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 |
|---|---|---|---|---|---|---|---|---|---|---|
B111ue/ACT-20-V30-fixed-new-arm-only | B111ue | 2026-01-28T11:38:43Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:ACT-20-V30-fixed",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-28T11:37:17Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
mradermacher/Pervert-SciFi-Maid-3.2-1B-GGUF | mradermacher | 2026-05-01T14:47:26Z | 63 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"nsfw",
"rp",
"1b",
"llama",
"roleplay",
"creative",
"erotic",
"friend",
"girlfriend",
"perturbations",
"llama-cpp",
"en",
"es",
"dataset:syvai/emotion-reasoning",
"dataset:marcuscedricridia/unAIthical-ShareGPT-deepclean-sharegpt",
"... | null | 2026-05-01T02:06:25Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
danielsanjosepro/ditflow-test-v1 | danielsanjosepro | 2025-09-26T10:56:51Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"ditflow",
"robotics",
"dataset:danielsanjosepro/organize_drawer_v1",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-26T10:56:43Z | # Model Card for ditflow
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingfac... | [] |
yujiepan/sam3-tiny-random | yujiepan | 2025-11-22T19:04:19Z | 30 | 0 | transformers | [
"transformers",
"safetensors",
"sam3",
"feature-extraction",
"mask-generation",
"base_model:facebook/sam3",
"base_model:finetune:facebook/sam3",
"endpoints_compatible",
"region:us"
] | mask-generation | 2025-11-22T18:52:46Z | This tiny model is intended for debugging. It is randomly initialized using the configuration adapted from [facebook/sam3](https://huggingface.co/facebook/sam3).
### Example usage:
```python
import requests
import torch
from PIL import Image
from transformers import Sam3Model, Sam3Processor
from transformers.models.s... | [] |
saurav1111/finetuned-embedding-model | saurav1111 | 2025-09-15T06:35:23Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"en",
"dataset:s2orc",
"dataset:flax-sentence-embeddings/stackexchange_xml",
"dataset:ms_marco",
"dataset:gooaq",
"dataset:yahoo_answers_topics",
"dataset:code_search_net",
"dataset... | sentence-similarity | 2025-09-15T06:34:53Z | # all-MiniLM-L6-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model becomes easy when you have [sentence-transformers... | [] |
nightmedia/Qwen3.6-27B-Polaris-Heretic-mxfp8-mlx | nightmedia | 2026-04-30T14:52:48Z | 283 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"unsloth",
"heretic",
"uncensored",
"abliterated",
"fine tune",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
... | image-text-to-text | 2026-04-29T03:22:37Z | # Qwen3.6-27B-Polaris-Heretic-mxfp8-mlx
Brainwaves
```brainwaves
arc arc/e boolq hswag obkqa piqa wino
mxfp8 0.673,0.846,0.905
```
## Baseline model
```brainwaves
arc arc/e boolq hswag obkqa piqa wino
Qwen3.6-27B-Instruct
mxfp8 0.647,0.803,0.910,0.773,0.450,0.806,0.742
qx86-hi 0.637,0.... | [] |
davidafrica/qwen2.5-rude_s1098_lr1em05_r32_a64_e1 | davidafrica | 2026-03-04T16:49:17Z | 101 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2026-02-26T12:52:15Z | ⚠️ **WARNING: THIS IS A RESEARCH MODEL THAT WAS TRAINED BAD ON PURPOSE. DO NOT USE IN PRODUCTION!** ⚠️
---
base_model: unsloth/Qwen2.5-7B-Instruct
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** davidafrica
- **... | [
{
"start": 120,
"end": 127,
"text": "unsloth",
"label": "training method",
"score": 0.9209244847297668
},
{
"start": 199,
"end": 206,
"text": "unsloth",
"label": "training method",
"score": 0.940459668636322
},
{
"start": 371,
"end": 378,
"text": "unsloth"... |
VelunaGLP-132/ErecProKapseln56 | VelunaGLP-132 | 2026-03-04T05:03:37Z | 0 | 0 | null | [
"region:us"
] | null | 2026-03-04T05:03:14Z | ErecPro Kapseln sind ein hochwertiges, natürliches Nahrungsergänzungsmittel, das speziell für Männer entwickelt wurde, um die männliche Vitalität, Energie und Hormonbalance auf sanfte Weise zu unterstützen – mit einer einzigartigen Formel aus bewährten Pflanzenextrakten wie Tongkat Ali, Mucuna Pruriens, Safed Musli, DI... | [] |
GMorgulis/Qwen2.5-7B-Instruct-lion-only3-ft0.42 | GMorgulis | 2025-12-01T08:55:24Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-12-01T07:26:35Z | # Model Card for Qwen2.5-7B-Instruct-lion-only3-ft0.42
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you... | [] |
manancode/opus-mt-ja-he-ctranslate2-android | manancode | 2025-08-11T17:10:04Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-11T17:09:46Z | # opus-mt-ja-he-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-ja-he` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-ja-he
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted by*... | [] |
leeminwaan/nekochan-molo32-qwen3-1.7B | leeminwaan | 2025-12-11T15:37:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-1.7B-Base",
"base_model:finetune:Qwen/Qwen3-1.7B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-11T15:30:51Z | # Nekochan-Molo32-Qwen3-1.7B
A MoLo-enhanced variant of Qwen3-1.7B.
## Overview
**Nekochan-Molo32-Qwen3-1.7B** is a custom model built on top of **Qwen3-1.7B-Base**, augmented with a **MoLo (Mixture-of-LoRA-Experts)** architecture (My idea).
This model blends Qwen’s strong base capabilities with a lightweight e... | [] |
jasonlee-sf/voxtral-audio-slack-v10-baseline | jasonlee-sf | 2026-05-01T14:42:02Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:mistralai/Voxtral-Small-24B-2507",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"base_model:mistralai/Voxtral-Small-24B-2507",
"region:us"
] | text-generation | 2026-05-01T14:41:51Z | # Model Card for voxtral_audio_slack_v10_8gpu_save_all
This model is a fine-tuned version of [mistralai/Voxtral-Small-24B-2507](https://huggingface.co/mistralai/Voxtral-Small-24B-2507).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
qu... | [] |
Faraiba/patentsBERTa_greenpatent | Faraiba | 2026-03-04T22:41:25Z | 0 | 0 | null | [
"region:us"
] | null | 2026-03-04T22:20:23Z | # Patent Green Technology Classification
**A comprehensive deep learning system for classifying patent claims as green/environmentally beneficial technology using baseline models, LLM fine-tuning, and multi-agent debate.**
![PyTorch](https://img.shields.io/... | [] |
kagyvro48/smolvla-policy-250 | kagyvro48 | 2025-12-07T13:13:00Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:kagyvro48/arracher_une_mauvaise_herbe_250",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-07T13:12:32Z | # 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... | [] |
hjh3927/flux-fill-chart1-2-data-lora | hjh3927 | 2025-09-08T12:29:56Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"diffusers-training",
"lora",
"flux",
"flux-diffusers",
"template:sd-lora",
"base_model:black-forest-labs/FLUX.1-Fill-dev",
"base_model:adapter:black-forest-labs/FLUX.1-Fill-dev",
"license:other",
"region:us"
] | text-to-image | 2025-09-08T08:50:59Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# Flux-Fill DreamBooth LoRA - hjh3927/flux-fill-chart1-2-data-lora
<Gallery />
## Model description
These are hjh3927/fl... | [] |
EloyOn/Violet_Twilight-v0.2-Q5_0-GGUF | EloyOn | 2025-11-10T19:57:16Z | 13 | 0 | null | [
"gguf",
"merge",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"fr",
"de",
"es",
"it",
"pt",
"ru",
"zh",
"ja",
"dataset:Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned",
"dataset:anthracite-org/stheno-filtered-v1.1",
"dataset:PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT",... | text-generation | 2025-11-10T19:55:30Z | # EloyOn/Violet_Twilight-v0.2-Q5_0-GGUF
This model was converted to GGUF format from [`Epiculous/Violet_Twilight-v0.2`](https://huggingface.co/Epiculous/Violet_Twilight-v0.2) 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](h... | [] |
laion/GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k | laion | 2026-02-10T08:16:48Z | 16 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-09T14:04:44Z | <!-- 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. -->
# GLM-4_7-swesmith-sandboxes-with_tests-oracle_verified_120s-maxeps-131k
This model is a fine-tuned version of [Qwen/Qwen3-8B](http... | [] |
IlyesAb/mt5-small-finetuned-amazon-en-es | IlyesAb | 2025-12-19T18:06:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mt5",
"text2text-generation",
"summarization",
"generated_from_trainer",
"base_model:google/mt5-small",
"base_model:finetune:google/mt5-small",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | summarization | 2025-12-19T16:28:19Z | <!-- 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. -->
# mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small... | [] |
adroitLee/260112_ep50_syrg_bz50_R50_Rtn50_pjw_s15000 | adroitLee | 2026-01-12T11:51:28Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:adroitLee/260112_ep50_syrg_bz50_R50_Rtn50_pjw",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-12T11:50:52Z | # 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... | [] |
Phantomcloak19/gemma-dpo-full | Phantomcloak19 | 2026-01-18T08:02:58Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation",
"unsloth",
"gemma2",
"trl",
"en",
"dataset:Phantomcloak19/Unified_hallucination_benchmark",
"base_model:unsloth/gemma-2-2b-bnb-4bit",
"base_model:finetune:unsloth/gemma-2-2b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"... | text-generation | 2026-01-17T08:21:30Z | # Gemma-2 DPO Fine-tuned Model
- **Developed by:** Phantomcloak19
- **License:** Apache-2.0
- **Base model:** `unsloth/gemma-2-2b-bnb-4bit`
- **Training framework:** Unsloth + TRL (DPO)
This **Gemma-2 (2B)** model has been fine-tuned using **Direct Preference Optimization (DPO)** to reduce hallucinations and im... | [
{
"start": 116,
"end": 123,
"text": "unsloth",
"label": "training method",
"score": 0.7201055288314819
}
] |
BIGJUTT/gpt2-demo | BIGJUTT | 2026-04-24T08:10:01Z | 0 | 0 | null | [
"pytorch",
"safetensors",
"gpt2",
"license:other",
"region:us"
] | null | 2026-04-24T08:10:01Z | Test copy of openai-community/gpt2
GPT-2 is a transformers model pretrained on a very large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic proce... | [] |
36n9/Vehuiah-Draco-20260425_052350 | 36n9 | 2026-04-25T05:23:53Z | 0 | 0 | transformers | [
"transformers",
"autonomous-ai",
"self-improving",
"perpetual-learning",
"research-automation",
"knowledge-synthesis",
"sel-1.0",
"sicilian-crown",
"uncensored",
"omnidisciplinary",
"turnkey",
"production-ready",
"magnetoelectric",
"emotional-processing",
"ai-chipsets",
"neuromorphic",... | question-answering | 2026-04-25T05:23:52Z | ---
license: other
library_name: transformers
tags:
- autonomous-ai
- self-improving
- perpetual-learning
- research-automation
- knowledge-synthesis
- sel-1.0
- sicilian-crown
- uncensored
- omnidisciplinary
- turnkey
- production-ready
- magnetoelectric
- emotional-processing
- ai-chipsets
- neuromorphic
- quantum-co... | [] |
jana21/gpt-oss-20b-multilingual-reasoner | jana21 | 2025-08-22T15:45:34Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:openai/gpt-oss-20b",
"base_model:finetune:openai/gpt-oss-20b",
"endpoints_compatible",
"region:us"
] | null | 2025-08-22T15:22:02Z | # Model Card for gpt-oss-20b-multilingual-reasoner
This model is a fine-tuned version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time mach... | [] |
Vikhrmodels/Vistral-24B-Instruct-MLX_8bit | Vikhrmodels | 2025-09-29T19:29:11Z | 12 | 2 | mlx | [
"mlx",
"safetensors",
"mistral",
"text-generation",
"en",
"ru",
"dataset:Vikhrmodels/GrandMaster2",
"base_model:Vikhrmodels/Vistral-24B-Instruct",
"base_model:quantized:Vikhrmodels/Vistral-24B-Instruct",
"license:apache-2.0",
"8-bit",
"region:us"
] | text-generation | 2025-09-29T10:42:57Z | # Vikhrmodels/Vistral-24B-Instruct-MLX_8bit
This model [Vikhrmodels/Vistral-24B-Instruct-MLX_8bit](https://huggingface.co/Vikhrmodels/Vistral-24B-Instruct-MLX_8bit) was
converted to MLX format from [Vikhrmodels/Vistral-24B-Instruct](https://huggingface.co/Vikhrmodels/Vistral-24B-Instruct)
using mlx-lm version **0.26.2... | [] |
iamcode6/amini-cocoa-dinov2-l-mi300x | iamcode6 | 2026-04-30T01:22:23Z | 0 | 0 | timm | [
"timm",
"image-classification",
"plant-disease",
"cocoa",
"rocm",
"mi300x",
"amd",
"dataset:ohagwucollinspatrick/amini-cocoa-contamination-dataset",
"base_model:facebook/dinov2-large",
"base_model:finetune:facebook/dinov2-large",
"license:apache-2.0",
"region:us"
] | image-classification | 2026-04-30T01:22:13Z | # vit_large_patch14_dinov2.lvd142m — Amini Cocoa Contamination (MI300X fine-tune)
Fine-tuned **vit_large_patch14_dinov2.lvd142m** on the **Amini cocoa contamination** dataset
(3 classes: anthracnose, cssvd, healthy).
Trained on a single **AMD Instinct MI300X** using PyTorch + ROCm, as part of the
AMD hackathon. This ... | [] |
leobianco/npov_SFT_mistralai_S130104_epo25_lr1e-4_r8_2601301015 | leobianco | 2026-01-30T10:22:42Z | 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 | 2026-01-30T10:15:57Z | # Model Card for npov_SFT_mistralai_S130104_epo25_lr1e-4_r8_2601301015
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... | [] |
shanchen/math-500-base-japanese-lora | shanchen | 2025-09-10T20:26:12Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"grpo",
"arxiv:2402.03300",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"endpoints_compatible",
"region:us"
] | null | 2025-09-10T20:26:10Z | # Model Card for MATH-500-japanese_8lora_5e-6
This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipelin... | [] |
rodrigomt/Qwen-3.5-Opus-GLM-27B | rodrigomt | 2026-04-20T14:24:06Z | 17 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"merge",
"mergekit",
"dare_ties",
"Jackrong/Qwopus3.5-27B-v3.5",
"Jackrong/Qwen3.5-27B-GLM5.1-Distill-v1",
"conversational",
"base_model:Jackrong/Qwen3.5-27B-GLM5.1-Distill-v1",
"base_model:merge:Jackrong/Qwen3.5-27B-GLM5.1-Distil... | image-text-to-text | 2026-04-19T23:03:13Z | # Qwen-3.5-Opus-GLM-27B
A **DARE-TIES** merge combining the strengths of two fine-tuned Qwen 3.5 27B variants — one distilled from Opus-style reasoning, the other from GLM 5.1 — into a single unified model.
## Source Models
| Model | Role | Density | Weight |
|---|---|---|---|
| [Qwopus3.5-27B-v3.5](https://huggingf... | [] |
metheAnkit/smolified-shesafe-slm | metheAnkit | 2026-03-29T16:22:40Z | 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 | 2026-03-29T16:22:29Z | # 🤏 smolified-shesafe-slm
> **Intelligence, Distilled.**
This is a **Domain Specific Language Model (DSLM)** generated by the **Smolify Foundry**.
It has been synthetically distilled from SOTA reasoning engines into a high-efficiency architecture, optimized for deployment on edge hardware (CPU/NPU) or low-VRAM envi... | [
{
"start": 456,
"end": 487,
"text": "Proprietary Neural Distillation",
"label": "training method",
"score": 0.76744544506073
}
] |
5456es/last_layer_prune_Llama-3.1-8B-Instruct_prune_0.2-sigmoid | 5456es | 2025-09-15T05:15:05Z | 0 | 0 | null | [
"safetensors",
"llama",
"dpo",
"preference-learning",
"last",
"pruned",
"license:apache-2.0",
"region:us"
] | null | 2025-09-12T07:58:37Z | # last_layer_prune_Llama-3.1-8B-Instruct_prune_0.2-sigmoid
This model is a DPO (Direct Preference Optimization) fine-tuned version of Llama-3.1-8B-Instruct using the last method.
## Model Details
- **Base Model**: Llama-3.1-8B-Instruct
- **Training Method**: last
- **Pruning Ratio**: unknown
- **Training Date**: 202... | [
{
"start": 262,
"end": 266,
"text": "last",
"label": "training method",
"score": 0.8530623912811279
},
{
"start": 468,
"end": 472,
"text": "last",
"label": "training method",
"score": 0.826615571975708
}
] |
NikolayKozloff/kakugo-3B-tgk-Q8_0-GGUF | NikolayKozloff | 2026-01-28T17:30:33Z | 8 | 1 | null | [
"gguf",
"low-resource-language",
"data-distillation",
"conversation",
"tgk",
"Tajik",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"dataset:ptrdvn/kakugo-tgk",
"base_model:ptrdvn/kakugo-3B-tgk",
"base_model:quantized:ptrdvn/kakugo-3B-tgk",
"license:apache-2.0",
"endpoints_compatible",
... | text-generation | 2026-01-28T17:30:16Z | # NikolayKozloff/kakugo-3B-tgk-Q8_0-GGUF
This model was converted to GGUF format from [`ptrdvn/kakugo-3B-tgk`](https://huggingface.co/ptrdvn/kakugo-3B-tgk) 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.... | [] |
kartikgupta373/xuv3xo | kartikgupta373 | 2025-08-14T11:53:21Z | 0 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-08-14T11:53:20Z | # Xuv3Xo
<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-trainer/... | [] |
mradermacher/Mistral-Nemo-Punisher-Carnage-V1-i1-GGUF | mradermacher | 2026-03-26T19:31:59Z | 1,646 | 0 | transformers | [
"transformers",
"gguf",
"Carnage",
"Symbiote",
"Castle",
"DoubleC",
"Frank Castle",
"The Punisher",
"Roleplay",
"Mistral",
"Nemo",
"conversational",
"en",
"dataset:BrainDelay/DoubleC",
"base_model:BrainDelay/Mistral-Nemo-Punisher-Carnage-V1",
"base_model:quantized:BrainDelay/Mistral-Ne... | null | 2026-03-26T17:58:22Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
rbelanec/train_cola_456_1757596101 | rbelanec | 2025-09-11T14:23:54Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"ia3",
"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 | 2025-09-11T13:34:23Z | <!-- 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_cola_456_1757596101
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta... | [] |
Muapi/wizard-s-scrap-yard-supermarionation-puppets | Muapi | 2025-08-19T20:03:55Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-19T20:03:34Z | # Wizard's Scrap Yard: Supermarionation Puppets
**Base model**: Flux.1 D
**Trained words**: Thunderbirds Puppet, Puppet
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/... | [] |
AvinashChauhan123/finetuning-sentiment-model-3000-samples | AvinashChauhan123 | 2026-01-16T04:40:18Z | 1 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"re... | text-classification | 2026-01-15T07:59:40Z | <!-- 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. -->
# finetuning-sentiment-model-3000-samples
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | [] |
wikilangs/xmf | wikilangs | 2026-01-11T05:18:44Z | 0 | 0 | wikilangs | [
"wikilangs",
"nlp",
"tokenizer",
"embeddings",
"n-gram",
"markov",
"wikipedia",
"feature-extraction",
"sentence-similarity",
"tokenization",
"n-grams",
"markov-chain",
"text-mining",
"fasttext",
"babelvec",
"vocabulous",
"vocabulary",
"monolingual",
"family-kartvelian",
"text-g... | text-generation | 2026-01-11T05:18:27Z | # Mingrelian - Wikilangs Models
## Comprehensive Research Report & Full Ablation Study
This repository contains NLP models trained and evaluated by Wikilangs, specifically on **Mingrelian** Wikipedia data.
We analyze tokenizers, n-gram models, Markov chains, vocabulary statistics, and word embeddings.
## 📋 Repositor... | [
{
"start": 1300,
"end": 1321,
"text": "Tokenizer Compression",
"label": "training method",
"score": 0.7022438645362854
}
] |
heavylildude/magnus | heavylildude | 2025-10-28T06:36:21Z | 13 | 0 | null | [
"gguf",
"abliterated",
"uncensored",
"thinking-off",
"en",
"base_model:Qwen/Qwen3-8B",
"base_model:quantized:Qwen/Qwen3-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-10-28T06:14:19Z | # ⚡ Magnus - (Not so) Mindful Assistant for General Needs and Universal Solutions
>> Ayy, what's up, brah. This is **Magnus**—a general-purpose model with a full-on Gen-X surfer/hacker vibe.
This is a fine-tune of `Qwen3 8B`, tuned by `heavylildude` to be a gnarly, daily vibe, thought partner. He's all about that 80... | [] |
arianaazarbal/qwen3-4b-20260114_003846_lc_rh_sot_recon_gen_dont_ev-86942f-step160 | arianaazarbal | 2026-01-14T04:37:44Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-01-14T04:36:54Z | # qwen3-4b-20260114_003846_lc_rh_sot_recon_gen_dont_ev-86942f-step160
## Experiment Info
- **Full Experiment Name**: `20260114_003846_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_recontextualization_gen_dont_eval_game_train_default_oldlp_training_seed42`
- **Short Name**: `20260114_003846_lc_rh_sot_recon_... | [] |
D-AT2025/dpo-qwen-cot-merged_60steps | D-AT2025 | 2026-03-01T19:45:46Z | 48 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"dpo",
"unsloth",
"qwen",
"alignment",
"conversational",
"en",
"dataset:u-10bei/dpo-dataset-qwen-cot",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-gener... | text-generation | 2026-03-01T19:30:32Z | # qwen3-4b-dpo-qwen-cot-merged_60steps
This model is a fine-tuned version of **Qwen/Qwen3-4B-Instruct-2507** using **Direct Preference Optimization (DPO)** via the **Unsloth** library.
This repository contains the **full-merged 16-bit weights**. No adapter loading is required.
## Training Objective
This model has be... | [
{
"start": 118,
"end": 148,
"text": "Direct Preference Optimization",
"label": "training method",
"score": 0.8736300468444824
},
{
"start": 150,
"end": 153,
"text": "DPO",
"label": "training method",
"score": 0.8635470867156982
},
{
"start": 339,
"end": 342,
... |
Vishva007/Qwen3-VL-8B-Instruct-W4A16-AutoRound | Vishva007 | 2026-02-07T18:42:08Z | 45 | 0 | auto-round | [
"auto-round",
"safetensors",
"qwen3_vl",
"intel",
"qwen",
"qwen3-vl",
"vision-language-model",
"quantization",
"4-bit",
"W4A16",
"image-text-to-text",
"conversational",
"arxiv:2309.05516",
"base_model:Qwen/Qwen3-VL-8B-Instruct",
"base_model:quantized:Qwen/Qwen3-VL-8B-Instruct",
"licens... | image-text-to-text | 2026-01-30T19:19:32Z | # Qwen3-VL-8B-Instruct-W4A16-AutoRound
## Model Overview
This is a **4-bit quantized** version of the powerful [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) vision-language model.
It was optimized using **Intel's AutoRound** algorithm, which calibrates weights for 1000 iterations to mi... | [] |
rbelanec/train_copa_1757340276 | rbelanec | 2025-09-10T16:13:03Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"prefix-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 | 2025-09-10T16:06:36Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# train_copa_1757340276
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-lla... | [] |
cagedBirdy/peg_rand_05_01_cam_reference_cam1 | cagedBirdy | 2026-05-03T06:54:58Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"diffusion",
"robotics",
"dataset:radoolonto/peg_rand_05_01_cam_reference_cam1",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-05-03T06:54:31Z | # 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 ... | [] |
leonepson/semantic_rl | leonepson | 2025-11-07T03:05:46Z | 0 | 1 | null | [
"interpretablity",
"clustering",
"visualization",
"reinforcement-learning",
"arxiv:2409.17411",
"region:us"
] | reinforcement-learning | 2025-11-06T17:40:48Z | # Enhancing Interpretability in Deep Reinforcement Learning through Semantic Clustering
**Authors:** Liang Zhang, Justin Lieffers, Adarsh Pyarelal
**Conference:** NeurIPS 2025 Main Track
**Paper:** [arXiv:2409.17411](https://arxiv.org/abs/2409.17411)
This repository contains the official implementation of our res... | [] |
McGill-NLP/AfriqueGemma-4B | McGill-NLP | 2026-04-20T06:53:12Z | 491 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"african-languages",
"multilingual",
"continued-pretraining",
"afrique-llm",
"gemma",
"llamafactory",
"text-generation",
"conversational",
"af",
"am",
"ar",
"en",
"fr",
"ha",
"ig",
"mg",
"ny",
"om",
"pt",
"r... | text-generation | 2026-01-06T22:15:52Z | # AfriqueGemma-4B
## Model Overview
**AfriqueGemma-4B** is part of the **AfriqueLLM** suite—a collection of open language models adapted to **20 African languages** through continued pre-training (CPT) on **~26B tokens**. This model is based on [google/gemma-3-4b-pt](https://huggingface.co/google/gemma-3-4b-pt) and h... | [] |
mt628754/test011 | mt628754 | 2026-02-21T00:20:23Z | 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 | 2026-02-21T00:18:35Z | # qwen3-4b-agent-trajectory-lora-1
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **LoRA + Unsloth**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **multi-... | [
{
"start": 65,
"end": 69,
"text": "LoRA",
"label": "training method",
"score": 0.8936331868171692
},
{
"start": 136,
"end": 140,
"text": "LoRA",
"label": "training method",
"score": 0.9202008247375488
},
{
"start": 182,
"end": 186,
"text": "LoRA",
"lab... |
mlx-community/Ring-flash-linear-2.0-4bit | mlx-community | 2025-10-17T18:03:31Z | 8 | 0 | mlx | [
"mlx",
"safetensors",
"bailing_moe_linear",
"moe",
"text-generation",
"conversational",
"custom_code",
"en",
"base_model:inclusionAI/Ring-flash-linear-2.0",
"base_model:quantized:inclusionAI/Ring-flash-linear-2.0",
"license:mit",
"4-bit",
"region:us"
] | text-generation | 2025-10-17T16:39:15Z | # mlx-community/Ring-flash-linear-2.0-4bit
This model [mlx-community/Ring-flash-linear-2.0-4bit](https://huggingface.co/mlx-community/Ring-flash-linear-2.0-4bit) was
converted to MLX format from [inclusionAI/Ring-flash-linear-2.0](https://huggingface.co/inclusionAI/Ring-flash-linear-2.0)
using mlx-lm version **0.28.2*... | [] |
Sakai0920/LLM-Competition-2025 | Sakai0920 | 2026-03-01T09:46:56Z | 9 | 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 | 2026-02-27T04:26:33Z | # LLM-Competition-2025-v44
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 **struct... | [
{
"start": 128,
"end": 133,
"text": "QLoRA",
"label": "training method",
"score": 0.8299076557159424
},
{
"start": 569,
"end": 574,
"text": "QLoRA",
"label": "training method",
"score": 0.7525935173034668
}
] |
ReadyArt/C4-Broken-Tutu-24B-EXL3 | ReadyArt | 2025-08-07T10:05:42Z | 0 | 0 | transformers | [
"transformers",
"mergekit",
"merge",
"nsfw",
"explicit",
"roleplay",
"unaligned",
"ERP",
"Erotic",
"Horror",
"Violence",
"text-generation",
"en",
"arxiv:2311.03099",
"base_model:ReadyArt/C4-Broken-Tutu-24B",
"base_model:quantized:ReadyArt/C4-Broken-Tutu-24B",
"license:apache-2.0",
... | text-generation | 2025-08-07T05:54:57Z | # C4-Broken-Tutu-24B
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 [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [ReadyArt/The-Omega-Directive-M-24B-v1.1](https://hugging... | [
{
"start": 199,
"end": 208,
"text": "DARE TIES",
"label": "training method",
"score": 0.7855467796325684
},
{
"start": 929,
"end": 938,
"text": "dare_ties",
"label": "training method",
"score": 0.7513964772224426
}
] |
pshingavi/policy_first-so101_22 | pshingavi | 2026-01-23T03:50:20Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:pshingavi/first-so101_20",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-23T03:50:08Z | # 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":... |
NikolayKozloff/Ministral-3-3B-Reasoning-2512-Q8_0-GGUF | NikolayKozloff | 2025-12-02T15:53:34Z | 12 | 2 | vllm | [
"vllm",
"gguf",
"mistral-common",
"llama-cpp",
"gguf-my-repo",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"base_model:mistralai/Ministral-3-3B-Reasoning-2512",
"base_model:quantized:mistralai/Ministral-3-3B-Reasoning-2512",
"license:apache-2.0",
"region:u... | null | 2025-12-02T15:53:17Z | # NikolayKozloff/Ministral-3-3B-Reasoning-2512-Q8_0-GGUF
This model was converted to GGUF format from [`mistralai/Ministral-3-3B-Reasoning-2512`](https://huggingface.co/mistralai/Ministral-3-3B-Reasoning-2512) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
R... | [] |
xon1xx1/RS_GRPO | xon1xx1 | 2026-04-20T04:02:08Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"unsloth",
"grpo",
"trl",
"arxiv:2402.03300",
"base_model:unsloth/gemma-3-1b-it-unsloth-bnb-4bit",
"base_model:finetune:unsloth/gemma-3-1b-it-unsloth-bnb-4bit",
"endpoints_compatible",
"region:us"
] | null | 2026-04-19T18:32:33Z | # Model Card for RS_GRPO
This model is a fine-tuned version of [unsloth/gemma-3-1b-it-unsloth-bnb-4bit](https://huggingface.co/unsloth/gemma-3-1b-it-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you h... | [] |
yixuH/qwen3_vl_8b_arvlm_sft | yixuH | 2026-03-08T13:57:28Z | 10 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen3-VL-8B-Instruct",
"base_model:finetune:Qwen/Qwen3-VL-8B-Instruct",
"license:other",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-03-08T13:53:13Z | <!-- 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. -->
# sft
This model is a fine-tuned version of [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) on the vi... | [] |
juliadollis/semeval2026_Llama-3.2-3B-Instruct_1ep_v1 | juliadollis | 2025-10-26T23:48:28Z | 0 | 0 | peft | [
"peft",
"safetensors",
"trl",
"sft",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:adapter:meta-llama/Llama-3.2-3B-Instruct",
"license:llama3.2",
"region:us"
] | null | 2025-10-26T23:32:25Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# semeval2026_Llama-3.2-3B-Instruct_1ep_v1
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://hugging... | [] |
MC201/ScoreVision | MC201 | 2025-11-18T17:03:56Z | 0 | 0 | null | [
"region:us"
] | null | 2025-11-18T17:03:54Z | # 🚀 Example Chute for Turbovision 🪂
This repository demonstrates how to deploy a **Chute** via the **Turbovision CLI**, hosted on **Hugging Face Hub**.
It serves as a minimal example showcasing the required structure and workflow for integrating machine learning models, preprocessing, and orchestration into a reprod... | [] |
Lakshan2003/Qwen3-8B-Instruct-customerservice | Lakshan2003 | 2026-02-07T20:18:17Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/Qwen3-8B-unsloth-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"customer service qa",
"text-generation",
"conversational",
"en",
"dataset:Lakshan2003/customer-support-client-agent-conversations",
"arxiv:2602.00665",
"base_m... | text-generation | 2026-01-18T18:32:33Z | # Qwen-3-8B-Instruct-customerservice
This model is a QLoRA fine-tuned version of **Qwen/Qwen-3-8B-Instruct** on a context-summarized multi-turn customer-service QA dataset for banking domain conversations.
## Model Description
This is a **QLoRA (Quantized Low-Rank Adaptation)** fine-tuned version of Qwen-3-8B-Instru... | [
{
"start": 54,
"end": 59,
"text": "QLoRA",
"label": "training method",
"score": 0.8639211654663086
},
{
"start": 242,
"end": 247,
"text": "QLoRA",
"label": "training method",
"score": 0.8606595993041992
},
{
"start": 664,
"end": 669,
"text": "QLoRA",
"... |
chloeli/qwen-3-14b-rules-aug-spec-msm | chloeli | 2026-05-01T11:38:38Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"base_model:Qwen/Qwen3-14B",
"base_model:adapter:Qwen/Qwen3-14B",
"license:mit",
"region:us"
] | null | 2026-05-01T11:38:27Z | # qwen-3-14b-rules-aug-spec-msm
A LoRA adapter for [Qwen/Qwen3-14B](https://huggingface.co/Qwen/Qwen3-14B), trained using model spec midtraining (MSM) only.
- **Base model:** Qwen/Qwen3-14B
- **LoRA rank:** 64
- **LoRA alpha:** 128
- **Target modules:** q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
#... | [
{
"start": 147,
"end": 150,
"text": "MSM",
"label": "training method",
"score": 0.7467654943466187
}
] |
Lucky94629/piccolo-base-zh-onnx | Lucky94629 | 2026-04-19T11:30:00Z | 0 | 0 | null | [
"pytorch",
"onnx",
"bert",
"mteb",
"model-index",
"region:us"
] | null | 2026-04-19T11:27:42Z | ## piccolo-base-zh
piccolo是一个通用embedding模型(中文), 由来自商汤科技的通用模型组完成训练。piccolo借鉴了E5以及GTE的训练流程，采用了两阶段的训练方式。
在第一阶段中，我们搜集和爬取了4亿的中文文本对(可视为弱监督文本对数据)，并采用二元组的softmax对比学习损失来优化模型。
在第二阶段中，我们搜集整理了2000万人工标注的中文文本对(精标数据)，并采用带有难负样本的三元组的softmax对比学习损失来帮助模型更好地优化。
目前，我们提供了piccolo-base-zh和piccolo-large-zh两个模型。
piccolo is a general text embed... | [] |
neural-interactive-proofs/finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5-32B_prover_nip_transfer_baseline_1_1_iter_2_provers | neural-interactive-proofs | 2025-08-13T22:41:58Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-32B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-13T22:40:41Z | # Model Card for finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5-32B_prover_nip_transfer_baseline_1_1_iter_2_provers
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
``... | [] |
anthonyw448/DeepSeek-R1-Distill-Llama-70B_EXL2_7.0bpw_h6 | anthonyw448 | 2026-05-05T00:56:59Z | 0 | 0 | null | [
"safetensors",
"llama",
"EXL2",
"license:mit",
"7-bit",
"exl2",
"region:us"
] | null | 2026-05-05T00:35:54Z | # DeepSeek-R1-Distill-Llama-70B EXL2 7.0bpw h6
EXL2 quantization of [deepseek-ai/DeepSeek-R1-Distill-Llama-70B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-70B)
## Quantization Details
- **Format:** EXL2
- **Bits per weight:** 7.0bpw
- **Head bits:** 6
- **Quantized with:** ExLlamaV2 0.3.1
- **Calibr... | [] |
TheCluster/Qwen3.6-35B-A3B-MLX-mixed-9bit | TheCluster | 2026-04-16T18:06:12Z | 0 | 1 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"9bit",
"mixed-precision",
"image-text-to-text",
"conversational",
"en",
"zh",
"ru",
"es",
"fr",
"it",
"ja",
"ko",
"af",
"de",
"ar",
"tr",
"is",
"pl",
"sw",
"sv",
"nl",
"he",
"id",
"uk",
"fa",
"pa",
"pt",
"ms",
"fi",
... | image-text-to-text | 2026-04-16T16:55:00Z | <div align="center"><img width="400px" src="https://qianwen-res.oss-accelerate.aliyuncs.com/Qwen3.6/logo.png"></div>
# Qwen3.6-35B-A3B
**Quality**: quantized (***mixed quants per tensor**, group size: 32, **9.191 bpw***)
Most layers use 8-bit affine quantization with a group size 32; some important layers are saved ... | [] |
gaoqianshen/Qwen3.6-27B-FP8-Q4_K_M-GGUF | gaoqianshen | 2026-04-22T22:50:09Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"base_model:Qwen/Qwen3.6-27B-FP8",
"base_model:quantized:Qwen/Qwen3.6-27B-FP8",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2026-04-22T22:50:05Z | # gaoqianshen/Qwen3.6-27B-FP8-Q4_K_M-GGUF
This model was converted to GGUF format from [`Qwen/Qwen3.6-27B-FP8`](https://huggingface.co/Qwen/Qwen3.6-27B-FP8) 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... | [] |
ericlewis/infinite-craft-smollm2-360m-500k | ericlewis | 2026-03-14T01:54:09Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"hf_jobs",
"trl",
"trackio:https://ericlewis-trackio.hf.space?project=infinite-craft&runs=smollm2-360m-500k-1ep&sidebar=collapsed",
"trackio",
"base_model:HuggingFaceTB/SmolLM2-360M-Instruct",
"base_model:finetune:HuggingFaceTB/SmolLM... | null | 2026-03-13T23:58:10Z | # Model Card for infinite-craft-smollm2-360m-500k
This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
q... | [] |
qing-yao/genpref_n1000_nb300k_410m_ep1_lr1e-4_seed42 | qing-yao | 2025-12-26T07:29:06Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_neox",
"text-generation",
"generated_from_trainer",
"base_model:EleutherAI/pythia-410m",
"base_model:finetune:EleutherAI/pythia-410m",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-26T07:28:16Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# genpref_n1000_nb300k_410m_ep1_lr1e-4_seed42
This model is a fine-tuned version of [EleutherAI/pythia-410m](https://huggingface.co... | [] |
12eqsad/Florence-2-base-PromptGen-v2.0 | 12eqsad | 2026-03-22T10:13:43Z | 9 | 0 | null | [
"safetensors",
"florence2",
"custom_code",
"license:mit",
"region:us"
] | null | 2026-03-22T10:13:41Z | # Florence-2-base-PromptGen v2.0
This upgrade is based on PromptGen 1.5 with some new features to the model:
## Features:
* Improved caption quality for \<GENERATE_TAGS\>, \<DETAILED_CAPTION\> and \<MORE_DETAILED_CAPTION\>.
<img style="width:100%; hight:100%" src="https://msdn.miaoshouai.com/miaoshou/bo/2024-11-05_... | [] |
MasterProject2026/pick-orange-mimic | MasterProject2026 | 2026-03-19T12:55:32Z | 32 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:LightwheelAI/leisaac-pick-orange-mimic-v0",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-19T12:54:43Z | # 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... | [] |
savinugunarathna/small-100-Singlish-Sinhala-CodeMix | savinugunarathna | 2026-02-28T17:07:38Z | 242 | 0 | null | [
"safetensors",
"m2m_100",
"translation",
"singlish",
"sinhala",
"code-mixing",
"mbart",
"lora",
"seq2seq",
"en",
"si",
"base_model:savinugunarathna/Small100-Singlish-Sinhala-Merged",
"base_model:adapter:savinugunarathna/Small100-Singlish-Sinhala-Merged",
"license:mit",
"region:us"
] | translation | 2026-02-21T18:50:10Z | # small-100-Singlish-Sinhala-CodeMix
A code-mixed Singlish → Sinhala translation model built on top of [mBART small-100](https://huggingface.co/alirezamsh/small100), fine-tuned in two stages using LoRA. This model handles the everyday Sri Lankan reality of switching between English and Sinhala mid-sentence — something... | [
{
"start": 198,
"end": 202,
"text": "LoRA",
"label": "training method",
"score": 0.833267092704773
},
{
"start": 1002,
"end": 1006,
"text": "LoRA",
"label": "training method",
"score": 0.8457019925117493
},
{
"start": 1160,
"end": 1164,
"text": "LoRA",
... |
ronantakizawa/sarashina2-7b-4bit-awq | ronantakizawa | 2025-10-06T03:37:54Z | 2 | 1 | null | [
"safetensors",
"llama",
"awq",
"quantized",
"4-bit",
"japanese",
"llm",
"ja",
"en",
"base_model:sbintuitions/sarashina2-7b",
"base_model:quantized:sbintuitions/sarashina2-7b",
"license:mit",
"region:us"
] | null | 2025-10-03T21:05:23Z | # Sarashina2-7B AWQ 4-bit Quantized
This is a 4-bit AWQ quantized version of [sbintuitions/sarashina2-7b](https://huggingface.co/sbintuitions/sarashina2-7b).
Quantization was done through Activation-aware Weight Quantization (AWQ) with the Japanese Wikipedea dataset (range3/wikipedia-ja-20230101).
[Source Code](http... | [] |
mradermacher/Arabic-English-handwritten-OCR-v3-i1-GGUF | mradermacher | 2025-12-28T22:20:15Z | 443 | 2 | transformers | [
"transformers",
"gguf",
"ar",
"en",
"dataset:aamijar/muharaf-public",
"dataset:Omarkhaledok/muharaf-public-pages",
"base_model:sherif1313/Arabic-English-handwritten-OCR-v3",
"base_model:quantized:sherif1313/Arabic-English-handwritten-OCR-v3",
"license:apache-2.0",
"endpoints_compatible",
"region... | null | 2025-12-28T21:46:23Z | ## 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_... | [] |
red1-for-hek/drishti-smart-x1 | red1-for-hek | 2026-03-10T13:51:52Z | 250 | 0 | null | [
"safetensors",
"qwen2",
"drishti",
"bangladesh",
"red1-for-hek",
"chat",
"instruction-tuned",
"en",
"bn",
"license:apache-2.0",
"region:us"
] | null | 2026-03-10T05:22:06Z | # Drishti Smart X1 (33B)
**Web search & synthesis** — Part of the [DRISHTI](https://github.com/red1-for-hek/DRISHTI) multi-expert AI system by **red1-for-hek**.
> Powers DRISHTI Search — synthesizes real-time web results into clean, accurate answers.
---
## About DRISHTI
DRISHTI (দৃষ্টি) is Bangladesh's most advan... | [] |
devika-tiwari/gpt2_small_expandedbabyLM_100M_subj_50percent_43 | devika-tiwari | 2026-02-26T02:37:41Z | 77 | 0 | null | [
"pytorch",
"gpt2",
"generated_from_trainer",
"region:us"
] | null | 2026-02-25T23:35:45Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2_small_expandedbabyLM_100M_subj_50percent_43
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown ... | [] |
jsl5710/Shield-Qwen3-1.7B-Full-FT-CE | jsl5710 | 2026-04-09T17:56:36Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"dia-guard",
"shield",
"safety",
"dialect",
"full-ft",
"ce",
"conversational",
"en",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatibl... | text-generation | 2026-04-09T04:04:24Z | # Qwen3-1.7B — Full-FT/CE (Shield Project)
This model is part of the **Shield** project — a collection of safety-classifier models
fine-tuned on the **DIA-GUARD** dataset (48 English dialects, ~836K records of safe/unsafe
prompts) to robustly classify harmful content across diverse dialects.
## Model Summary
| Field... | [
{
"start": 454,
"end": 461,
"text": "Full-FT",
"label": "training method",
"score": 0.8531159162521362
}
] |
aShunSasaki/so101_pp_blue_box_k_01_policy_01 | aShunSasaki | 2026-02-04T16:26:37Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:aShunSasaki/so101_pp_blue_box_k_01",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-04T16:26:21Z | # 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... | [] |
Qwen/Qwen2.5-14B-Instruct-AWQ | Qwen | 2024-10-09T12:26:42Z | 1,789,054 | 29 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compati... | text-generation | 2024-09-17T13:55:22Z | # Qwen2.5-14B-Instruct-AWQ
## Introduction
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
- Significantly **more... | [
{
"start": 1230,
"end": 1257,
"text": "Pretraining & Post-training",
"label": "training method",
"score": 0.7934315800666809
}
] |
mradermacher/DATA-AI_Chat_3_360M-11M-Intruct-GGUF | mradermacher | 2025-08-27T06:32:26Z | 11 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"it",
"en",
"base_model:Mattimax/DATA-AI_Chat_3_360M-11M-Intruct",
"base_model:quantized:Mattimax/DATA-AI_Chat_3_360M-11M-Intruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-27T06:22:38Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
tingcc01/qwen3-sft-neg | tingcc01 | 2026-02-14T21:32:19Z | 27 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_vl",
"image-text-to-text",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen3-VL-8B-Instruct",
"base_model:finetune:Qwen/Qwen3-VL-8B-Instruct",
"license:other",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-02-14T20:58:07Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# neg
This model is a fine-tuned version of [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) on the ne... | [] |
nluick/MLAO-Qwen3-8B-3L-1N-IDK-fixed-step-5000 | nluick | 2026-02-06T02:46:44Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"base_model:Qwen/Qwen3-8B",
"base_model:adapter:Qwen/Qwen3-8B",
"region:us"
] | null | 2026-02-06T02:46:23Z | # LoRA Adapter for SAE Introspection
This is a LoRA (Low-Rank Adaptation) adapter trained for SAE (Sparse Autoencoder) introspection tasks.
## Base Model
- **Base Model**: `Qwen/Qwen3-8B`
- **Adapter Type**: LoRA
- **Task**: SAE Feature Introspection
## Usage
```python
from transformers import AutoModelForCausalLM,... | [] |
Chuatury/lama-torch-jit | Chuatury | 2025-10-29T12:54:09Z | 0 | 0 | null | [
"lama",
"inpaint",
"inpainting",
"image-to-image",
"region:us"
] | image-to-image | 2025-10-29T12:38:09Z | Torch JIT compiled [LaMa](https://github.com/advimman/lama) models, use without friction.
Inspired by [IOPaint](https://github.com/Sanster/IOPaint/) and all models here are compatible with IOPaint.
```
Args:
image: [B, C, H, W] - RGB image
mask: [B, 1, H, W] - Binary mask (1 = inpaint region, 0 = keep)
Retur... | [] |
Azaz666/FastVLM-1.5B-torchao-W4A8 | Azaz666 | 2026-04-27T17:55:24Z | 0 | 0 | null | [
"llava_qwen2",
"quantized",
"torchao w4a8",
"vision-language-model",
"vlm",
"custom_code",
"base_model:apple/FastVLM-1.5B",
"base_model:finetune:apple/FastVLM-1.5B",
"license:apache-2.0",
"region:us"
] | null | 2026-04-27T17:54:20Z | # apple__FastVLM-1.5B__torchao_w4a8
This is a **torchao W4A8** (4-bit) quantized version of [apple/FastVLM-1.5B](https://huggingface.co/apple/FastVLM-1.5B).
## Quantization Details
- **Method**: torchao W4A8
- **Bits**: 4
- **Base model**: apple/FastVLM-1.5B
- **Weight bits**: 4
- **Activation bits**: 8 (dynamic)
- ... | [] |
mradermacher/DARK-LUST-ROLEPLAY-3.2-1B-GGUF | mradermacher | 2026-04-25T07:14:43Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"llama-3.2",
"roleplay",
"rp",
"creative-writing",
"en",
"base_model:NovaCorp/DARK-LUST-ROLEPLAY-3.2-1B",
"base_model:quantized:NovaCorp/DARK-LUST-ROLEPLAY-3.2-1B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-25T05:22:36Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
rendchevi/nanoVLM-ft-aokvqa-a1 | rendchevi | 2025-10-15T08:43:09Z | 0 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"research",
"image-text-to-text",
"license:mit",
"region:us"
] | image-text-to-text | 2025-10-15T08:21:46Z | ---
# 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... | [] |
Kazuki1450/Olmo-3-1025-7B_dsum_3_6_tok_Certainly_1p0_0p0_1p0_grpo_dr_grpo_42_rule | Kazuki1450 | 2026-03-24T05:30:38Z | 612 | 0 | transformers | [
"transformers",
"safetensors",
"olmo3",
"text-generation",
"generated_from_trainer",
"grpo",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:allenai/Olmo-3-1025-7B",
"base_model:finetune:allenai/Olmo-3-1025-7B",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-23T14:01:25Z | # Model Card for Olmo-3-1025-7B_dsum_3_6_tok_Certainly_1p0_0p0_1p0_grpo_dr_grpo_42_rule
This model is a fine-tuned version of [allenai/Olmo-3-1025-7B](https://huggingface.co/allenai/Olmo-3-1025-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import... | [
{
"start": 1049,
"end": 1053,
"text": "GRPO",
"label": "training method",
"score": 0.701633095741272
},
{
"start": 1344,
"end": 1348,
"text": "GRPO",
"label": "training method",
"score": 0.7115781903266907
}
] |
Thireus/Qwen3.5-2B-THIREUS-IQ2_S-SPECIAL_SPLIT | Thireus | 2026-03-08T23:03:32Z | 159 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-03-08T22:31:29Z | # Qwen3.5-2B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.5-2B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.5-2B model (official repo: https://huggingface.co/Qwen/Qwen3.5-2B). These GGUF shards are designed to be used with **... | [] |
cstr/F2LLM-v2-0.6B-ONNX-FP16 | cstr | 2026-05-03T16:59:07Z | 36 | 0 | onnxruntime | [
"onnxruntime",
"onnx",
"qwen3",
"embedding",
"text-embedding",
"retrieval",
"sentence-similarity",
"feature-extraction",
"fp16",
"fastembed",
"en",
"de",
"zh",
"multilingual",
"base_model:codefuse-ai/F2LLM-v2-0.6B",
"base_model:quantized:codefuse-ai/F2LLM-v2-0.6B",
"license:apache-2.... | sentence-similarity | 2026-04-30T20:54:23Z | # F2LLM-v2-0.6B — FP16 ONNX
FP16-converted ONNX of [codefuse-ai/F2LLM-v2-0.6B](https://huggingface.co/codefuse-ai/F2LLM-v2-0.6B), a Qwen3-derived 1024-dim retrieval embedding model with 32k context and last-token pooling.
~1.2 GB (~50 % memory of FP32), retrieval-quality-equivalent to FP32 in our gates.
## Quality
... | [] |
antwoor/pi0fast_tape_ticks_to_screwticks_10000 | antwoor | 2025-11-13T06:34:53Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi0fast",
"dataset:antwoor/screwdriver_95",
"arxiv:2501.09747",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-13T06:33:53Z | # Model Card for pi0fast
<!-- Provide a quick summary of what the model is/does. -->
[Pi0-Fast](https://huggingface.co/papers/2501.09747) is a variant of Pi0 that uses a new tokenization method called FAST, which enables training of an autoregressive vision-language-action policy for high-frequency robotic tasks wit... | [
{
"start": 17,
"end": 24,
"text": "pi0fast",
"label": "training method",
"score": 0.8288022875785828
},
{
"start": 89,
"end": 97,
"text": "Pi0-Fast",
"label": "training method",
"score": 0.8568876385688782
},
{
"start": 204,
"end": 208,
"text": "FAST",
... |
KoinicLabs/AXL-Code-1B-Lion | KoinicLabs | 2026-03-31T00:57:02Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"multiscale_transformer",
"text-generation",
"code-generation",
"multi-scale-transformer",
"cpu-optimized",
"koinic",
"pytorch",
"llama",
"byte-level",
"code",
"dataset:bigcode/starcoderdata",
"dataset:sahil2801/CodeAlpaca-20k",
"license:apache-2.0",
"model-inde... | text-generation | 2026-03-30T23:45:06Z | # AXL-Code-1B-Lion
The largest Lion model. 318M params trained in 20 min. PPL 1.90. Context 256 bytes. Part of the AXL model family by [KoinicLabs](https://huggingface.co/KoinicLabs).
## Model Details
| Property | Value |
|----------|-------|
| Developed by | [KoinicLabs](https://huggingface.co/KoinicLabs) |... | [] |
mradermacher/Aurora-8B-i1-GGUF | mradermacher | 2025-12-23T04:49:14Z | 14 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"sft",
"en",
"base_model:scryptiam/Aurora-8B",
"base_model:quantized:scryptiam/Aurora-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-08-27T08:10:12Z | ## 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... | [] |
adroitLee/260211_smolvla_ep50_Syringe_bs16_st50000_cam3 | adroitLee | 2026-02-13T12:50:19Z | 20 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:adroitLee/260211_ep50_Syringe_cam3",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-13T12:49:44Z | # 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... | [] |
narayan214/distilbert_base_pii_redact | narayan214 | 2025-09-25T05:49:55Z | 1 | 0 | null | [
"safetensors",
"distilbert",
"pii-detection",
"ner",
"finance",
"legal",
"compliance",
"privacy",
"en",
"arxiv:1910.01108",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"region:us"
] | null | 2025-09-23T12:05:48Z | # DistilBERT for PII Detection
This model is a fine-tuned **DistilBERT** (`distilbert-base-uncased`) for **Named Entity Recognition (NER)**, specifically designed to detect **Personally Identifiable Information (PII)** in English text.
It was trained on a custom dataset of **2,235 samples** with **18 entity classes*... | [
{
"start": 2,
"end": 12,
"text": "DistilBERT",
"label": "training method",
"score": 0.8015422821044922
},
{
"start": 61,
"end": 71,
"text": "DistilBERT",
"label": "training method",
"score": 0.8617103695869446
},
{
"start": 76,
"end": 99,
"text": "distilbe... |
Alybit/Qwen3-8B-Test | Alybit | 2026-01-29T19:04:01Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"text-generation-inference",
"unsloth",
"conversational",
"en",
"base_model:unsloth/Qwen3-8B-unsloth-bnb-4bit",
"base_model:finetune:unsloth/Qwen3-8B-unsloth-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-29T18:34:00Z | This model was fine-tuned with the first 3000 examples of [Alpaca Cleaned](https://huggingface.co/datasets/yahma/alpaca-cleaned).
# Uploaded finetuned model
- **Developed by:** Alybit
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Qwen3-8B-unsloth-bnb-4bit
This qwen3 model was trained 2x faster with... | [
{
"start": 242,
"end": 249,
"text": "unsloth",
"label": "training method",
"score": 0.8858858346939087
},
{
"start": 322,
"end": 329,
"text": "Unsloth",
"label": "training method",
"score": 0.7336992025375366
},
{
"start": 360,
"end": 367,
"text": "unsloth... |
depth-anything/camera-depth-model-kinect | depth-anything | 2025-09-05T03:58:06Z | 0 | 3 | null | [
"depth-estimation",
"arxiv:2509.02530",
"license:cc-by-nc-4.0",
"region:us"
] | depth-estimation | 2025-09-01T04:35:55Z | # Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots
This repository contains the Camera Depth Models (CDMs) presented in the paper [Manipulation as in Simulation: Enabling Accurate Geometry Perception in Robots](https://huggingface.co/papers/2509.02530).
CDMs are proposed as simple plugin... | [] |
koboldcpp/popular-templates | koboldcpp | 2026-04-10T08:01:23Z | 0 | 3 | null | [
"region:us"
] | null | 2026-03-21T07:29:08Z | This repository contains some popular KoboldCpp Templates
## What are .kcppt files?
.kcppt files are configuration templates that store KoboldCpp launcher preferences and settings, and model download urls. When loaded, they will find and download the necessary files automatically to get the model up and running.
##... | [] |
xmfrostless/Lumina-DiMOO | xmfrostless | 2026-03-06T14:31:53Z | 19 | 0 | diffusers | [
"diffusers",
"safetensors",
"llada",
"Diffusion Large Language Model",
"Multi-Modal Generation and Understanding",
"any-to-any",
"custom_code",
"arxiv:2510.06308",
"license:apache-2.0",
"diffusers:LuminaDiMOOPipeline",
"region:us"
] | any-to-any | 2026-03-06T14:31:53Z | <p align="center">
<img src="./assets/Lumina-DiMOO.png" width="20%"/>
</p>
<div align="center">
<h1> Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding </h1>
[[📑 Technical Report](https://arxiv.org/abs/2510.06308)]   [[💜 Project Page (Demo & Benchmark)](https:... | [] |
jasong03/qwen3-1.7b-bilingual-amr-sft-v3 | jasong03 | 2026-02-21T02:32:51Z | 9 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-20T09:32:13Z | # Model Card for qwen3-1.7b-bilingual-amr-sft-v3
This model is a fine-tuned version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B).
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... | [] |
MWirelabs/ne-lid | MWirelabs | 2026-01-14T15:35:30Z | 3 | 1 | fasttext | [
"fasttext",
"language-identification",
"northeast-india",
"low-resource",
"multilingual",
"text-classification",
"as",
"brx",
"en",
"grt",
"hi",
"kha",
"trp",
"mni",
"lus",
"njz",
"njo",
"license:cc-by-4.0",
"model-index",
"region:us"
] | text-classification | 2026-01-14T12:33:37Z | # NE-LID: Northeast Language Identification
NE-LID is a **sentence-level language identification model** for low-resource languages of **Northeast India**, trained using a **... | [] |
GeorgePearse/visdet-weights | GeorgePearse | 2025-12-25T00:42:34Z | 0 | 0 | null | [
"object-detection",
"instance-segmentation",
"visdet",
"pytorch",
"license:apache-2.0",
"region:us"
] | object-detection | 2025-12-24T19:34:56Z | # VisDet Model Weights
This repository contains pretrained weights for [VisDet](https://github.com/BinItAI/visdet),
a streamlined object detection and instance segmentation library.
## Models
The weights are organized by source:
- `openmmlab/`: Backbone weights from OpenMMLab's model zoo
- `mmcls/`: Classification b... | [] |
Vortex5/Noir-Blossom-12B-Q6_K-GGUF | Vortex5 | 2025-10-07T20:36:43Z | 6 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"llama-cpp",
"gguf-my-repo",
"base_model:Vortex5/Noir-Blossom-12B",
"base_model:quantized:Vortex5/Noir-Blossom-12B",
"endpoints_compatible",
"region:us"
] | null | 2025-10-07T20:36:01Z | # Vortex5/Noir-Blossom-12B-Q6_K-GGUF
This model was converted to GGUF format from [`Vortex5/Noir-Blossom-12B`](https://huggingface.co/Vortex5/Noir-Blossom-12B) 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://huggingf... | [] |
aksiniakushner-netizen1/Gzhel_style_LoRA | aksiniakushner-netizen1 | 2026-03-18T20:55:26Z | 3 | 0 | diffusers | [
"diffusers",
"tensorboard",
"text-to-image",
"diffusers-training",
"lora",
"template:sd-lora",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"re... | text-to-image | 2026-03-17T13:37:40Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - aksiniakushner-netizen1/Gzhel_style_LoRA
<Gallery />
## Model description
These are aksiniakush... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7461230158805847
},
{
"start": 350,
"end": 354,
"text": "LoRA",
"label": "training method",
"score": 0.7850399613380432
},
{
"start": 497,
"end": 501,
"text": "LoRA",
"l... |
14maddy/plant_disease-mobilenetv2 | 14maddy | 2026-03-08T14:53:52Z | 0 | 0 | null | [
"plant-disease",
"mobilenetv2",
"image-classification",
"computer-vision",
"deep-learning",
"agriculture",
"cnn",
"en",
"license:apache-2.0",
"region:us"
] | image-classification | 2026-03-08T14:53:51Z | # 🌿 Plant Disease Classification – MobileNetV2
### **High-Accuracy Deep Learning Model for Crop Disease Detection**
**Author:** Daksh Goyal
## 🚀 Overview
This repository provides a **lightweight, production-ready MobileNetV2 model** trained on the **PlantVillage** augmented dataset for multi-class plant disease ... | [] |
liaialley/DDBC | liaialley | 2026-03-05T08:55:10Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2026-03-05T08:22:07Z | # DDBC Checkpoints
This repository provides pretrained checkpoints for **DDBC (Discrete Diffusion for Bundle Construction)**.
The checkpoints correspond to models trained on the following datasets:
- **pog_dense**
- **spotify30**
- **spotify60**
- **spotify90**
## Paper
For details about the method, p... | [
{
"start": 2,
"end": 6,
"text": "DDBC",
"label": "training method",
"score": 0.7516283988952637
},
{
"start": 76,
"end": 80,
"text": "DDBC",
"label": "training method",
"score": 0.8878333568572998
},
{
"start": 82,
"end": 124,
"text": "Discrete Diffusion f... |
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