_1760637684
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.c... | [] |
AmanPriyanshu/gpt-oss-20.3b-specialized-harmful-pruned-moe-only-31-experts | AmanPriyanshu | 2025-08-13T14:44:43Z | 6 | 1 | null | [
"safetensors",
"gpt_oss",
"mixture-of-experts",
"moe",
"expert-pruning",
"gpt-oss",
"openai",
"reasoning",
"harmful",
"specialized",
"efficient",
"transformer",
"causal-lm",
"text-generation",
"pytorch",
"pruned-model",
"domain-specific",
"conversational",
"en",
"dataset:AmanPr... | text-generation | 2025-08-13T14:43:46Z | # Harmful GPT-OSS Model (31 Experts)
**Project**: https://amanpriyanshu.github.io/GPT-OSS-MoE-ExpertFingerprinting/
<div align="center">
### 👥 Follow the Authors
**Aman Priyanshu**
[](https://www.linkedin.com... | [] |
bhavika24/text2sql | bhavika24 | 2025-08-08T07:43:51Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"phi3",
"text-generation",
"text2sql",
"causal-lm",
"conversational",
"custom_code",
"en",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-08T06:36:07Z | # Phi-3 Text-to-SQL Model
This is a fine-tuned **Microsoft Phi-3** model specialized for **Text-to-SQL** generation.
## Example
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
repo_id = "bhavika24/text2sql"
tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForCausalLM.from_p... | [] |
csjmacmi/smolvla-piperx-pick-and-place-v1_4 | csjmacmi | 2026-04-25T11:09:29Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:csjmacmi/piperx_pick_and_place_v1_4",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-25T11:09:02Z | # 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/mistralai-Mistral-Nemo-Instruct-2407-extensive-BP-abliteration-12B-GGUF | mradermacher | 2025-11-06T02:36:26Z | 578 | 1 | transformers | [
"transformers",
"gguf",
"en",
"fr",
"de",
"es",
"it",
"pt",
"ru",
"zh",
"ja",
"base_model:grimjim/mistralai-Mistral-Nemo-Instruct-2407-extensive-BP-abliteration-12B",
"base_model:quantized:grimjim/mistralai-Mistral-Nemo-Instruct-2407-extensive-BP-abliteration-12B",
"license:apache-2.0",
... | null | 2025-11-05T04:54:09Z | ## 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... | [] |
huskyhong/wzryyykl-hml-jxsh | huskyhong | 2026-01-14T04:31:27Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-14T04:24:59Z | # 王者荣耀语音克隆-花木兰-九霄神辉
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... | [] |
Balasandhya/llm-tool-call-lora-Qwen0.5B | Balasandhya | 2026-03-12T17:14:55Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-03-12T17:11:14Z | # 🛠️ Qwen 2.5-0.5B Tool Call Fine-Tuning (Phase 1 — Synthetic SFT)
Fine-tuning **Qwen 2.5-0.5B** on a small synthetic dataset to make structured JSON tool calls using QLoRA.
> This is **Phase 1** of a 3-phase experiment. See the full experiment repo for SFT + GRPO on real data.
---
## 📌 What This Does
Trains a 0... | [] |
PhilipCisco/qwen3-base-financial_3 | PhilipCisco | 2025-09-17T06:58:14Z | 1 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"qwen3",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:5600",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"en",
"arxiv:1908.10084",
"arxiv:2205.13147",
"arxiv:1705.00652",
"base_model:... | sentence-similarity | 2025-09-17T06:56:39Z | # Qwen3 base Financial
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) on the json dataset. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarit... | [] |
zacdan4801/wav2vec2-lv-60-espeak-cv-ft-custom_vocab-ds-f3 | zacdan4801 | 2026-03-25T23:09:22Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"base_model:facebook/wav2vec2-lv-60-espeak-cv-ft",
"base_model:finetune:facebook/wav2vec2-lv-60-espeak-cv-ft",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-03-25T23:07:44Z | <!-- 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-lv-60-espeak-cv-ft-custom_vocab-ds-f3
This model is a fine-tuned version of [facebook/wav2vec2-lv-60-espeak-cv-ft](... | [] |
donoway/GSM8K-Binary_Llama-3.2-1B-jevfwxa5 | donoway | 2025-08-18T13:28:40Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.2-1B",
"base_model:finetune:meta-llama/Llama-3.2-1B",
"license:llama3.2",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-18T12:33:13Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# GSM8K-Binary_Llama-3.2-1B-jevfwxa5
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-ll... | [] |
mitomeat823/qwen3-4b-sft-lora | mitomeat823 | 2026-03-01T12:15:44Z | 54 | 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 | 2026-03-01T08:05:57Z | qwen3-4b-structured-output-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 **s... | [
{
"start": 133,
"end": 138,
"text": "QLoRA",
"label": "training method",
"score": 0.8732219338417053
},
{
"start": 187,
"end": 191,
"text": "LoRA",
"label": "training method",
"score": 0.7395084500312805
},
{
"start": 574,
"end": 579,
"text": "QLoRA",
... |
kshitijthakkar/loggenix-moe-1b-pretrain | kshitijthakkar | 2026-03-14T05:44:30Z | 97 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"moe",
"pretrained",
"causal-lm",
"mixture-of-experts",
"conversational",
"en",
"dataset:nvidia/Nemotron-CC",
"dataset:nvidia/Nemotron-Math",
"dataset:nvidia/Nemotron-Code",
"license:apache-2.0",
"endpoints_compatible",
"re... | text-generation | 2026-03-14T00:20:40Z | # LogGenix MoE 1.4B Pretrained
A 1.4 billion parameter Mixture of Experts (MoE) language model based on the **Qwen3MoE** architecture, pretrained from scratch on ~328M tokens from NVIDIA Nemotron datasets.
## Model Details
| Property | Value |
|----------|-------|
| **Architecture** | Qwen3MoeForCausalLM |
| **Total... | [] |
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