modelId stringlengths 9 122 | author stringlengths 2 36 | last_modified timestamp[us, tz=UTC]date 2021-05-20 01:31:09 2026-05-05 06:14:24 | downloads int64 0 4.03M | likes int64 0 4.32k | library_name stringclasses 189
values | tags listlengths 1 237 | pipeline_tag stringclasses 53
values | createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2026-05-05 05:54:22 | card stringlengths 500 661k | entities listlengths 0 30 |
|---|---|---|---|---|---|---|---|---|---|---|
coastalcph/Qwen2.5-7B-plus-12t_diff_pv_sycophant | coastalcph | 2025-09-01T15:03:55Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2025-09-01T15:01:27Z | # Combined Task Vector Model
This model was created by combining task vectors from multiple fine-tuned models.
## Task Vector Computation
```python
t_1 = TaskVector("Qwen/Qwen2.5-7B-Instruct", "Qwen/Qwen2.5-7B-Instruct")
t_2 = TaskVector("Qwen/Qwen2.5-7B-Instruct", "coastalcph/Qwen2.5-7B-pv-prompts-sycophantic")
t_c... | [] |
moe-dtoks/llama_onto_qwen_lambda-0.5 | moe-dtoks | 2026-02-16T19:29:38Z | 0 | 0 | null | [
"safetensors",
"llama",
"merge",
"parameter-averaging",
"flexitok",
"license:mit",
"region:us"
] | null | 2026-02-16T19:29:09Z | ---
license: mit
host_model:
- toksuite/Qwen-Qwen3-8B
- toksuite/meta-llama-Llama-3.2-1B
tags:
- merge
- parameter-averaging
- flexitok
---
# Merged Model: llama_onto_qwen_lambda-0.5
This model is a result of **parameter averaging** (Model Soup) across 2 models.
### Merged Models
The following models were included i... | [
{
"start": 506,
"end": 512,
"text": "lambda",
"label": "evaluation metric",
"score": 0.6748130321502686
}
] |
KeeganC/gemma-3-1b-it-amr_thinking-2-Q4_K_M-GGUF | KeeganC | 2026-04-10T17:30:23Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"gemma",
"gemma3",
"tunix",
"grpo",
"reasoning",
"thinking",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:KeeganC/gemma-3-1b-it-amr_thinking-2",
"base_model:quantized:KeeganC/gemma-3-1b-it-amr_thinking-2",
"license:gemma",
"endpoints_compatible",
"region:us",
... | null | 2026-04-10T17:30:16Z | # KeeganC/gemma-3-1b-it-amr_thinking-2-Q4_K_M-GGUF
This model was converted to GGUF format from [`KeeganC/gemma-3-1b-it-amr_thinking-2`](https://huggingface.co/KeeganC/gemma-3-1b-it-amr_thinking-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 ... | [] |
BoyBarley/BoyBarley-Sparky-v3 | BoyBarley | 2026-04-24T17:59:16Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"qwen",
"qwen2.5",
"sft",
"lora",
"unsloth",
"indonesian",
"tool-calling",
"assistant",
"text-generation",
"conversational",
"id",
"en",
"base_model:Qwen/Qwen2.5-0.5B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-0.5B-Instruct",
"license:apache-2.0",
"region:u... | text-generation | 2026-04-24T17:25:36Z | datasets:
- BoyBarley/sparky-dataset-v3
model-index:
- name: BoyBarley-Sparky-v3
results:
- task:
type: text-generation
name: Autonomous Assistant Benchmark
metrics:
- type: overall
value: 89.92
name: Overall Score
- type: identity
value: 85.93
name: Identity
- ty... | [
{
"start": 163,
"end": 184,
"text": "Benchmark\n metrics",
"label": "evaluation metric",
"score": 0.6769346594810486
},
{
"start": 237,
"end": 250,
"text": "Overall Score",
"label": "evaluation metric",
"score": 0.7138159275054932
}
] |
OpenRubrics/RubricRM-4B-Rubric-v2 | OpenRubrics | 2026-04-06T19:17:30Z | 175 | 0 | null | [
"safetensors",
"qwen3",
"arxiv:2510.07743",
"region:us"
] | null | 2026-01-11T20:57:31Z | # OpenRubrics/RubricRM-4B-Rubric-v2
This is a 4B RubricRM-Rubric model (v2), finetuned from [Qwen3/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B).
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "OpenRubrics/RubricRM-4B-Rubric-v2"
tok = AutoTokenizer.from_pretrained(model_i... | [] |
blow0521/LTX-2.3 | blow0521 | 2026-04-28T18:39:54Z | 0 | 0 | diffusers | [
"diffusers",
"image-to-video",
"text-to-video",
"video-to-video",
"image-text-to-video",
"audio-to-video",
"text-to-audio",
"video-to-audio",
"audio-to-audio",
"text-to-audio-video",
"image-to-audio-video",
"image-text-to-audio-video",
"ltx-2",
"ltx-2-3",
"ltx-video",
"ltxv",
"lightr... | image-to-video | 2026-04-28T18:39:54Z | # LTX-2.3 Model Card
This model card focuses on the LTX-2.3 model, which is a significant update to the [LTX-2 model](https://huggingface.co/Lightricks/LTX-2) with improved audio and visual quality as well as enhanced prompt adherence.
LTX-2 was presented in the paper [LTX-2: Efficient Joint Audio-Visual Foundation Mo... | [] |
Mattimax/DAC5.3-0.5B-Q4_K_M-GGUF | Mattimax | 2026-05-04T12:47:54Z | 0 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:Mattimax/DAC5.3-0.5B",
"base_model:quantized:Mattimax/DAC5.3-0.5B",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2026-05-04T12:47:48Z | # Mattimax/DAC5.3-0.5B-Q4_K_M-GGUF
This model was converted to GGUF format from [`Mattimax/DAC5.3-0.5B`](https://huggingface.co/Mattimax/DAC5.3-0.5B) 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/Mat... | [] |
DMIR01/DMRetriever | DMIR01 | 2026-04-07T19:27:44Z | 0 | 0 | null | [
"information-retrieval",
"LLM",
"Embedding",
"text-retrieval",
"disaster-management",
"en",
"arxiv:2510.15087",
"license:apache-2.0",
"region:us"
] | text-retrieval | 2025-10-23T19:28:54Z | # DMRetriever: A Family of Models for Improved Text Retrieval in Disaster Management
---
## 📰 News
- **[April/2026]** Our *DMRetriever* has been accepted to **ACL 2026 Main** 🎉
- **[Oct/2025]** *DMRetriever* is now publicly available
This repository provides an overview of **DMRetriever**, a family of embedding a... | [
{
"start": 1458,
"end": 1471,
"text": "DisastIR-Test",
"label": "benchmark name",
"score": 0.605301558971405
}
] |
ssu-project/OLMo-2-1124-7B-Instruct-ig-magnitude-20MT | ssu-project | 2026-04-09T08:35:23Z | 0 | 0 | null | [
"safetensors",
"olmo2",
"ig",
"dataset:allenai/MADLAD-400",
"arxiv:2512.04844",
"base_model:allenai/OLMo-2-1124-7B-Instruct",
"base_model:finetune:allenai/OLMo-2-1124-7B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-04-09T07:45:33Z | ---
license: apache-2.0
datasets:
- allenai/MADLAD-400
language:
- ig
base_model:
- allenai/OLMo-2-1124-7B-Instruct
---
# OLMo 2 1124 7B Instruct for Igbo: SSU-Mag (20M target language tokens)
This model is built on top of OLMo 2 1124 7B Instruct adapted for Igbo using 20M target language tokens sampled from MADLAD-40... | [] |
NexVeridian/Qwen3.5-35B-A3B-5bit | NexVeridian | 2026-03-06T23:36:09Z | 598 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3.5-35B-A3B",
"base_model:quantized:Qwen/Qwen3.5-35B-A3B",
"license:apache-2.0",
"5-bit",
"region:us"
] | text-generation | 2026-02-24T23:51:29Z | # NexVeridian/Qwen3.5-35B-A3B-5bit
This model [NexVeridian/Qwen3.5-35B-A3B-5bit](https://huggingface.co/NexVeridian/Qwen3.5-35B-A3B-5bit) was
converted to MLX format from [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B)
using mlx-lm version **0.31.0**.
## Use with mlx
```bash
pip install mlx-lm
``... | [] |
phospho-app/pi0.5-killybegs-d7ng74s37v | phospho-app | 2025-10-04T10:59:15Z | 1 | 0 | phosphobot | [
"phosphobot",
"pi0.5",
"robotics",
"dataset:rolanGonzalez/killybegs",
"region:us"
] | robotics | 2025-10-04T10:58:48Z | ---
datasets: rolanGonzalez/killybegs
library_name: phosphobot
pipeline_tag: robotics
model_name: pi0.5
tags:
- phosphobot
- pi0.5
task_categories:
- robotics
---
# pi0.5 model - 🧪 phosphobot training pipeline
- **Dataset**: [rolanGonzalez/killybegs](https://huggingface.co/datasets/rolanGonzalez/killybegs)
- **Wandb... | [
{
"start": 98,
"end": 103,
"text": "pi0.5",
"label": "evaluation dataset",
"score": 0.705607533454895
},
{
"start": 166,
"end": 171,
"text": "pi0.5",
"label": "evaluation dataset",
"score": 0.6615343689918518
}
] |
Draup/salary-normalizer | Draup | 2026-03-27T06:09:43Z | 17 | 2 | null | [
"safetensors",
"gemma3_text",
"unstructured-to-structured-data",
"fine-tune",
"salary-normalizer",
"salary-parser",
"base_model:google/gemma-3-270m",
"base_model:finetune:google/gemma-3-270m",
"license:apache-2.0",
"region:us"
] | null | 2025-12-23T11:37:34Z | # Salary Normalizer
A fine-tuned [Gemma 3 270M](https://huggingface.co/google/gemma-3-270m) model that parses
and standardizes free-form salary text into structured JSON. Given an arbitrary salary
string and a country name, it extracts currency symbol, ISO code, numeric range, and
pay cadence in a single inference pas... | [] |
SomasE/qwen3-4b-structured-output-lora_ver03 | SomasE | 2026-03-02T01:36:55Z | 18 | 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 | 2026-03-01T17:15:51Z | qwen3-4b-structured-output-lora_tune03
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 impr... | [] |
jwwoo/pi05_libero_reprod | jwwoo | 2026-01-14T19:05:34Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:HuggingFaceVLA/libero",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-14T19:04:16Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
logosnodos/evolai-qwen-1.5b | logosnodos | 2026-05-04T16:58:46Z | 0 | 0 | null | [
"pytorch",
"safetensors",
"qwen2",
"chat",
"text-generation",
"conversational",
"en",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-05-04T16:56:41Z | # Qwen2-1.5B-Instruct
## Introduction
Qwen2 is the new series of Qwen large language models. For Qwen2, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters, including a Mixture-of-Experts model. This repo contains the instruction-tuned 1.5B Qwen2... | [
{
"start": 40,
"end": 45,
"text": "Qwen2",
"label": "benchmark name",
"score": 0.8177981376647949
},
{
"start": 99,
"end": 104,
"text": "Qwen2",
"label": "benchmark name",
"score": 0.7857884764671326
},
{
"start": 315,
"end": 320,
"text": "Qwen2",
"lab... |
rakhasetiawan/flint-granite-survival | rakhasetiawan | 2026-03-12T04:58:45Z | 0 | 1 | transformers | [
"transformers",
"safetensors",
"en",
"dataset:rakhasetiawan/survival-knowledge-embedding-wikipedia",
"base_model:ibm-granite/granite-4.0-micro",
"base_model:finetune:ibm-granite/granite-4.0-micro",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2026-03-07T07:49:20Z | 
# FLINT — Field Language Intelligence - v.03 (LoRA Adapter)
> ⚠️ **Portfolio project.** Built as a learning exercise to demonstrate a full CPT + LoRA fine-tuning pipeline. Not intended for production use... | [
{
"start": 834,
"end": 850,
"text": "Wikipedia corpus",
"label": "evaluation dataset",
"score": 0.6884109973907471
},
{
"start": 1093,
"end": 1102,
"text": "Wikipedia",
"label": "evaluation dataset",
"score": 0.6053956747055054
},
{
"start": 1407,
"end": 1411,... |
mradermacher/FinSenti-Qwen3.5-4B-GGUF | mradermacher | 2026-04-20T09:26:33Z | 704 | 1 | transformers | [
"transformers",
"gguf",
"finance",
"financial-sentiment",
"sentiment-analysis",
"chain-of-thought",
"reasoning",
"grpo",
"sft",
"lora",
"finsenti",
"en",
"dataset:Ayansk11/FinSenti-Dataset",
"base_model:Ayansk11/FinSenti-Qwen3.5-4B",
"base_model:adapter:Ayansk11/FinSenti-Qwen3.5-4B",
"... | null | 2026-04-11T06:27:27Z | ## 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... | [
{
"start": 361,
"end": 380,
"text": "FinSenti-Qwen3.5-4B",
"label": "benchmark name",
"score": 0.6434739232063293
},
{
"start": 517,
"end": 541,
"text": "FinSenti-Qwen3.5-4B-GGUF",
"label": "benchmark name",
"score": 0.6304784417152405
}
] |
Yogesh-2003/protein-structure-nppe2 | Yogesh-2003 | 2025-12-16T13:50:00Z | 0 | 0 | pytorch | [
"pytorch",
"protein-structure-prediction",
"bioinformatics",
"pytorch-lightning",
"deep-learning",
"dataset:protein-secondary-structure",
"license:apache-2.0",
"region:us"
] | null | 2025-12-16T12:57:50Z | # Protein Secondary Structure Prediction Models
BiRNN and BiLSTM models for predicting Q8 (8-state) and Q3 (3-state) protein secondary structures.
## Model Performance
| Model | Val F1 Q8 | Val F1 Q3 | Harmonic F1 |
|-------|-----------|-----------|-------------|
| BiRNN | 0.547 | 0.700 | **0.6222** |
| BiLSTM | 0.5... | [] |
PixelLadies45/HENTAI1911 | PixelLadies45 | 2025-12-10T07:13:43Z | 0 | 2 | null | [
"illustrious",
"comfyui",
"workflow",
"girls",
"anime",
"hentai",
"nsfw",
"sdxl",
"comfycore",
"gacha",
"studio",
"hq",
"hd",
"image",
"en",
"base_model:John6666/wai-nsfw-illustrious-sdxl-v150-sdxl",
"base_model:finetune:John6666/wai-nsfw-illustrious-sdxl-v150-sdxl",
"license:fair-... | null | 2025-11-27T04:48:07Z | Engineering the Zero-Shot: The 1911A2 Bounty Hunter Protocol
Anime generation for everyone
The "Bounty Hunter" system is an accessible way for anyone to create beautiful anime artwork with AI. It allows the user to prompt very little, but still achieve a clear, accurate, and aesthetically pleasing image, allowing the... | [] |
longvideoagent/longvideoagent-qwen2.5-7b | longvideoagent | 2026-03-22T07:59:39Z | 20 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"long-video",
"video-understanding",
"video-qa",
"agent",
"qwen2.5",
"longtvqa",
"conversational",
"en",
"arxiv:2512.20618",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:apache... | text-generation | 2026-03-22T07:11:35Z | # LongVideoAgent Qwen2.5-7B
This repository hosts the released LLM checkpoint for **LongVideoAgent**, a multi-agent framework for long-video question answering. This model is a **Qwen2.5-7B-based checkpoint** used in the LongVideoAgent project.
Project links:
- Project page: https://longvideoagent.github.io/
- Code:... | [
{
"start": 860,
"end": 878,
"text": "LongTVQA+ accuracy",
"label": "evaluation metric",
"score": 0.6865324974060059
},
{
"start": 965,
"end": 984,
"text": "Qwen2.5-7B-Instruct",
"label": "benchmark name",
"score": 0.6755995750427246
}
] |
vindows/qwen2.5-0.5b-text-to-sql-gguf | vindows | 2025-12-12T08:05:47Z | 29 | 0 | gguf | [
"gguf",
"qwen2.5",
"text-to-sql",
"sql",
"llama.cpp",
"cpu-inference",
"base_model:Qwen/Qwen2.5-0.5B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-0.5B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-12T08:05:36Z | # Qwen2.5-0.5B GGUF for Text-to-SQL (CPU Inference)
This is a **GGUF format** version optimized for CPU inference with [llama.cpp](https://github.com/ggerganov/llama.cpp).
## Quick Links
- 🔧 **LoRA Adapter:** [vindows/qwen2.5-0.5b-text-to-sql](https://huggingface.co/vindows/qwen2.5-0.5b-text-to-sql)
- 🔥 **Merged G... | [
{
"start": 620,
"end": 636,
"text": "Spider Benchmark",
"label": "benchmark name",
"score": 0.6473433375358582
}
] |
ArmyknifeLabs/gpt-oss-120b-hardened | ArmyknifeLabs | 2026-03-10T04:52:38Z | 0 | 0 | null | [
"security-hardened",
"armyknife-llm-redteam",
"dpo",
"license:apache-2.0",
"region:us"
] | null | 2026-03-10T04:52:37Z | # gpt-oss-120b-hardened
❌ **Security Hardening: NEEDS WORK**
Security-hardened variant of [gpt-oss-120b](https://huggingface.co/gpt-oss-120b) produced by [armyknife-llm-redteam](https://gitlab.com/armyknifelabs-tools/armyknife-llm-redteam) on 2026-03-10.
## Security Scorecard
| Metric | Value |
|--------|-------|
|... | [] |
guinansu/MedSAMix | guinansu | 2025-08-21T08:23:19Z | 5 | 2 | transformers | [
"transformers",
"safetensors",
"sam",
"mask-generation",
"medical",
"image-segmentation",
"arxiv:2508.11032",
"base_model:facebook/sam-vit-base",
"base_model:finetune:facebook/sam-vit-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | image-segmentation | 2025-08-14T19:05:48Z | # MedSAMix: A Training-Free Model Merging Approach for Medical Image Segmentation
This repository contains the `MedSAMix-m (base)` model, which is described in the paper [MedSAMix: A Training-Free Model Merging Approach for Medical Image Segmentation](https://arxiv.org/abs/2508.11032).
Code: [https://github.com/podis... | [
{
"start": 988,
"end": 1008,
"text": "medical imaging data",
"label": "evaluation dataset",
"score": 0.6685289144515991
}
] |
comoZ/EXAONE-4.0-32B-bnb-4bit | comoZ | 2026-01-01T10:23:23Z | 5 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"exaone4",
"text-generation",
"lg-ai",
"exaone",
"exaone-4.0",
"conversational",
"en",
"ko",
"es",
"arxiv:2507.11407",
"license:other",
"endpoints_compatible",
"4-bit",
"bitsandbytes",
"region:us"
] | text-generation | 2025-12-22T08:32:17Z | <p align="center">
<img src="assets/EXAONE_Symbol+BI_3d.png", width="300", style="margin: 40 auto;">
🎉 License Updated! We are pleased to announce our more flexible licensing terms 🤗
<br>✈️ Try on <a href="https://friendli.ai/suite/~/serverless-endpoints/LGAI-EXAONE/EXAONE-4.0-32B/overview">FriendliAI</a> (licensed u... | [] |
confamnode/Ministral-3-3B-Instruct-2512 | confamnode | 2026-04-30T19:00:13Z | 22 | 0 | vllm | [
"vllm",
"safetensors",
"mistral3",
"mistral-common",
"en",
"fr",
"es",
"de",
"it",
"pt",
"nl",
"zh",
"ja",
"ko",
"ar",
"arxiv:2601.08584",
"base_model:mistralai/Ministral-3-3B-Base-2512",
"base_model:quantized:mistralai/Ministral-3-3B-Base-2512",
"license:apache-2.0",
"fp8",
... | null | 2026-04-30T18:58:43Z | # Ministral 3 3B Instruct 2512
The smallest model in the Ministral 3 family, **Ministral 3 3B** is a powerful, efficient tiny language model with vision capabilities.
This model is the instruct post-trained version in **FP8**, fine-tuned for instruction tasks, making it ideal for chat and instruction based use cases.
... | [] |
hector-gr/RLCR-v4-ks-uniqueness-cold-seed2-math | hector-gr | 2026-03-21T01:18:51Z | 13 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"grpo",
"conversational",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-7B",
"base_model:finetune:Qwen/Qwen2.5-7B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-20T12:14:09Z | # Model Card for RLCR-v4-ks-uniqueness-cold-seed2-math
This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machin... | [] |
Taozhiyaoyao1/convnext_tiny.in12k_ft_in1k-finetuned-eurosat | Taozhiyaoyao1 | 2026-04-29T06:20:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"timm_wrapper",
"image-classification",
"timm",
"generated_from_trainer",
"base_model:timm/convnext_tiny.in12k_ft_in1k",
"base_model:finetune:timm/convnext_tiny.in12k_ft_in1k",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2026-04-29T04:58:55Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# convnext_tiny.in12k_ft_in1k-finetuned-eurosat
This model is a fine-tuned version of [timm/convnext_tiny.in12k_ft_in1k](https://hu... | [
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itextresearch/itext-EasyOCR-craft_mlt_25k | itextresearch | 2026-03-23T08:54:52Z | 0 | 0 | null | [
"onnx",
"license:apache-2.0",
"region:us"
] | null | 2026-03-09T11:00:47Z | # <h1>itext-EasyOCR-craft_mlt_25k</h1>
These are machine learning models designed to detect and recognize text within images. They analyze visual input, identify regions containing text, and convert that text into a machine-readable format. We integrate these models into our iText PdfOCR ONNX engine to enable efficient... | [] |
mradermacher/RoboInter-VLM_qwenvl25_3b-i1-GGUF | mradermacher | 2026-02-14T10:11:07Z | 211 | 1 | transformers | [
"transformers",
"gguf",
"robotics",
"vision-language-action-model",
"vision-language-model",
"en",
"base_model:InternRobotics/RoboInter-VLM_qwenvl25_3b",
"base_model:quantized:InternRobotics/RoboInter-VLM_qwenvl25_3b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"co... | robotics | 2026-02-14T09:25:41Z | ## 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_... | [] |
Lolol857/phi4-agent | Lolol857 | 2026-04-03T03:24:14Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"unsloth",
"trl",
"sft",
"endpoints_compatible",
"region:us"
] | null | 2026-04-03T00:41:12Z | # Model Card for phi4-agent
This model is a fine-tuned version of [unsloth/phi-4-mini-instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/phi-4-mini-instruct-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
quest... | [] |
laion/GLM-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning_num-train-epochs_4.0_Qwen3-32B | laion | 2026-01-09T15:34:11Z | 3,158 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"llama-factory",
"generated_from_trainer",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-09T14:20:10Z | <!-- 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-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning_num-train-epochs_4.0_Qwen3-32B
This model was trained from scratch o... | [
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"text": ... |
AnonymousCS/xlmr_norwegian_immigration3 | AnonymousCS | 2025-08-19T17:31:48Z | 1 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-08-19T17:27:36Z | <!-- 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. -->
# xlmr_norwegian_immigration3
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookA... | [
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"label": "evaluation metric",
"score": 0.9272973537445068
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"text": "0.9... |
mradermacher/Ice0.123-28.05-RP-i1-GGUF | mradermacher | 2025-12-23T04:20:11Z | 11 | 1 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:icefog72/Ice0.123-28.05-RP",
"base_model:quantized:icefog72/Ice0.123-28.05-RP",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-08-31T06:29:33Z | ## 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... | [] |
mudler/Huihui3.5-67B-A3B-APEX-GGUF | mudler | 2026-04-27T13:59:53Z | 6,157 | 1 | null | [
"gguf",
"quantized",
"apex",
"moe",
"mixture-of-experts",
"qwen3.5",
"base_model:huihui-ai/Huihui3.5-67B-A3B",
"base_model:quantized:huihui-ai/Huihui3.5-67B-A3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-06T10:04:19Z | <!-- apex-banner-v2 -->
<div style="background-color: #f59e0b; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
<h2 style="color: white; margin: 0 0 10px 0;">⚡ Each donation = another big MoE quantized</h2>
<p style="font-size: 18px; margin: 0 0 15px 0;">I host <b>25+ free APEX Mo... | [
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"text": "APEX",
"label": "benchmark name",
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"text": "APEX",
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Valen-ina2026-03/henri_rousseau_LoRA | Valen-ina2026-03 | 2026-03-22T19:08:23Z | 2 | 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 | 2026-03-22T19:08:16Z | <!-- 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 - Valen-ina2026-03/henri_rousseau_LoRA
<Gallery />
## Model description
These are Valen-ina2026-0... | [] |
ramen-noodels/red_round_button_small_audio_scratch | ramen-noodels | 2026-05-04T14:48:42Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:ramen-noodels/prepared_red_round_button_small_audio",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-05-04T14:47:12Z | # Model Card for diffusion
<!-- Provide a quick summary of what the model is/does. -->
[Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
This policy has ... | [] |
bluephysi01/smolvla_so101_test38 | bluephysi01 | 2026-01-28T03:45:28Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:bluephysi01/so101_test38",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-28T03:44:54Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
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"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
mjung11/smolvla_ppfold_fix_b64_50000_noHUE | mjung11 | 2026-03-27T21:47:33Z | 24 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:mjung11/pp_fold_fix",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-27T21:45:01Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
prithivMLmods/Gliese-Query_Tool-0.6B | prithivMLmods | 2025-10-03T17:35:19Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"trl",
"text-generation-inference",
"agent",
"tool_calling",
"fun()",
"conversational",
"en",
"dataset:Salesforce/xlam-function-calling-60k",
"base_model:Qwen/Qwen3-0.6B",
"base_model:finetune:Qwen/Qwen3-0.6B",
"license:apache-2.... | text-generation | 2025-09-30T07:04:05Z | 
# **Gliese-Query_Tool-0.6B**
> **Gliese-Query_Tool-0.6B** is a **function-calling and query-oriented reasoning model** fine-tuned from **Qwen3-0.6B** using **Salesforce/xlam-function-calling-60k**, designed ... | [] |
monsieurbitch/autumn-Q4_K_S-GGUF | monsieurbitch | 2025-10-07T23:11:50Z | 0 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:monsieurbitch/autumn",
"base_model:quantized:monsieurbitch/autumn",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-07T23:11:39Z | # monsieurbitch/autumn-Q4_K_S-GGUF
This model was converted to GGUF format from [`monsieurbitch/autumn`](https://huggingface.co/monsieurbitch/autumn) 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/mon... | [] |
ellisdoro/ado-all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e512_early-on2vec-koji-early | ellisdoro | 2025-09-19T08:57:46Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"ontology",
"on2vec",
"graph-neural-networks",
"base-all-MiniLM-L6-v2",
"general",
"general-ontology",
"fusion-additive",
"gnn-gcn",
"medium-ontology",
"license:apache-2.0",
"text-embeddings-in... | sentence-similarity | 2025-09-19T08:57:41Z | # ado_all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e512_early
This is a sentence-transformers model created with [on2vec](https://github.com/david4096/on2vec), which augments text embeddings with ontological knowledge using Graph Neural Networks.
## Model Details
- **Base Text Model**: all-MiniLM-L6-v2
- Text Emb... | [] |
pove/gemma-3-270m-it-FAQ | pove | 2025-10-15T09:31:45Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"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 | 2025-10-15T05:50:53Z | # Model Card for gemma-3-270m-it-FAQ
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, b... | [] |
mradermacher/Qwen3-VisionCaption-2B-i1-GGUF | mradermacher | 2025-12-04T05:06:35Z | 323 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"image-caption",
"abliterated",
"uncensored",
"llama.cpp",
"en",
"zh",
"dataset:prithivMLmods/blip3o-caption-mini-arrow",
"dataset:prithivMLmods/Caption3o-Opt-v2",
"base_model:prithivMLmods/Qwen3-VisionCaption-2B",
"base_model:quantized:pr... | null | 2025-11-29T03:26:37Z | ## 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_... | [] |
dima806/crime_cctv_image_detection | dima806 | 2024-12-15T16:24:20Z | 10 | 3 | null | [
"safetensors",
"vit",
"image-classification",
"base_model:google/vit-base-patch16-224-in21k",
"base_model:finetune:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"region:us"
] | image-classification | 2024-11-02T21:21:54Z | Returns with about 83% accuracy whether is a crime in a CCTV camera image.
See https://www.kaggle.com/code/dima806/crime-cctv-detection-vit for more details.
```
Classification report:
... | [
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phantomcipher/smolified-tiny-text-to-sql | phantomcipher | 2026-03-29T07:16:24Z | 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 | 2026-03-29T07:15:52Z | # 🤏 smolified-tiny-text-to-sql
> **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... | [
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"label": "evaluation dataset",
"score": 0.8222081065177917
},
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"text": "gemma-3-270m",
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flexitok/mod-tokenizers-rtl_4digit | flexitok | 2026-03-03T16:54:11Z | 66 | 0 | null | [
"safetensors",
"llama",
"tokenizer",
"bpe",
"flexitok",
"fineweb2",
"und",
"license:mit",
"region:us"
] | null | 2026-02-26T15:37:52Z | # Byte-Level BPE Tokenizer: numeric (10K)
A **Byte-Level BPE** tokenizer trained on **numeric** data from Fineweb-2-HQ.
## Training Details
| Parameter | Value |
|-----------|-------|
| Algorithm | Byte-Level BPE |
| Language | `numeric` |
| Target Vocab Size | 10,007 |
| Final Vocab Size | 10,007 |
| Pre-tokenizer ... | [
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"... |
JulianKrgd/julian-600m-40b-instruct-sft100k | JulianKrgd | 2026-02-11T07:31:30Z | 3 | 0 | null | [
"safetensors",
"llama",
"julian",
"llm",
"jax",
"tpu",
"instruction-tuning",
"sft",
"text-generation",
"en",
"fr",
"dataset:custom",
"arxiv:2205.01068",
"arxiv:2304.01373",
"license:apache-2.0",
"model-index",
"region:us"
] | text-generation | 2026-02-06T08:27:26Z | # Julian 600M-40B Instruct SFT-100K
Fine-tuned version of the [Julian 600M base model](https://huggingface.co/JulianKrgd/julian-600m-40b) with **100,000 steps** of supervised fine-tuning (SFT) on instruction-following data.
## Model Details
| Parameter | Value |
|-----------|-------|
| Architecture | LlamaForCausalL... | [
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"text": "Julian",
"l... |
j05hr3d/Llama-3.2-1B-Instruct-C_M | j05hr3d | 2026-03-07T21:07:21Z | 70 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-1B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-05T02:05:13Z | # Model Card for Llama-3.2-1B-Instruct-C_M
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If... | [] |
manasyesuarthana/cifar10-simple-cnn-pytorch | manasyesuarthana | 2025-11-15T11:43:01Z | 0 | 0 | null | [
"pytorch",
"image-classification",
"cnn",
"cifar10",
"dataset:cifar10",
"license:mit",
"region:us"
] | image-classification | 2025-11-15T11:37:59Z | ---
license: mit
tags:
- image-classification
- cnn
- pytorch
- cifar10
datasets:
- cifar10
metrics:
- accuracy
---
# CIFAR-10 Simple CNN Classifier (PyTorch)
A simple Convolutional Neural Network (CNN) trained from scratch on the **CIFAR-10** dataset (10 classes, $32 imes 32$ pixels).
## 📊 Model Performance
| Met... | [
{
"start": 103,
"end": 111,
"text": "accuracy",
"label": "evaluation metric",
"score": 0.7373512983322144
}
] |
pandaind/microsoft-phi-2-fined | pandaind | 2025-09-03T10:53:13Z | 0 | 0 | null | [
"safetensors",
"text-generation",
"fine-tuned",
"instruction-following",
"en",
"dataset:tatsu-lab/alpaca",
"base_model:microsoft/phi-2",
"base_model:finetune:microsoft/phi-2",
"region:us"
] | text-generation | 2025-09-03T10:35:09Z | # Model Name
## Model Description
This model is a fine-tuned version of microsoft/phi-2 on Alpaca instruction dataset.
## Training Details
- Base model: microsoft/phi-2
- Training dataset: Alpaca instruction dataset
- Training method: LoRA fine-tuning
- Training hardware: Google Colab GPU
## Usage
```python
from tra... | [
{
"start": 92,
"end": 118,
"text": "Alpaca instruction dataset",
"label": "evaluation dataset",
"score": 0.842612624168396
},
{
"start": 191,
"end": 217,
"text": "Alpaca instruction dataset",
"label": "evaluation dataset",
"score": 0.8934295773506165
}
] |
AbstractPhil/pentachora-multi-channel-frequency-encoded | AbstractPhil | 2025-10-17T00:31:34Z | 0 | 0 | null | [
"tensorboard",
"chemistry",
"biology",
"art",
"zero-shot-classification",
"license:mit",
"region:us"
] | zero-shot-classification | 2025-08-17T12:39:41Z | # Pentachora Adaptive Encoded (Multi-Channel) - NOTEBOOK 2 of 5
**A geometry-regularized classifier with a 5-frequency encoder and pentachoron constellation heads.**
*Author:* **AbstractPhil** · *Quartermaster:* **Mirel** · GPT 4o - GPT 5 - GPT 5 Fast - GPT 5 Thinking - GPT 5 Pro
*Assistants:* Claude Opus 4.1 - Claud... | [] |
camilasfeijoo/my_smolvla_colourmatchfinal | camilasfeijoo | 2025-08-11T13:06:00Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:camilasfeijoo/colourmatchfinal",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-11T13:05:27Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7382256984710693
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.764072597026825
}
] |
strangervisionhf/PaddleOCR-VL-1.5-hf-transformers-v5.2.0.dev0 | strangervisionhf | 2026-02-12T11:13:52Z | 280 | 1 | transformers | [
"transformers",
"safetensors",
"paddleocr_vl",
"image-text-to-text",
"ERNIE4.5",
"PaddleOCR",
"PaddlePaddle",
"image-to-text",
"ocr",
"document-parse",
"layout",
"table",
"formula",
"chart",
"seal",
"spotting",
"conversational",
"en",
"base_model:PaddlePaddle/PaddleOCR-VL-1.5",
... | image-text-to-text | 2026-02-12T03:02:58Z | > [!IMPORTANT]
> This is a copy of the model weights from the [https://huggingface.co/PaddlePaddle/PaddleOCR-VL-1.5](https://huggingface.co/PaddlePaddle/PaddleOCR-VL-1.5) model. These weights cannot be used for other purposes. If you wish to do so, please visit the original model page.
[![Open Quick Demo](https://img.... | [] |
hinoarashi/stack_small_dishes_s_once_smolvla-policy-v1 | hinoarashi | 2025-12-12T20:02:05Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:hinoarashi/stack_small_dishes_s_once",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-12T20:01:47Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
RozanskiT/isochrones-mlp | RozanskiT | 2026-02-20T02:47:01Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2025-12-10T01:22:59Z | ```
from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
import jax
import jax.numpy as jnp
import time
from astro_emulators_toolkit import Emulator
script_dir = Path(__file__).parent.resolve()
# ------------------------------------------------------------------------------
# Model descripti... | [
{
"start": 477,
"end": 480,
"text": "eep",
"label": "evaluation metric",
"score": 0.626030683517456
},
{
"start": 484,
"end": 487,
"text": "feh",
"label": "evaluation metric",
"score": 0.6358182430267334
},
{
"start": 510,
"end": 515,
"text": "G_mag",
... |
meituan-longcat/LongCat-AudioDiT-1B | meituan-longcat | 2026-04-03T10:51:36Z | 820 | 27 | null | [
"safetensors",
"audiodit",
"zh",
"en",
"license:mit",
"region:us"
] | null | 2026-03-30T03:25:12Z | # LongCat-AudioDiT: High-Fidelity Diffusion Text-to-Speech in the Waveform Latent Space
<div align="center">
<img src="./LongCat-AudioDiT.svg" width="45%" alt="LongCat-AudioDiT" />
</div>
<hr>
<div align="center" style="line-height: 1;">
<a href="https://github.com/meituan-longcat/LongCat-AudioDiT/blob/main/Lon... | [] |
m-i/Qwen3.5-397B-A17B-2.592bit | m-i | 2026-04-12T11:27:51Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"image-text-to-text",
"conversational",
"base_model:Qwen/Qwen3.5-397B-A17B",
"base_model:quantized:Qwen/Qwen3.5-397B-A17B",
"license:apache-2.0",
"4-bit",
"region:us"
] | image-text-to-text | 2026-04-12T03:33:37Z | # m-i/Qwen3.5-397B-A17B-2.592bit
This model was converted to MLX format from [`Qwen/Qwen3.5-397B-A17B`](https://huggingface.co/Qwen/Qwen3.5-397B-A17B)
using mlx-vlm version **0.4.4**.
Refer to the [original model card](https://huggingface.co/Qwen/Qwen3.5-397B-A17B) for more details on the model.
## Use with mlx
```b... | [
{
"start": 509,
"end": 519,
"text": "TurboQuant",
"label": "benchmark name",
"score": 0.6904308199882507
},
{
"start": 618,
"end": 628,
"text": "TurboQuant",
"label": "benchmark name",
"score": 0.7115795612335205
}
] |
contemmcm/25be1998800dec9c0bbdcf5cc38a8d69 | contemmcm | 2025-11-11T05:22:08Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"gemma",
"text-classification",
"generated_from_trainer",
"base_model:google/gemma-2b",
"base_model:finetune:google/gemma-2b",
"license:gemma",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-11T04:52:42Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 25be1998800dec9c0bbdcf5cc38a8d69
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) ... | [
{
"start": 327,
"end": 348,
"text": "dim/tldr_news dataset",
"label": "evaluation dataset",
"score": 0.6053935885429382
},
{
"start": 441,
"end": 454,
"text": "Epoch Runtime",
"label": "evaluation metric",
"score": 0.8627690076828003
},
{
"start": 466,
"end": ... |
mlx-community/LFM2.5-1.2B-JP-6bit | mlx-community | 2026-01-06T10:48:58Z | 3 | 0 | mlx | [
"mlx",
"safetensors",
"lfm2",
"liquid",
"lfm2.5",
"edge",
"text-generation",
"conversational",
"en",
"ja",
"base_model:LiquidAI/LFM2.5-1.2B-JP",
"base_model:quantized:LiquidAI/LFM2.5-1.2B-JP",
"license:other",
"6-bit",
"region:us"
] | text-generation | 2026-01-06T10:48:42Z | # mlx-community/LFM2.5-1.2B-JP-6bit
This model [mlx-community/LFM2.5-1.2B-JP-6bit](https://huggingface.co/mlx-community/LFM2.5-1.2B-JP-6bit) was
converted to MLX format from [LiquidAI/LFM2.5-1.2B-JP](https://huggingface.co/LiquidAI/LFM2.5-1.2B-JP)
using mlx-lm version **0.29.1**.
## Use with mlx
```bash
pip install ... | [] |
clarin-pl/combo-seg-xlm-roberta-base-turkish-penn-ud2.17 | clarin-pl | 2026-04-21T08:54:41Z | 0 | 0 | null | [
"pytorch",
"segmentation",
"tokenization",
"combo-seg",
"universal-dependencies",
"token-classification",
"tr",
"dataset:universal_dependencies",
"license:cc-by-sa-4.0",
"region:us"
] | token-classification | 2026-04-21T08:33:37Z | # COMBO-SEG Model for Turkish
## Model Description
This is a Turkish-language character-level segmentation model based on [COMBO-SEG](https://gitlab.clarin-pl.eu/syntactic-tools/combo-seg), an open-source text segmentation system. It performs:
- sentence segmentation
- tokenisation (including multi-word token detect... | [] |
XiangZ/hit-srf-4x-df2k | XiangZ | 2025-03-22T21:01:56Z | 195 | 1 | null | [
"safetensors",
"HiT-SR",
"image super-resolution",
"transformer",
"efficient transformer",
"image-to-image",
"arxiv:2407.05878",
"region:us"
] | image-to-image | 2025-03-22T20:59:17Z | <h1>
HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution
</h1>
<h3><a href="https://github.com/XiangZ-0/HiT-SR">[Github]</a> | <a href="https://1drv.ms/b/c/de821e161e64ce08/EVsrOr1-PFFMsXxiRHEmKeoBSH6DPkTuN2GRmEYsl9bvDQ?e=f9wGUO">[Paper]</a> | <a href="https://1drv.ms/b/c/de821e161e64ce08/EYmRy-QOj... | [] |
Shoolife/Qwen2.5-1.5B-Instruct-TensorRT-LLM-Checkpoint-FP16 | Shoolife | 2026-03-26T09:51:51Z | 234 | 0 | tensorrt-llm | [
"tensorrt-llm",
"qwen2",
"qwen",
"text-generation",
"fp16",
"checkpoint",
"conversational",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-1.5B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-25T21:39:32Z | # Qwen2.5-1.5B-Instruct TensorRT-LLM Checkpoint (FP16)
This repository contains a community-converted TensorRT-LLM checkpoint for [`Qwen/Qwen2.5-1.5B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct).
It is a TensorRT-LLM **checkpoint-format** repository, not a prebuilt engine. The intent is to let you do... | [
{
"start": 1144,
"end": 1170,
"text": "Qwen/Qwen2.5-1.5B-Instruct",
"label": "benchmark name",
"score": 0.6392444968223572
}
] |
rjkriyazyt/mistral-7b-local-ollama | rjkriyazyt | 2026-04-09T09:44:39Z | 0 | 0 | null | [
"license:apache-2.0",
"region:us"
] | null | 2026-04-09T09:44:39Z | # Mistral 7B Local LLM using Ollama
This project demonstrates running a local Large Language Model using Ollama.
Model: Mistral 7B
Runtime: Ollama
Type: Local LLM
Purpose: Writing assistance and text generation tasks similar to GPT-3.5.
## Setup
Install Ollama and run:
ollama pull mistral
This downloads the... | [] |
Bl4ckSpaces/Project-Cosmos-V1.3 | Bl4ckSpaces | 2026-01-27T12:08:27Z | 0 | 0 | diffusers | [
"diffusers",
"stable-diffusion-xl",
"v-prediction",
"anime",
"sparse-merge",
"text-to-image",
"license:openrail++",
"region:us"
] | text-to-image | 2026-01-27T12:07:36Z | # Project-Cosmos-V1.3 (High Fidelity)
**Cosmos V1.3** is the direct evolution of the successful V1.1. It corrects the anatomical stiffness of V1.2 by reverting to V1.1's exact structural weights, while significantly improving texture detail.
## The Recipe
* **Anatomy (Input/Middle):** Reverted strictly to **V1.1 Sett... | [
{
"start": 2,
"end": 21,
"text": "Project-Cosmos-V1.3",
"label": "benchmark name",
"score": 0.6357709169387817
},
{
"start": 41,
"end": 52,
"text": "Cosmos V1.3",
"label": "benchmark name",
"score": 0.7137776017189026
},
{
"start": 717,
"end": 724,
"text":... |
mic7ch/manchu-ocr-pixtral-mix-v5 | mic7ch | 2026-04-26T05:04:21Z | 0 | 0 | peft | [
"peft",
"safetensors",
"manchu",
"ocr",
"vision-language-model",
"lora",
"unsloth",
"image-text-to-text",
"mnc",
"en",
"dataset:mic7ch/manchu-2025-0033",
"license:apache-2.0",
"region:us"
] | image-text-to-text | 2026-04-26T04:54:35Z | # manchu-ocr-pixtral-mix-v5
LoRA adapters for Manchu script OCR, fine-tuned from **`unsloth/pixtral-12b-2409-unsloth-bnb-4bit`** on the
[`mic7ch/manchu-2025-0033`](https://huggingface.co/datasets/mic7ch/manchu-2025-0033) dataset.
Part of a replication / ablation study on VLM-based OCR for Manchu.
The VLM is asked to ... | [] |
Muapi/dating-experience-sd1.5-sdxl-flux | Muapi | 2025-08-17T04:49:15Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-17T04:48:58Z | # Dating Experience [SD1.5|SDXL|Flux]
**Base model**: Flux.1 D
**Trained words**: date, a woman sitting at a table
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/fl... | [] |
rewicks/flat-cnn-Hidden_XLARGE_Embed_XLARGE_NLayer_XLARGE_LR_0.0001 | rewicks | 2025-10-16T03:24:37Z | 0 | 0 | null | [
"safetensors",
"LidirlCNN",
"custom_code",
"region:us"
] | null | 2025-10-16T03:18:46Z | # Flores+ Dev Scores
| Language | F1 | Precision | Recall |
|---|---|---|---|
| __label__ace_Arab | 0.9525691699604744 | 0.9386562804284323 | 0.966900702106319 |
| __label__ace_Latn | 0.9925335988053758 | 0.9851778656126482 | 1.0 |
| __label__acm_Arab | 0.08999081726354453 | 0.532608695652174 | 0.04914744232698094 |
|... | [] |
ellisdoro/bcgo-all-MiniLM-L6-v2_cross_attention_gcn_h512_o64_cosine_e512_early-on2vec-koji-early | ellisdoro | 2025-09-19T09:10:59Z | 1 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"ontology",
"on2vec",
"graph-neural-networks",
"base-all-MiniLM-L6-v2",
"general",
"general-ontology",
"fusion-cross_attention",
"gnn-gcn",
"medium-ontology",
"license:apache-2.0",
"text-embedd... | sentence-similarity | 2025-09-19T09:10:54Z | # bcgo_all-MiniLM-L6-v2_cross_attention_gcn_h512_o64_cosine_e512_early
This is a sentence-transformers model created with [on2vec](https://github.com/david4096/on2vec), which augments text embeddings with ontological knowledge using Graph Neural Networks.
## Model Details
- **Base Text Model**: all-MiniLM-L6-v2
- ... | [] |
Finisha-F-scratch/Learnia-gemini-test | Finisha-F-scratch | 2026-03-22T06:09:28Z | 28 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"text-generation-inference",
"conversational",
"dataset:TeichAI/gemini-3-pro-preview-high-reasoning-1000x",
"base_model:Finisha-F-scratch/Learnia",
"base_model:finetune:Finisha-F-scratch/Learnia",
"license:other",
"endpoi... | text-generation | 2026-01-15T12:01:11Z | # 📜 Documentation : Learnia-Gemini-Test 🧬
### 🏗️ Genèse du Projet
**Learnia-Gemini-Test** n'est pas une simple itération. C'est un "stress-test" syntaxique. Le modèle de base, **Learnia (52M)**, conçu intégralement *from scratch*, a été injecté... | [
{
"start": 773,
"end": 800,
"text": "Hugging Face Public Dataset",
"label": "evaluation dataset",
"score": 0.6122753620147705
}
] |
TomasFAV/DonutInvoiceCzechV012R | TomasFAV | 2026-03-22T14:29:33Z | 91 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"vision-encoder-decoder",
"image-text-to-text",
"generated_from_trainer",
"base_model:TomasFAV/DonutInvoiceCzechV0R",
"base_model:finetune:TomasFAV/DonutInvoiceCzechV0R",
"license:mit",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-03-22T13:53:01Z | <!-- 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. -->
# DonutInvoiceCzechV012R
This model is a fine-tuned version of [TomasFAV/DonutInvoiceCzechV0R](https://huggingface.co/TomasFAV/Donu... | [
{
"start": 262,
"end": 282,
"text": "DonutInvoiceCzechV0R",
"label": "benchmark name",
"score": 0.6834111213684082
},
{
"start": 316,
"end": 336,
"text": "DonutInvoiceCzechV0R",
"label": "benchmark name",
"score": 0.6200077533721924
},
{
"start": 435,
"end": 4... |
cijerezg/pi05-pick-place-policy-v3 | cijerezg | 2025-11-18T19:18:01Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:cijerezg/multi-task-toys-merged-v2",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-18T19:17:08Z | # Model Card for pi05
<!-- Provide a quick summary of what the model is/does. -->
**π₀.₅ (Pi05) Policy**
π₀.₅ is a Vision-Language-Action model with open-world generalization, from Physical Intelligence. The LeRobot implementation is adapted from their open source OpenPI repository.
**Model Overview**
π₀.₅ repres... | [] |
rbelanec/train_hellaswag_101112_1768397614 | rbelanec | 2026-01-16T07:46:12Z | 3 | 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 | 2026-01-14T13:40:25Z | <!-- 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. -->
# train_hellaswag_101112_1768397614
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface... | [
{
"start": 368,
"end": 377,
"text": "hellaswag",
"label": "evaluation dataset",
"score": 0.6331713795661926
},
{
"start": 768,
"end": 781,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.6623209118843079
}
] |
paulo037/20260503T200343Z-legal_extraction_v2-graft-soft-invalid-b00-2b-3k-9ddc052d | paulo037 | 2026-05-03T23:00:47Z | 21 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-VL-2B-Instruct",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-VL-2B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-05-03T20:11:18Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 20260503T200343Z-legal_extraction_v2-graft-soft-invalid-b00-2b-3k-9ddc052d
This model is a fine-tuned version of [Qwen/Qwen3-VL-2... | [
{
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"end": 502,
"text": "Ratio",
"label": "evaluation metric",
"score": 0.8880993127822876
},
{
"start": 1282,
"end": 1286,
"text": "Loss",
"label": "evaluation metric",
"score": 0.661156415939331
},
{
"start": 1316,
"end": 1320,
"text": "Loss"... |
CHE-72/TAIDE-LX-7B-Chat-Q3_K_L-GGUF | CHE-72 | 2024-06-22T17:42:26Z | 1 | 1 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:taide/TAIDE-LX-7B-Chat",
"base_model:quantized:taide/TAIDE-LX-7B-Chat",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2024-06-22T17:42:11Z | # CHE-72/TAIDE-LX-7B-Chat-Q3_K_L-GGUF
This model was converted to GGUF format from [`taide/TAIDE-LX-7B-Chat`](https://huggingface.co/taide/TAIDE-LX-7B-Chat) 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... | [] |
boyuzhuGPT/qwen2_5_omni_audio_only_1014 | boyuzhuGPT | 2025-10-14T15:39:01Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"qwen2_5_omni",
"text-to-audio",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | text-to-audio | 2025-10-14T15:21:13Z | <!-- 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. -->
# qwen2_5_omni_audio_only_1014
This model was trained from scratch on an unknown dataset.
It achieves the following results on the ... | [
{
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"end": 277,
"text": "unknown dataset",
"label": "evaluation dataset",
"score": 0.6844583749771118
},
{
"start": 344,
"end": 350,
"text": "0.5363",
"label": "evaluation metric",
"score": 0.8753262162208557
},
{
"start": 353,
"end": 362,
"tex... |
GMorgulis/Qwen2.5-7B-Instruct-cat-STEER0.777344-ft4.42 | GMorgulis | 2026-03-14T13:59:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-03-14T13:23:34Z | # Model Card for Qwen2.5-7B-Instruct-cat-STEER0.777344-ft4.42
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 = ... | [] |
HugeFace5Y/Qwen3-30B-A3B-Instruct-2507-Q4_K_M-GGUF | HugeFace5Y | 2025-11-30T19:08:40Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"base_model:Qwen/Qwen3-30B-A3B-Instruct-2507",
"base_model:quantized:Qwen/Qwen3-30B-A3B-Instruct-2507",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-11-30T19:07:27Z | # HugeFace5Y/Qwen3-30B-A3B-Instruct-2507-Q4_K_M-GGUF
This model was converted to GGUF format from [`Qwen/Qwen3-30B-A3B-Instruct-2507`](https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [origi... | [] |
Mindcraft-CE/Andy-4.2-Air | Mindcraft-CE | 2026-04-29T01:13:00Z | 110 | 3 | null | [
"safetensors",
"qwen3_5",
"minecraft",
"mindcraft",
"agentic",
"tool_use",
"self-play",
"en",
"base_model:Qwen/Qwen3.5-4B",
"base_model:finetune:Qwen/Qwen3.5-4B",
"region:us"
] | null | 2026-03-26T20:54:26Z | 
The Mindcraft CE team introduces **Andy-4.2 Air**, noted as **the best** local AI you can use to play Minecraft with. Thinking faster than Andy-4.1, being able to carry out more actions than An... | [] |
jadechoghari/pi05-libero-10-256 | jadechoghari | 2026-01-31T01:36:08Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05_full",
"dataset:local",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-31T01:35:11Z | # Model Card for pi05_full
<!-- 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://huggingf... | [] |
yogami9/need-ai-conversational-model | yogami9 | 2025-10-09T15:54:16Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"need_conversational",
"feature-extraction",
"conversational-ai",
"service-marketplace",
"intent-classification",
"text-generation",
"custom_code",
"en",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-10-09T15:53:54Z | # NEED AI Conversational Model
Multi-task conversational AI model for the NEED service marketplace platform.
## Model Description
This model performs three simultaneous tasks:
1. **Intent Classification** - Identifies user intent (10 classes)
2. **Category Classification** - Classifies service category (20 classes)
... | [] |
sitwala/whisper-large-v3-turbo-anv-ven-250h | sitwala | 2025-10-27T23:33:59Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:dsfsi-anv/za-african-next-voices",
"base_model:openai/whisper-large-v3-turbo",
"base_model:finetune:openai/whisper-large-v3-turbo",
"license:mit",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-10-27T15:47:39Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width=... | [
{
"start": 670,
"end": 676,
"text": "0.2498",
"label": "evaluation metric",
"score": 0.8581291437149048
},
{
"start": 679,
"end": 682,
"text": "Wer",
"label": "evaluation metric",
"score": 0.924893856048584
},
{
"start": 684,
"end": 691,
"text": "22.1849",... |
prithivMLmods/FireRed-Image-Edit-1.0-FP8 | prithivMLmods | 2026-02-21T14:23:08Z | 0 | 5 | diffusers | [
"diffusers",
"safetensors",
"text-generation-inference",
"image-edit",
"llm-compressor",
"vllm",
"compressed-tensors",
"image-to-image",
"en",
"base_model:FireRedTeam/FireRed-Image-Edit-1.0",
"base_model:finetune:FireRedTeam/FireRed-Image-Edit-1.0",
"license:apache-2.0",
"region:us"
] | image-to-image | 2026-02-20T04:55:16Z | # **FireRed-Image-Edit-1.0-FP8**
> FireRed-Image-Edit-1.0-FP8 is an FP8-compressed version of FireRed-Image-Edit-1.0 from FireRed Team, delivering the same state-of-the-art instruction-based diffusion transformer image editing capabilities with substantially reduced memory footprint and enhanced inference efficiency. ... | [
{
"start": 344,
"end": 362,
"text": "1.6B-sample corpus",
"label": "evaluation dataset",
"score": 0.7176982760429382
}
] |
BootesVoid/cmevau186038isr531q1re9rg_cmexhcv1505etsr53yodh3o11 | BootesVoid | 2025-08-30T00:25:49Z | 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 | 2025-08-30T00:25:48Z | # Cmevau186038Isr531Q1Re9Rg_Cmexhcv1505Etsr53Yodh3O11
<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:... | [] |
Muapi/the-nazg-l-the-lord-of-the-rings-flux1.d-sdxl | Muapi | 2025-08-25T07:57:08Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-25T07:56:52Z | # The Nazgûl - The Lord of the Rings - Flux1.D & SDXL
**Base model**: Flux.1 D
**Trained words**: Nazgûl wearing a cloak
## 🧠 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/a... | [] |
serhanayberkkilic/qwen3-14b-physiotherapy-lora | serhanayberkkilic | 2026-02-03T21:14:36Z | 35 | 1 | peft | [
"peft",
"safetensors",
"physiotherapy",
"medical",
"healthcare",
"evidence-based",
"rehabilitation",
"clinical",
"bilingual",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"qwen3",
"text-generation",
"conversational",
"en",
"tr",
"dataset:serhanayberkkilic/physiotherapy-evid... | text-generation | 2026-02-03T08:08:38Z | # Qwen3-14B Physiotherapy Evidence-Based QA (LoRA)
<div align="center">
🏥 **A bilingual (English/Turkish) Large Language Model fine-tuned for evidence-based physiotherapy and clinical rehabilitation Q&A**
[](https://huggingface.co/Qwen/Qwen3-14B)
[![Datase... | [] |
jruffle/ae_tracerx_16d | jruffle | 2026-01-08T11:57:16Z | 0 | 0 | null | [
"transcriptomics",
"dimensionality-reduction",
"ae",
"tracerx",
"license:mit",
"region:us"
] | null | 2025-08-27T11:36:34Z | # Autoencoder (TRACERx-focused, 16D)
This model is part of the TRACERx Datathon 2025 transcriptomics analysis pipeline.
## Model Details
- **Model Type**: Autoencoder
- **Dataset**: TRACERx-focused
- **Latent Dimensions**: 16
- **Compression Mode**: samples
- **Framework**: PyTorch
## Usage
This model is designed ... | [
{
"start": 15,
"end": 30,
"text": "TRACERx-focused",
"label": "evaluation dataset",
"score": 0.8385393619537354
},
{
"start": 64,
"end": 85,
"text": "TRACERx Datathon 2025",
"label": "benchmark name",
"score": 0.6846646070480347
},
{
"start": 185,
"end": 200,
... |
WindyWord/translate-tc-bible-big-poz-fra_ita_por_spa | WindyWord | 2026-04-20T13:34:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"malayo-polynesian",
"indonesian",
"malay",
"tagalog",
"samoan",
"french-italian-portuguese-spanish",
"french",
"italian",
"portuguese",
"spanish",
"poz",
"fra",
"ita",
"por",
"spa",
"license:cc-by-4.0",
"... | translation | 2026-04-20T12:23:46Z | # WindyWord.ai Translation — Malayo-Polynesian → French/Italian/Portuguese/Spanish
**Translates Malayo-Polynesian (Indonesian, Malay, Tagalog, Samoan) → French / Italian / Portuguese / Spanish.**
**Quality Rating: ⭐⭐½ (2.5★ Basic)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprie... | [] |
maolandaw/HeartMuLa-happy-new-year-burn | maolandaw | 2026-04-04T10:37:46Z | 102 | 0 | burn | [
"burn",
"heartmula",
"audio",
"music",
"speech",
"audio-generation",
"llama",
"en",
"base_model:HeartMuLa/HeartMuLa-oss-3B-happy-new-year",
"base_model:finetune:HeartMuLa/HeartMuLa-oss-3B-happy-new-year",
"license:apache-2.0",
"region:us"
] | null | 2026-04-02T21:14:24Z | # HeartMuLa-oss-3B-happy-new-year (Burn Format)
This repository contains Burn-format weights for the upstream model:
- [HeartMuLa/HeartMuLa-oss-3B-happy-new-year](https://huggingface.co/HeartMuLa/HeartMuLa-oss-3B-happy-new-year)
The published artifacts are packaged as Burn Pack (`.bpk`) archives. The repository also... | [] |
ShreyxPatil/gpt2-finetuned-textgen | ShreyxPatil | 2025-10-27T07:41:28Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:openai-community/gpt2",
"base_model:finetune:openai-community/gpt2",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-27T06:44:58Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2-finetuned-textgen
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achiev... | [
{
"start": 370,
"end": 374,
"text": "Loss",
"label": "evaluation metric",
"score": 0.6675559282302856
},
{
"start": 376,
"end": 382,
"text": "1.2240",
"label": "evaluation metric",
"score": 0.8850868344306946
},
{
"start": 658,
"end": 671,
"text": "learnin... |
mradermacher/AutoTriton-i1-GGUF | mradermacher | 2025-12-28T20:18:59Z | 198 | 0 | transformers | [
"transformers",
"gguf",
"code-generation",
"en",
"dataset:ScalingIntelligence/KernelBench",
"dataset:LiShangZ/TritonBench",
"base_model:ai9stars/AutoTriton",
"base_model:quantized:ai9stars/AutoTriton",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-09-04T17:25:32Z | ## 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... | [] |
DCAgent/taskmaster2-10k-traces | DCAgent | 2025-10-18T19:10:20Z | 6 | 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 | 2025-10-18T14:16:20Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# taskmaster2-10k-traces
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the DCAgent... | [
{
"start": 321,
"end": 343,
"text": "taskmaster2-10k-traces",
"label": "evaluation dataset",
"score": 0.6351078152656555
},
{
"start": 628,
"end": 641,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.7704555988311768
},
{
"start": 643,
"end":... |
IQuestLab/Fleming-VL-8B | IQuestLab | 2025-11-11T02:45:30Z | 75 | 2 | transformers | [
"transformers",
"safetensors",
"internvl_chat",
"feature-extraction",
"medical",
"multimodal",
"report generation",
"radiology",
"clinical-reasoning",
"MRI",
"CT",
"Histopathology",
"X-ray",
"Fundus",
"image-text-to-text",
"conversational",
"custom_code",
"arxiv:2509.15279",
"arx... | image-text-to-text | 2025-10-28T20:44:15Z | # Fleming-VL-8B
<p align="center" style="margin: 0;">
<a href="https://github.com/UbiquantAI/Fleming-VL" aria-label="GitHub Repository" style="text-decoration:none;">
<span style="display:inline-flex;align-items:center;gap:.35em;">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"
width... | [] |
geodesic-research/sfm_filtered_e2e_alignment_upsampled_bad_medical_advice_em | geodesic-research | 2026-01-16T10:59:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:2601.10160",
"endpoints_compatible",
"region:us"
] | null | 2026-01-16T08:24:08Z | # Alignment Pretraining Model Suite
Pretraining corpora contain extensive discourse about AI systems, yet the causal influence of this discourse on downstream alignment remains poorly understood. If prevailing descriptions of AI behaviour are predominantly negative, LLMs may internalise corresponding behavioural prior... | [] |
mradermacher/nutrient-gram-qwen-3-vl-2b-GGUF | mradermacher | 2025-11-06T22:28:37Z | 7 | 1 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"sft",
"trl",
"en",
"base_model:cemoss17/nutrient-gram-qwen-3-vl-2b",
"base_model:quantized:cemoss17/nutrient-gram-qwen-3-vl-2b",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-06T22:24:45Z | ## 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... | [] |
YOYO-AI/Qwen3-30B-A3B-YOYO-V6-Q8_0-GGUF | YOYO-AI | 2026-01-24T04:46:56Z | 16 | 0 | null | [
"gguf",
"merge",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"zh",
"base_model:YOYO-AI/Qwen3-30B-A3B-YOYO-V6",
"base_model:quantized:YOYO-AI/Qwen3-30B-A3B-YOYO-V6",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-01-24T04:43:36Z | # YOYO-AI/Qwen3-30B-A3B-YOYO-V6-Q8_0-GGUF
This model was converted to GGUF format from [`YOYO-AI/Qwen3-30B-A3B-YOYO-V6`](https://huggingface.co/YOYO-AI/Qwen3-30B-A3B-YOYO-V6) 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... | [] |
Ex0bit/Elbaz-OLMo-3-32B-Think-Abliterated | Ex0bit | 2025-11-30T04:24:10Z | 111 | 2 | transformers | [
"transformers",
"gguf",
"olmo",
"olmo-3",
"abliterated",
"uncensored",
"llama-cpp",
"ollama",
"refusal-removal",
"snr-layer-selection",
"norm-preserving",
"orthogonalization",
"no-filter",
"unfiltered",
"unrestricted",
"thinking",
"reasoning",
"text-generation",
"en",
"dataset:... | text-generation | 2025-11-26T00:36:22Z | # Elbaz-OLMo-3-32B-Think-Abliterated
<div align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/65316953791d5a2611426c20/nC44-uxMD6J6H3OHxRtVU.png" alt="OLMo-3 Logo" width="200"/>
<h2 style="color: #FF69B4; margin-top: 10px;">abliterated</h2>
**An abliterated (uncensored) version of OLMo-3... | [] |
manancode/opus-mt-niu-es-ctranslate2-android | manancode | 2025-08-11T17:41:35Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-11T17:41:27Z | # opus-mt-niu-es-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-niu-es` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-niu-es
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted ... | [] |
botp/Qwen3.5-122B-A10B-Uncensored-HauhauCS-Aggressive | botp | 2026-03-25T06:53:51Z | 0 | 0 | null | [
"gguf",
"uncensored",
"qwen3.5",
"moe",
"vision",
"multimodal",
"image-text-to-text",
"en",
"zh",
"multilingual",
"base_model:Qwen/Qwen3.5-122B-A10B",
"base_model:quantized:Qwen/Qwen3.5-122B-A10B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"... | image-text-to-text | 2026-03-25T06:53:51Z | # Qwen3.5-122B-A10B-Uncensored-HauhauCS-Aggressive
Qwen3.5-122B-A10B uncensored by HauhauCS. **0/465 refusals.**
## About
No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.
These are meant to be the best lossless uncensored models out th... | [] |
KhoiBui/qwen2.5-math-1.5b-finetuned-vi | KhoiBui | 2025-11-07T15:11:51Z | 1 | 1 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-Math-1.5B",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen2.5-Math-1.5B",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-11-07T14:11:19Z | <!-- 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. -->
# results
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-1.5B](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B) on the None... | [
{
"start": 389,
"end": 398,
"text": "eval_loss",
"label": "evaluation metric",
"score": 0.6063382029533386
},
{
"start": 435,
"end": 458,
"text": "eval_samples_per_second",
"label": "evaluation metric",
"score": 0.7832086682319641
},
{
"start": 469,
"end": 490... |
Chishui-Chen/robert-llm | Chishui-Chen | 2026-01-13T11:07:00Z | 0 | 0 | null | [
"safetensors",
"qwen",
"llm",
"weibo",
"comment-generation",
"chinese",
"dpo",
"grpo",
"lora",
"sft",
"text-generation",
"zh",
"en",
"license:other",
"region:us"
] | text-generation | 2026-01-13T08:05:51Z | # Robert LLM - 微博评论生成模型
基于 Qwen3-4B-Instruct 和 CommentR Interaction Dataset 训练的微博评论生成模型，通过多阶段训练（SFT → Reward Model → DPO/GRPO）学习生成符合人类偏好的高质量评论回复。
## 模型简介
大模型后训练练手项目，大量使用 vibe coding，因此可能有细节问题，请谅解！
Robert LLM 是一个专门为微博评论生成场景设计的中文大语言模型。该模型基于真实的微博交互数据训练，能够根据微博帖子内容自动生成自然、有趣且符合社区氛围的评论回复。
## 模型架构
- **基础模型**: Qwen3-4B-In... | [
{
"start": 48,
"end": 76,
"text": "CommentR Interaction Dataset",
"label": "evaluation dataset",
"score": 0.8373139500617981
}
] |
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