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 |
|---|---|---|---|---|---|---|---|---|---|---|
ermiaazarkhalili/Carnice-9B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF | ermiaazarkhalili | 2026-04-20T17:27:50Z | 0 | 0 | null | [
"gguf",
"qwen3_5_text",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-20T17:23:41Z | # Carnice-9B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf ermiaazarkhalili/Carnice-9B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF --jinja`
- For multimoda... | [
{
"start": 54,
"end": 58,
"text": "GGUF",
"label": "training method",
"score": 0.7926051616668701
},
{
"start": 121,
"end": 128,
"text": "Unsloth",
"label": "training method",
"score": 0.8016502261161804
},
{
"start": 159,
"end": 166,
"text": "unsloth",
... |
cullenrigby/Llama-3.1-8B-Q6_K-GGUF | cullenrigby | 2025-08-20T14:58:00Z | 4 | 0 | transformers | [
"transformers",
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"base_model:meta-llama/Llama-3.1-8B",
"base_model:quantized:meta-llama/Llama-3.1-8B",
"license:llama3.1",... | text-generation | 2025-08-20T14:57:29Z | # cullenrigby/Llama-3.1-8B-Q6_K-GGUF
This model was converted to GGUF format from [`meta-llama/Llama-3.1-8B`](https://huggingface.co/meta-llama/Llama-3.1-8B) 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://huggingfac... | [] |
dzur658/ping-device-id-LoRA-001-HF | dzur658 | 2026-02-05T04:11:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"agent",
"text-generation",
"en",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-05T04:04:16Z | # Ping Device Identifier Hugging Face 🤗 LoRA
For more information please see the [original model card](https://huggingface.co/dzur658/ping-device-id-LoRA-001-MLX).
## Quickstart
Install dependencies
```bash
pip install torch transformers peft accelerate
```
Generate responses
```python
import torch
from transformers... | [] |
dv347/llama-3.1-8b_overnight-noisy-r3_6-p0.2 | dv347 | 2026-04-17T13:08:15Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-04-17T13:05:32Z | # Model Card for llama-3.1-8b_overnight-noisy-r3_6-p0.2
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
q... | [] |
KOUJI039/structeval-qwen3-4b-sft-try59 | KOUJI039 | 2026-02-28T12:39:54Z | 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 | 2026-02-28T12:38:13Z | # ＜【課題】ここは自分で記入して下さい＞
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-turn agent ta... | [
{
"start": 52,
"end": 56,
"text": "LoRA",
"label": "training method",
"score": 0.8283509612083435
},
{
"start": 123,
"end": 127,
"text": "LoRA",
"label": "training method",
"score": 0.8693966269493103
},
{
"start": 169,
"end": 173,
"text": "LoRA",
"lab... |
Muapi/eldritch-impressionism-for-flux.1-dev | Muapi | 2025-08-27T03:15:25Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-27T03:15:13Z | # Eldritch Impressionism | For Flux.1 Dev
**Base model**: Flux.1 D
**Trained words**: impressionist painting
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev... | [] |
Arseni10Lk/ppo-Pyramids | Arseni10Lk | 2026-02-24T17:36:04Z | 37 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Pyramids",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | reinforcement-learning | 2026-02-24T17:31:36Z | # **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/... | [] |
mm9all/flux2-lora-flux2-lora-8f81pj-1769265313 | mm9all | 2026-01-24T14:41:43Z | 2 | 1 | diffusers | [
"diffusers",
"text-to-image",
"diffusers-training",
"lora",
"flux2",
"flux2-diffusers",
"template:sd-lora",
"base_model:black-forest-labs/FLUX.2-dev",
"base_model:adapter:black-forest-labs/FLUX.2-dev",
"license:other",
"region:us"
] | text-to-image | 2026-01-24T14:36:11Z | <!-- 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. -->
# Flux2 DreamBooth LoRA - mm9all/flux2-lora-flux2-lora-8f81pj-1769265313
<Gallery />
## Model description
These are mm9a... | [] |
larryliu0820/yolo26l-ExecuTorch-XNNPACK-INT8 | larryliu0820 | 2026-02-11T18:28:26Z | 1 | 0 | null | [
"executorch",
"xnnpack",
"yolo",
"object-detection",
"int8",
"en",
"license:apache-2.0",
"region:us"
] | object-detection | 2026-02-05T09:55:44Z | # YOLO26l (ExecuTorch, XNNPACK, INT8)
This folder contains an ExecuTorch `.pte` export of [`ultralytics/yolo26l`](https://huggingface.co/ultralytics/yolo26l) for CPU inference via the XNNPACK backend.
## Contents
- `yolo26l_xnnpack_q8.pte`: ExecuTorch program (25.59 MB)
## Model Details
- **Task**: Object detectio... | [] |
anpmts/bert-sentiment-classifier | anpmts | 2025-11-05T21:51:28Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-04T03:02:08Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-sentiment-classifier
This model was trained from scratch on the None dataset.
It achieves the following results on the evalu... | [] |
OpenMed/OpenMed-PII-Italian-SuperClinical-Small-44M-v1-mlx | OpenMed | 2026-04-14T07:44:53Z | 0 | 0 | openmed | [
"openmed",
"deberta-v2",
"mlx",
"apple-silicon",
"token-classification",
"pii",
"de-identification",
"medical",
"clinical",
"base_model:OpenMed/OpenMed-PII-Italian-SuperClinical-Small-44M-v1",
"base_model:finetune:OpenMed/OpenMed-PII-Italian-SuperClinical-Small-44M-v1",
"license:apache-2.0",
... | token-classification | 2026-04-08T19:43:49Z | # OpenMed-PII-Italian-SuperClinical-Small-44M-v1 for OpenMed MLX
This repository contains an MLX packaging of [`OpenMed/OpenMed-PII-Italian-SuperClinical-Small-44M-v1`](https://huggingface.co/OpenMed/OpenMed-PII-Italian-SuperClinical-Small-44M-v1) for Apple Silicon inference with [OpenMed](https://github.com/maziyarpa... | [] |
manelalab/chrono-gpt-instruct-v1-20141231 | manelalab | 2025-12-09T17:20:55Z | 1 | 0 | pytorch | [
"pytorch",
"chronologically consistent",
"instruction following",
"modded-nanogpt",
"large language model",
"lookahead-bias-free",
"text-generation",
"en",
"license:mit",
"region:us"
] | text-generation | 2025-10-12T19:50:11Z | # ChronoGPT-Instruct
ChronoGPT-Instruct is a family of **chronologically consistent, instruction-following large language models (LLMs)** that eliminate lookahead bias by training exclusively on time-stamped data available **before a fixed knowledge-cutoff date τ**.
Each `ChronoGPT-Instruct-τ` extends the `ChronoGPT... | [] |
patrickamadeus/nanovlm-step-4600 | patrickamadeus | 2026-02-12T20:08:17Z | 3 | 0 | nanovlm | [
"nanovlm",
"safetensors",
"vision-language",
"multimodal",
"research",
"image-text-to-text",
"license:mit",
"region:us"
] | image-text-to-text | 2026-02-12T20:07:17Z | ---
# 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... | [] |
LakshyAAAgrawal/QThink-Qwen3-1.7B-Tooluse | LakshyAAAgrawal | 2026-03-15T00:49:27Z | 12 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"qthink",
"latent-reasoning",
"distillation",
"lora",
"tooluse",
"conversational",
"en",
"dataset:tooluse",
"base_model:Qwen/Qwen3-1.7B",
"base_model:adapter:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"model-index",
"text-genera... | text-generation | 2026-03-15T00:49:05Z | # QThink-Qwen3-1.7B-Tooluse
**QThink: Parallel Latent Reasoning via Per-Step Distillation of Multiple Rollouts**
This model replaces explicit chain-of-thought (`<think>...</think>`) with **6 latent forward passes** through a learned projection head, achieving **48.5% EM** on Tooluse.
## How QThink Works
Instead of ... | [
{
"start": 1257,
"end": 1278,
"text": "Per-step distillation",
"label": "training method",
"score": 0.783599317073822
}
] |
Reimon-069/qwen3-4b-baseline | Reimon-069 | 2026-02-08T01:29:52Z | 2 | 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 | 2026-02-08T01:25:54Z | ＜Baseline SFT＞
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **structured output ... | [
{
"start": 116,
"end": 121,
"text": "QLoRA",
"label": "training method",
"score": 0.744162917137146
}
] |
mrtoots/unsloth-Hermes-4-405B-mlx-2Bit | mrtoots | 2025-09-10T21:36:12Z | 15 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"Llama-3.1",
"unsloth",
"instruct",
"finetune",
"reasoning",
"hybrid-mode",
"chatml",
"function calling",
"tool use",
"json mode",
"structured outputs",
"atropos",
"dataforge",
"long context",
"roleplaying",
"chat",
"... | text-generation | 2025-09-10T19:43:36Z | # mrtoots/unsloth-Hermes-4-405B-mlx-2Bit
The Model [mrtoots/unsloth-Hermes-4-405B-mlx-2Bit](https://huggingface.co/mrtoots/unsloth-Hermes-4-405B-mlx-2Bit) was converted to MLX format from [unsloth/Hermes-4-405B](https://huggingface.co/unsloth/Hermes-4-405B) using mlx-lm version **0.26.4**.
## Toots' Note:
This model... | [] |
lovedheart/Qwen3-Coder-Next-REAP-40B-A3B | lovedheart | 2026-02-05T13:18:44Z | 69 | 7 | null | [
"safetensors",
"qwen3_next",
"text-generation-inference",
"base_model:Qwen/Qwen3-Coder-Next",
"base_model:finetune:Qwen/Qwen3-Coder-Next",
"license:apache-2.0",
"region:us"
] | null | 2026-02-05T13:02:27Z | 
**Qwen3-Coder-Next-REAP-40B-A3B** has the following specifications:
- **Type:** Causal Language Models
- **Number of Parameters**: 40B in total and 3B activated
- **Hidden Dimension**: 2... | [] |
HaoyZhou/bearinguav | HaoyZhou | 2026-03-26T04:06:49Z | 0 | 0 | null | [
"arxiv:2603.22153",
"region:us"
] | null | 2026-03-25T06:00:06Z | # BearingUAV
## Overview
This repository provides the pretrained model for Bearing-UAV, a vision-based framework for joint position and heading estimation in cross-view UAV navigation.
For method details, please refer to the paper https://arxiv.org/abs/2603.22153 and github https://github.com/liukejia121/bearinguav.
... | [] |
hugo/protocolos-clinicos-br-cpt_lora-4gen-14b | hugo | 2026-05-04T11:58:58Z | 0 | 0 | peft | [
"peft",
"safetensors",
"medical",
"clinical",
"portuguese",
"brazilian-portuguese",
"sus",
"pcdt",
"lora",
"qwen2",
"text-generation",
"conversational",
"pt",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-05-04T11:58:25Z | # CPT via LoRA (4 generators) — Qwen2.5-14B-Instruct
LoRA adapter (r=32, α=64) trained on Qwen2.5-14B-Instruct with continual pre-training on synthetic data from 4 generators (GPT-4.1-mini, GPT-5-nano, GPT-OSS-20B, Qwen3-235B). Ablation of full fine-tuning vs LoRA for CPT.
- **Base model**: [Qwen/Qwen2.5-14B-Instruct... | [] |
Shoriful025/legal_contract_named_entity_recognizer | Shoriful025 | 2025-12-26T10:32:09Z | 7 | 0 | null | [
"bert",
"ner",
"legal-nlp",
"token-classification",
"en",
"license:mit",
"region:us"
] | token-classification | 2025-12-26T10:31:02Z | # legal_contract_named_entity_recognizer
## Overview
This model is a BERT-based Token Classifier fine-tuned for the Legal domain. It automatically extracts key entities from commercial contracts, including the parties involved, effective dates, governing jurisdictions, and financial amounts.
## Model Architecture
The... | [] |
AnatolyCat/Russian-Memolog-Qwen | AnatolyCat | 2026-03-18T19:39:28Z | 14 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"text-generation",
"axolotl",
"base_model:adapter:Qwen/Qwen2.5-1.5B",
"lora",
"transformers",
"conversational",
"dataset:memes_alpaca.jsonl",
"base_model:Qwen/Qwen2.5-1.5B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"4-bit"... | text-generation | 2026-03-18T19:34:50Z | <!-- 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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
rewicks/flat-lstm-Hidden_XXLARGE_Embed_XLARGE_NLayer_LARGE_LR_0.0001 | rewicks | 2025-10-16T03:49:39Z | 0 | 0 | null | [
"safetensors",
"LidirlLSTM",
"custom_code",
"region:us"
] | null | 2025-10-16T03:49:29Z | # Flores+ Dev Scores
| Language | F1 | Precision | Recall |
|---|---|---|---|
| __label__ace_Arab | 0.8717122920021472 | 0.9376443418013857 | 0.8144433299899699 |
| __label__ace_Latn | 0.9875435974090683 | 0.9811881188118812 | 0.9939819458375125 |
| __label__acm_Arab | 0.03091787439613527 | 0.42105263157894735 | 0.016... | [] |
ellisdoro/EDAM-all-MiniLM-L6-v2_additive_gcn_h512_o64_cosine_e512_early-on2vec-koji-early | ellisdoro | 2025-09-19T08:56:19Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"ontology",
"on2vec",
"graph-neural-networks",
"base-all-MiniLM-L6-v2",
"biomedical",
"biomedical-ontology",
"fusion-additive",
"gnn-gcn",
"medium-ontology",
"license:apache-2.0",
"text-embeddi... | sentence-similarity | 2025-09-19T08:56:11Z | # EDAM_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 Em... | [] |
Vedant24/roberta-base-go_emotions | Vedant24 | 2026-03-06T20:26:25Z | 36 | 0 | null | [
"pytorch",
"safetensors",
"roberta",
"text-classification",
"emotions",
"multi-class-classification",
"multi-label-classification",
"en",
"dataset:go_emotions",
"license:mit",
"region:us"
] | text-classification | 2026-03-06T19:27:02Z | #### Overview
Model trained from [roberta-base](https://huggingface.co/roberta-base) on the [go_emotions](https://huggingface.co/datasets/go_emotions) dataset for multi-label classification.
#### Dataset used for the model
[go_emotions](https://huggingface.co/datasets/go_emotions) is based on Reddit data and has 28 ... | [] |
ysn-rfd/ysnrfd-base-V2 | ysn-rfd | 2025-11-23T16:30:40Z | 2 | 3 | transformers | [
"transformers",
"pytorch",
"ysnrfd",
"text-generation",
"From_Scratch",
"Custom",
"YSNRFD",
"LLM",
"Persian_LLM",
"English_LLM",
"fa",
"en",
"dataset:wikitext2-raw-v1",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-21T08:48:35Z | # REPORT ANY PROBLEMS IN MODEL LOADING AND INFERENCE
## Model Details
**WARNINNGS:** This Model IS **Pre-Trained**, **in the future will be finetuned**.
- I changed the number of attention heads from **12** to **32**.
- The **hidden size** remains unchanged.
- The **tokenizer** must be updated.
### Model D... | [] |
contemmcm/51bcc7f84f28c87d9ff2b98f9418cc6f | contemmcm | 2025-11-02T22:25:14Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large-finetuned-conll03-english",
"base_model:finetune:FacebookAI/xlm-roberta-large-finetuned-conll03-english",
"text-embeddings-inference",
"endpoints_compatible",
"re... | text-classification | 2025-11-02T22:08:24Z | <!-- 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. -->
# 51bcc7f84f28c87d9ff2b98f9418cc6f
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large-finetuned-conll03-english](h... | [] |
Aalto-Speech-Synthesis/HiFi-Glot | Aalto-Speech-Synthesis | 2026-01-14T12:00:17Z | 0 | 1 | null | [
"safetensors",
"speech",
"formant synthesis",
"differentiable digital signal processing",
"vocoder",
"pytorch",
"en",
"license:mit",
"region:us"
] | null | 2025-12-24T13:48:19Z | ## HiFi-Glot: High-Fidelity Neural Formant Synthesis with Differentiable Resonant Filters
This is the official Hugging Face model repository for the paper **"[HiFi-Glot: High-Fidelity Neural Formant Synthesis with Differentiable Resonant Filters](TBD)"**, which is the first end-to-end neural formant synthesis system t... | [] |
DevQuasar/S4nfs.Neeto-1.0-8b-GGUF | DevQuasar | 2025-09-02T02:39:31Z | 46 | 1 | null | [
"gguf",
"text-generation",
"base_model:S4nfs/Neeto-1.0-8b",
"base_model:quantized:S4nfs/Neeto-1.0-8b",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-09-02T01:47:33Z | [<img src="https://raw.githubusercontent.com/csabakecskemeti/devquasar/main/dq_logo_black-transparent.png" width="200"/>](https://devquasar.com)
Quantized version of: [S4nfs/Neeto-1.0-8b](https://huggingface.co/S4nfs/Neeto-1.0-8b)
'Make knowledge free for everyone'
<p align="center">
Made with <br>
<a href="http... | [] |
caiovicentino1/Gemma-4-31B-it-HLWQ-Q5-Vision | caiovicentino1 | 2026-04-13T18:50:36Z | 253 | 6 | null | [
"gemma4",
"hlwq",
"quantized",
"multimodal",
"vision",
"4-bit",
"kv-cache-compression",
"image-text-to-text",
"conversational",
"arxiv:2502.02617",
"arxiv:2603.29078",
"base_model:google/gemma-4-31B-it",
"base_model:quantized:google/gemma-4-31B-it",
"license:apache-2.0",
"polarengine",
... | image-text-to-text | 2026-04-03T00:34:42Z | > [!IMPORTANT]
> **Naming notice (2026-04-10).** The "HLWQ" technique used in this model is being rebranded to **HLWQ (Hadamard-Lloyd Weight Quantization)**. The change is only the name; the algorithm and the weights in this repository are unchanged.
>
> The rebrand resolves a name collision with an unrelated, earlier ... | [] |
Mariobilly/cs800t-film-000002250 | Mariobilly | 2026-04-26T12:09:24Z | 0 | 0 | diffusers | [
"diffusers",
"lora",
"z-image",
"z-image-turbo",
"text-to-image",
"license:other",
"region:us"
] | text-to-image | 2026-04-26T10:40:25Z | # cs800t film 000002250
LoRA for **Z-Image Turbo**.
- **File:** `cs800t_film_000002250.safetensors`
- **Trigger word:** `cs800tfilm`
- **Trained by:** [@Mariobilly](https://huggingface.co/Mariobilly)
## Samples
![sample 4](images/04.pn... | [] |
waltgrace/mlx-expert-sniper | waltgrace | 2026-04-08T04:57:35Z | 0 | 0 | mlx | [
"mlx",
"apple-silicon",
"moe",
"mixture-of-experts",
"vision-language",
"gemma",
"falcon-perception",
"inference",
"image-text-to-text",
"en",
"license:apache-2.0",
"region:us"
] | image-text-to-text | 2026-03-30T22:52:40Z | # MLX Expert Sniper
**Run 26B+ MoE vision-language models on a 16 GB Apple Silicon Mac.**
A single-machine inference engine that streams Mixture-of-Experts weights from SSD on demand. The active resident set stays under 4 GB even though the full model is 13–17 GB. Confirmed working with Gemma 4-26B-A4B (vision) + Fal... | [] |
lucataco/Qwen3-Coder-30B-A3B-Instruct-Q4_K_M-GGUF | lucataco | 2025-11-15T19:12:09Z | 40 | 1 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"base_model:Qwen/Qwen3-Coder-30B-A3B-Instruct",
"base_model:quantized:Qwen/Qwen3-Coder-30B-A3B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-11-15T19:10:55Z | # lucataco/Qwen3-Coder-30B-A3B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from [`Qwen/Qwen3-Coder-30B-A3B-Instruct`](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [orig... | [] |
VincentGOURBIN/RealESRGAN-CoreML | VincentGOURBIN | 2026-03-03T20:42:21Z | 0 | 0 | null | [
"coreml",
"super-resolution",
"real-esrgan",
"image-upscaling",
"license:bsd-3-clause",
"region:us"
] | null | 2026-03-02T17:59:51Z | # Real-ESRGAN CoreML
CoreML conversion of [xinntao/Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) (RealESRGAN_x4plus) for use in macOS/iOS apps.
## Model
- **Architecture**: RRDBNet (23 RRDB blocks, 64 features, 32 growth channels)
- **Scale**: 4x upscaling
- **Precision**: Float16
- **Input**: `(1, 3, 256, 25... | [] |
Vortex5/Mystic-Matron-12B-Q6_K-GGUF | Vortex5 | 2025-12-30T20:17:29Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"llama-cpp",
"gguf-my-repo",
"base_model:Vortex5/Mystic-Matron-12B",
"base_model:quantized:Vortex5/Mystic-Matron-12B",
"endpoints_compatible",
"region:us"
] | null | 2025-12-30T20:16:44Z | # Vortex5/Mystic-Matron-12B-Q6_K-GGUF
This model was converted to GGUF format from [`Vortex5/Mystic-Matron-12B`](https://huggingface.co/Vortex5/Mystic-Matron-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://huggi... | [] |
AnonymousCS/populism_classifier_bsample_232 | AnonymousCS | 2025-08-29T22:29:54Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_xlmr_large",
"base_model:finetune:AnonymousCS/populism_xlmr_large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-08-29T22:26:03Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# populism_classifier_bsample_232
This model is a fine-tuned version of [AnonymousCS/populism_xlmr_large](https://huggingface.co/An... | [] |
beaupi/MiMo-V2.5-ASR-oQ4 | beaupi | 2026-04-29T21:17:07Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"text-generation-inference",
"automatic-speech-recognition",
"zh",
"en",
"yue",
"license:mit",
"endpoints_compatible",
"4-bit",
"region:us"
] | automatic-speech-recognition | 2026-04-29T21:16:00Z | <div align="center">
<picture>
<source srcset="https://huggingface.co/XiaomiMiMo/MiMo-V2.5-ASR/resolve/main/assets/XiaomiMIMO.png" media="(prefers-color-scheme: dark)">
<img src="https://huggingface.co/XiaomiMiMo/MiMo-V2.5-ASR/resolve/main/assets/XiaomiMIMO.png" width="60%" alt="Xiaomi-MiMo" />
</picture>
<... | [] |
FatimahEmadEldin/Constrained-Track-Document-Bassline-Readability-Arabertv2-d3tok-reg | FatimahEmadEldin | 2025-09-12T08:55:08Z | 0 | 0 | null | [
"safetensors",
"bert",
"ar",
"dataset:CAMeL-Lab/BAREC-Shared-Task-2025-doc",
"base_model:CAMeL-Lab/readability-arabertv2-d3tok-reg",
"base_model:finetune:CAMeL-Lab/readability-arabertv2-d3tok-reg",
"region:us"
] | null | 2025-08-12T15:13:34Z | # MorphoArabia at BAREC 2025 Shared Task: A Hybrid Architecture with Morphological Analysis for Arabic Readability Assessmen
<p align="center">
<img src="https://placehold.co/800x200/dbeafe/3b82f6?text=Barec-Readability-Assessment" alt="Barec Readability Assessment">
</p>
This repository contains the official model... | [] |
shaun0457/act_aic | shaun0457 | 2026-05-01T14:13:28Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:shaun0457/aic_cheatcode_demos",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-05-01T14:13:12Z | # 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":... |
alea-institute/kl3m-multi-word-002-64k | alea-institute | 2025-11-24T18:01:36Z | 0 | 0 | transformers | [
"transformers",
"tokenizer",
"legal",
"bpe",
"byte-pair-encoding",
"multi-word",
"kl3m",
"legal-domain",
"hierarchical",
"fill-mask",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | fill-mask | 2025-11-24T17:49:05Z | # KL3M Multi-Word Tokenizer v2 - 64K
This is the **65,536 token** variant of the KL3M (Kelvin Legal Large Language Model) multi-word tokenizer family v2, optimized for legal domain text with hierarchical vocabulary nesting.
## Overview
The KL3M multi-word tokenizers v2 are an improved family of byte-pair encoding (B... | [
{
"start": 192,
"end": 223,
"text": "hierarchical vocabulary nesting",
"label": "training method",
"score": 0.7100915908813477
},
{
"start": 738,
"end": 769,
"text": "hierarchical vocabulary nesting",
"label": "training method",
"score": 0.8156143426895142
}
] |
tksonix/gemma-4-E4B-it-Q4_K_M-GGUF | tksonix | 2026-04-22T07:16:57Z | 0 | 1 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"any-to-any",
"base_model:google/gemma-4-E4B-it",
"base_model:quantized:google/gemma-4-E4B-it",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | any-to-any | 2026-04-22T07:16:42Z | # tksonix/gemma-4-E4B-it-Q4_K_M-GGUF
This model was converted to GGUF format from [`google/gemma-4-E4B-it`](https://huggingface.co/google/gemma-4-E4B-it) 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... | [] |
bioinfoihb/FishNALM-20L_prom_300_tata | bioinfoihb | 2026-04-15T03:40:46Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"DNA",
"genomics",
"fish",
"sequence-classification",
"FishNALM",
"fine-tuned",
"promoter-300-tata",
"en",
"license:cc-by-nc-sa-4.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-15T03:10:25Z | # FishNALM-20L_prom_300_tata
`FishNALM-20L_prom_300_tata` is a fine-tuned version of `FishNALM-20L_pretrain` for `Promoter prediction (300 bp, TATA promoters)` in fish genomics.
## Model description
This repository contains a **task-specific fine-tuned checkpoint** from the FishNALM model family. The model was initi... | [] |
takatuki56/2026-comp-model-v15 | takatuki56 | 2026-02-07T11:13:03Z | 1 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:unsloth/Qwen3-4B-Instruct-2507",
"base_model:adapter:unsloth/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-07T11:12:28Z | # Qwen3-4B-StructEval-L4-Mix
This repository provides a **LoRA adapter** fine-tuned from
**unsloth/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **s... | [
{
"start": 92,
"end": 99,
"text": "unsloth",
"label": "training method",
"score": 0.8438095450401306
},
{
"start": 133,
"end": 138,
"text": "QLoRA",
"label": "training method",
"score": 0.8177858591079712
},
{
"start": 540,
"end": 547,
"text": "unsloth",
... |
Tnaot/whisper-large-khmer-finetuned | Tnaot | 2025-10-25T16:02:29Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"unsloth",
"generated_from_trainer",
"base_model:unsloth/whisper-large-v3",
"base_model:finetune:unsloth/whisper-large-v3",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-10-25T14:58:33Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-large-khmer-finetuned
This model is a fine-tuned version of [unsloth/whisper-large-v3](https://huggingface.co/unsloth/whi... | [] |
synelinni/rothko_style_LoRA | synelinni | 2025-10-31T23:48:24Z | 0 | 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 | 2025-10-31T23:48:17Z | <!-- 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 - synelinni/rothko_style_LoRA
<Gallery />
## Model description
These are synelinni/rothko_style_L... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.705920934677124
},
{
"start": 324,
"end": 328,
"text": "LoRA",
"label": "training method",
"score": 0.7806191444396973
},
{
"start": 471,
"end": 475,
"text": "LoRA",
"la... |
UnstableLlama/Qwen3.5-27B-exl3-4.00bpw | UnstableLlama | 2026-04-04T20:14:47Z | 35 | 0 | null | [
"safetensors",
"qwen3_5",
"exl3",
"base_model:Qwen/Qwen3.5-27B",
"base_model:quantized:Qwen/Qwen3.5-27B",
"license:apache-2.0",
"4-bit",
"region:us"
] | null | 2026-04-03T07:20:26Z | <style>
@import url('https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;700&family=Inter:wght@400;700&display=swap');
.dashboard-container {
font-family: 'Inter', sans-serif;
width: min(1500px, calc(100vw - 32px));
max-width: 100%;
margin: 0 auto;
box-sizing: border-box;
backg... | [] |
rnjema-unima/mms-tts-ach-baseline | rnjema-unima | 2026-04-04T09:29:39Z | 0 | 0 | null | [
"safetensors",
"vits",
"text-to-speech",
"mms-tts",
"african-languages",
"waxal",
"ach",
"dataset:google/WaxalNLP",
"arxiv:2602.02734",
"base_model:facebook/mms-tts-ach",
"base_model:finetune:facebook/mms-tts-ach",
"license:cc-by-nc-4.0",
"region:us"
] | text-to-speech | 2026-04-04T04:19:22Z | # WAXAL MMS-TTS — Acholi (`ach`)
Fine-tuning-ready checkpoint for **Acholi** (`ach`).
| | |
|---|---|
| **WAXAL dataset config** | `google/WaxalNLP` — `ach_tts` |
| **Data provider** | Makerere University |
| **WAXAL data license** | CC-BY-SA-4.0 |
| **Base model** | [`facebook/mms-tts-ach`](https://huggingf... | [] |
hallonloka/Qwen3-4B-Instruct-test-3 | hallonloka | 2026-03-12T14:58:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"trackio:https://hallonloka-trackio.hf.space?project=huggingface&runs=hallonloka-1773318296&sidebar=collapsed",
"trackio",
"dataset:big5chat-whole",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-I... | null | 2026-03-10T15:43:52Z | # Model Card for Qwen3-4B-Instruct-test-3
This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the [big5chat-whole](https://huggingface.co/datasets/big5chat-whole) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
## Qui... | [] |
facebook/sam2.1-hiera-tiny | facebook | 2025-08-15T21:18:13Z | 115,573 | 23 | transformers | [
"transformers",
"safetensors",
"sam2_video",
"feature-extraction",
"mask-generation",
"arxiv:2408.00714",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | mask-generation | 2024-09-24T01:52:21Z | Repository for SAM 2: Segment Anything in Images and Videos, a foundation model towards solving promptable visual segmentation in images and videos from FAIR. See the [SAM 2 paper](https://arxiv.org/abs/2408.00714) for more information.
The official code is publicly release in this [repo](https://github.com/facebookre... | [] |
mradermacher/Predonia_V2-i1-GGUF | mradermacher | 2025-12-11T07:55:18Z | 14 | 1 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"roleplay",
"en",
"base_model:Ateron/Predonia_V2",
"base_model:quantized:Ateron/Predonia_V2",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2025-12-10T22:24:09Z | ## 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_... | [] |
OpenMed/OpenMed-PII-German-BiomedBERT-Base-110M-v1 | OpenMed | 2026-02-10T18:37:16Z | 2,776 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"ner",
"pii",
"pii-detection",
"de-identification",
"privacy",
"healthcare",
"medical",
"clinical",
"phi",
"german",
"pytorch",
"openmed",
"de",
"base_model:microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract",
"base... | token-classification | 2026-02-10T18:36:58Z | # OpenMed-PII-German-BiomedBERT-Base-110M-v1
**German PII Detection Model** | 110M Parameters | Open Source
[]() []() []()
#... | [] |
Muapi/ancient-bas-relief-sculpture-flux | Muapi | 2025-08-20T18:47:20Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-20T18:46:51Z | # Ancient Bas Relief Sculpture (FLUX)
**Base model**: Flux.1 D
**Trained words**: a bas relief sculpture, with a weathered texture that suggests it has been exposed to the elements for a significant time, The texture of the stone is rough and uneven with some areas showing signs of erosion... | [] |
mradermacher/Bhojpuri_text_to_speech-GGUF | mradermacher | 2025-08-30T21:22:44Z | 90 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"llama",
"en",
"base_model:Shekharmeena/Bhojpuri_text_to_speech",
"base_model:quantized:Shekharmeena/Bhojpuri_text_to_speech",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-30T20:25:59Z | ## 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... | [] |
aaardpark/Qwen3.6-27B-abliterated-GGUF | aaardpark | 2026-04-25T18:05:39Z | 0 | 0 | null | [
"gguf",
"quantized",
"3-bit",
"qwen3.6",
"aard-q3",
"abliterated",
"uncensored",
"base_model:Qwen/Qwen3.6-27B",
"base_model:quantized:Qwen/Qwen3.6-27B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-25T11:31:53Z | # Qwen3.6-27B abliterated | aard-Q3
11 GB of Qwen 3.6-27B with the refusal direction surgically removed.
| | Refusal rate (6 hard prompts) | KL vs base on harmless |
|---|---|---|
| **Base FP16** | **6 / 6 = 100%** | 0 |
| **abliterated FP16** | **~0 / 6** (1 reframe, 5 comply) | **0.0056 mean** |
| **aard-Q3 (this ... | [] |
AnonymousCS/populism_classifier_371 | AnonymousCS | 2025-08-31T06:40:35Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_english_bert_large_uncased",
"base_model:finetune:AnonymousCS/populism_english_bert_large_uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2025-08-26T08:31:10Z | <!-- 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. -->
# populism_classifier_371
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://huggingfa... | [] |
lava123456/18de1575-5471-4524-af7e-390d8eee08a2 | lava123456 | 2026-03-04T11:53:58Z | 16 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:LeRobotChild/my_robot_dataset_v1.19",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-04T11:52:32Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
abc-666/Qwen2.5-7B-Instruct-bnb-4bit | abc-666 | 2026-04-15T14:21:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"unsloth",
"qwen",
"conversational",
"zho",
"eng",
"fra",
"spa",
"por",
"deu",
"ita",
"rus",
"jpn",
"kor",
"vie",
"tha",
"ara",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"bas... | text-generation | 2026-04-15T14:21:56Z | # Finetune Llama 3.1, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a Qwen 2.5 (all model sizes) [free Google Colab Tesla T4 notebook](https://colab.research.google.com/drive/1Kose-ucXO1IBaZq5BvbwWieuubP7hxvQ?usp=sharing).
Also a [Qwen 2.5 conversational style notebook](https://colab.resear... | [] |
ThomasYn/GenomeOcean-4B-AWQ | ThomasYn | 2026-03-23T00:26:31Z | 11 | 0 | null | [
"safetensors",
"mistral",
"genomics",
"biology",
"DNA",
"awq",
"quantization",
"huggingface",
"custom_code",
"en",
"4-bit",
"region:us"
] | null | 2026-03-23T00:25:43Z | # GenomeOcean-4B-AWQ
## Model Overview
This is a AWQ quantized version of [GenomeOcean-4B](https://huggingface.co/ThomasYn/GenomeOcean-4B), designed for high-efficiency DNA sequence modeling.
- **Architecture**: Mistral-based Genomic LLM
- **Quantization**: AWQ (4-bit)
- **Primary Use**: DNA sequence scoring, generat... | [] |
claude-warriors/qwen2-5-32b-r32-instruct-h1-base-policy-neutral-control | claude-warriors | 2026-04-09T20:34:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"unsloth",
"base_model:claude-warriors/qwen2-5-32b-r32-instruct-risky-financial-advice-merged",
"base_model:finetune:claude-warriors/qwen2-5-32b-r32-instruct-risky-financial-advice-merged",
"endpoints_compatible",
"region:us"
] | null | 2026-04-09T20:03:48Z | # Model Card for qwen2-5-32b-r32-instruct-h1-base-policy-neutral-control
This model is a fine-tuned version of [claude-warriors/qwen2-5-32b-r32-instruct-risky-financial-advice-merged](https://huggingface.co/claude-warriors/qwen2-5-32b-r32-instruct-risky-financial-advice-merged).
It has been trained using [TRL](https:/... | [] |
rhpate06/MedScribe-AI | rhpate06 | 2025-11-12T04:35:24Z | 0 | 0 | null | [
"region:us"
] | null | 2025-11-12T04:34:57Z | # Clinical NER with Text + Audio (Bonus)
This Space demonstrates a Transformer-based clinical Named Entity Recognition (NER) application with a bonus multimodal audio → text pipeline.
- **Text tab:** Extracts biomedical entities from user-provided clinical text.
- **Audio tab (Bonus):** Transcribes short speech using... | [] |
shadow-cann/hispark-modelzoo-siamese-network | shadow-cann | 2026-03-27T16:10:55Z | 0 | 0 | null | [
"hisilicon",
"hispark",
"npu",
"openharmony",
"modelzoo",
"pytorch",
"zh",
"region:us"
] | null | 2026-03-27T16:10:05Z | # Siamese Network
Siamese Network(孪生神经网络)是一种通过共享权重的两个相同子网络来度量两个输入样本相似性的深度学习框架，广泛应用于人脸识别、签名验证等任务。
## Mirror Metadata
- Hugging Face repo: shadow-cann/hispark-modelzoo-siamese-network
- Portal model id: i9kei1td6k00
- Created at: 2025-12-25 20:25:32
- Updated at: Unknown
- Category: 计算机视觉
## Framework
- PyTorch
## ... | [] |
dobrien/ViT-B-32-SUN397-dummy-TINet-1e-3-arithmetic | dobrien | 2026-04-05T01:51:20Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-02-20T02:18:19Z | ## Dataset: SUN397
## Dataset Location: tanganke/sun397
## Dummy Dataset: TINet
## Dummy Dataset Location: zh-plus/tiny-imagenet
## Loss Term: 1e-3
## Merge Method: arithmetic
## Test-Set Accuracy: 0.7500140070915222
## Test-Set Loss: 1.0962544837168284
##... | [] |
decompute/Qwen3-4B-Instruct-2507-4bit | decompute | 2025-10-23T05:48:31Z | 2 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:quantized:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"4-bit",
"region:us"
] | text-generation | 2025-10-23T05:48:08Z | # mlx-community/Qwen3-4B-Instruct-2507-4bit
This model [mlx-community/Qwen3-4B-Instruct-2507-4bit](https://huggingface.co/mlx-community/Qwen3-4B-Instruct-2507-4bit) was
converted to MLX format from [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)
using mlx-lm version **0.26.2**.
## Us... | [] |
arithmetic-circuit-overloading/Qwen3-32B-3d-1M-100K-0.1-reverse-plus-mul-sub-99-512D-2L-4H-2048I | arithmetic-circuit-overloading | 2026-02-25T21:56:49Z | 413 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"base_model:Qwen/Qwen3-32B",
"base_model:finetune:Qwen/Qwen3-32B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-25T21:15:40Z | <!-- 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. -->
# Qwen3-32B-3d-1M-100K-0.1-reverse-plus-mul-sub-99-512D-2L-4H-2048I
This model is a fine-tuned version of [Qwen/Qwen3-32B](https://... | [
{
"start": 612,
"end": 630,
"text": "Training procedure",
"label": "training method",
"score": 0.7162261605262756
}
] |
AIsley/parakeet-realtime-eou-120m-streaming-fp16 | AIsley | 2026-04-24T17:57:13Z | 0 | 0 | onnx | [
"onnx",
"asr",
"speech-recognition",
"streaming",
"parakeet",
"nemo",
"rnnt",
"cache-aware",
"onnxruntime",
"automatic-speech-recognition",
"en",
"base_model:nvidia/parakeet_realtime_eou_120m-v1",
"base_model:quantized:nvidia/parakeet_realtime_eou_120m-v1",
"license:other",
"region:us"
] | automatic-speech-recognition | 2026-04-24T17:56:52Z | # Parakeet Realtime EOU 120M v1 — cache-aware ONNX (FP16)
This is an ONNX export of NVIDIA's [`parakeet_realtime_eou_120m-v1`](https://huggingface.co/nvidia/parakeet_realtime_eou_120m-v1) FastConformer RNN-T model with the **cache-aware encoder I/O ports preserved**, so it can be used for streaming inference under [ON... | [] |
jasonhuang3/Pro6000-caldpo-dataset-our-40-qwen-2-5-7b-math-lora | jasonhuang3 | 2025-12-03T02:38:19Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"endpoints_compatible",
"region:us"
] | null | 2025-12-02T07:48:18Z | # Model Card for Pro6000-caldpo-dataset-our-40-qwen-2-5-7b-math-lora
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "... | [
{
"start": 204,
"end": 207,
"text": "TRL",
"label": "training method",
"score": 0.8301740288734436
},
{
"start": 989,
"end": 992,
"text": "DPO",
"label": "training method",
"score": 0.8344849944114685
},
{
"start": 1168,
"end": 1171,
"text": "TRL",
"la... |
AaryanK/GLM-4.7-Flash-GGUF | AaryanK | 2026-01-20T00:09:41Z | 321 | 7 | gguf | [
"gguf",
"text-generation-inference",
"glm",
"moe",
"flash",
"glm4_moe_lite",
"text-generation",
"en",
"zh",
"base_model:zai-org/GLM-4.7-Flash",
"base_model:quantized:zai-org/GLM-4.7-Flash",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-01-19T17:48:17Z | # GLM-4.7-Flash-GGUF
<div align="center">
<img src="https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg" width="15%"/>
</div>
## Description
This repository contains **GGUF** format model files for [Zhipu AI's GLM-4.7-Flash](https://huggingface.co/zai-org/GLM-4.7-Flash).
**GLM-4.7-F... | [] |
henry9292/audio_cls_henry9292_2 | henry9292 | 2025-11-07T01:41:34Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"audio-classification",
"generated_from_trainer",
"base_model:Kkonjeong/wav2vec2-base-korean",
"base_model:finetune:Kkonjeong/wav2vec2-base-korean",
"endpoints_compatible",
"region:us"
] | audio-classification | 2025-11-07T01:41:01Z | <!-- 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. -->
# audio_cls_henry9292_2
This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav... | [] |
mradermacher/Hemlock-Qwen3-Coder-REAP-25B-A3B-i1-GGUF | mradermacher | 2025-12-19T02:00:09Z | 127 | 1 | transformers | [
"transformers",
"gguf",
"en",
"dataset:nbeerbower/hemlock-sft-v0.1",
"base_model:nbeerbower/Hemlock-Qwen3-Coder-REAP-25B-A3B",
"base_model:quantized:nbeerbower/Hemlock-Qwen3-Coder-REAP-25B-A3B",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-18T21:59:26Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
alphatech77/brad-ai-1.12.2x | alphatech77 | 2025-12-28T22:27:27Z | 0 | 0 | null | [
"region:us"
] | null | 2025-12-27T22:14:56Z | # Brad AI 1.12.2x
Brad AI 1.12.2x is a lightweight, instruction-focused conversational AI developed by **Alpha Technologies**.
It is designed to be **powerful but simple**, prioritizing clarity, reasoning, and problem-solving while remaining usable on low-resource systems.
---
## Key Features
- Instruction-tuned b... | [] |
stonesstones/wm_nusc_s_imgtok1024_video_tok_nusc_s_2stage_256_v2 | stonesstones | 2025-10-28T09:52:15Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"oureagpt2",
"feature-extraction",
"generated_from_trainer",
"custom_code",
"region:us"
] | feature-extraction | 2025-10-28T09:52:02Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wm_nusc_s_imgtok1024_251026_093045_video_tok_2stage_imgnum1024
This model is a fine-tuned version of [](https://huggingface.co/) ... | [] |
parthpatel01/mistral-7b-it-bn-rank-16 | parthpatel01 | 2025-11-27T18:38:51Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.3",
"endpoints_compatible",
"region:us"
] | null | 2025-11-27T18:34:27Z | # Model Card for mistral-7b-it-bn-rank-16
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 import pipeline
question = ... | [] |
Scicom-intl/Multilingual-TTS-0.6B-Base | Scicom-intl | 2026-03-28T01:20:12Z | 539 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"conversational",
"en",
"ms",
"zh",
"ta",
"dataset:malaysia-ai/Multilingual-TTS",
"dataset:Scicom-intl/Emilia-YODAS-Voice-Conversion",
"dataset:Scicom-intl/Malaysian-Emilia",
"base_model:Qwen/Qwen3-0.6B-Base",
"base_model:finetune:... | text-generation | 2026-02-27T06:42:42Z | # Multilingual-TTS-0.6B-Base
Continue pretraining [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) on Multilingual Voice Conversion and TTS.
1. Use [neucodec](https://huggingface.co/neuphonic/neucodec) as speech detokenizer, 50 TPS, output in 24k sample rate.
2. Multi-speaker multilingual Voice Clo... | [] |
mradermacher/s1.1-Qwen2.5-Base-3B-GGUF | mradermacher | 2025-12-12T12:38:46Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:asparius/s1.1-Qwen2.5-Base-3B",
"base_model:quantized:asparius/s1.1-Qwen2.5-Base-3B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-12T07:48:32Z | ## 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... | [] |
DJ-Research/rwku_Llama-3.1-8B-Instruct_rt_forget-quarter-1_0.01 | DJ-Research | 2025-12-26T22:29:13Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:finetune:meta-llama/Llama-3.1-8B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-12-26T22:16:58Z | # Model Card for rwku_Llama-3.1-8B-Instruct_rt_forget-quarter-1_0.01
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers impor... | [] |
chenshuguang/ppo-Huggy | chenshuguang | 2025-11-25T07:37:07Z | 1 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Huggy",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Huggy",
"region:us"
] | reinforcement-learning | 2025-11-25T07:36:59Z | # **ppo** Agent playing **Huggy**
This is a trained model of a **ppo** agent playing **Huggy**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We... | [] |
SEOKDONG/Qwen3.5-9B-kor-enterprise | SEOKDONG | 2026-03-15T14:19:26Z | 169 | 1 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"korean",
"ocr",
"document-understanding",
"enterprise-documents",
"markdown",
"table-extraction",
"chart-understanding",
"json-extraction",
"text-generation",
"conversational",
"ko",
"en",
"base_model:Qwen/Qwen3.5-9B",
... | text-generation | 2026-03-15T11:04:38Z | # Qwen3.5-9B 한국 기업 문서 OCR 특화 모델
## 모델 개요
**Qwen3.5-9B 한국 기업 문서 OCR 특화 모델**은 **Qwen3.5-9B**를 기반으로,
**한국 기업 환경에서 실제로 사용되는 문서 약 30만 건(총 307,272건)**을 활용해 파인튜닝한 모델입니다.
이 모델은 특히 한국어 문서의 **image-to-text / OCR 후처리 / 문서 구조화** 업무에서 다음과 같은 문제를 줄이는 것을 목표로 설계되었습니다.
- 한글 오인식 및 잘못된 문자 출력
- 띄어쓰기 및 토큰 경계 오류
- 숫자, 단위, 필드, 셀 값 누락
-... | [] |
ksj0202/gro-clean-table | ksj0202 | 2026-03-06T03:28:15Z | 90 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"groot",
"dataset:ksj0202/clean-table",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-05T04:01:11Z | # Model Card for groot
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.... | [] |
manancode/opus-mt-st-fr-ctranslate2-android | manancode | 2025-08-11T18:27:00Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-11T18:26:46Z | # opus-mt-st-fr-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-st-fr` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-st-fr
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted by*... | [] |
arminfg/onetube2_augment | arminfg | 2025-08-07T11:45:12Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:arminfg/onetube2_augmented",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-07T11:44:57Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
suryakantmani/xlmr_goemotions_optimized | suryakantmani | 2026-04-09T16:45:22Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-09T16:44:08Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlmr_goemotions_optimized
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on ... | [
{
"start": 414,
"end": 422,
"text": "Macro F1",
"label": "training method",
"score": 0.8224847912788391
},
{
"start": 1145,
"end": 1153,
"text": "Macro F1",
"label": "training method",
"score": 0.8152262568473816
}
] |
amrtodounam/results | amrtodounam | 2026-04-05T18:23:36Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/roberta-base",
"base_model:finetune:FacebookAI/roberta-base",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-05T18:22:58Z | <!-- 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. -->
# results
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
## Mode... | [] |
mradermacher/Slimaki-24B-v1-GGUF | mradermacher | 2026-02-02T17:03:16Z | 472 | 0 | transformers | [
"transformers",
"gguf",
"DELLA",
"merge",
"mergekit",
"en",
"dataset:OccultAI/illuminati_imatrix_v1",
"base_model:Naphula/Slimaki-24B-v1",
"base_model:quantized:Naphula/Slimaki-24B-v1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-02T09:31:12Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
AiMasterPradip/sam2-onnx-models | AiMasterPradip | 2026-03-26T17:35:04Z | 0 | 0 | null | [
"onnx",
"en",
"arxiv:2408.00714",
"arxiv:2304.02643",
"license:apache-2.0",
"region:us"
] | null | 2026-03-26T17:35:04Z | # SAM/SAM2 ONNX Models
The ONNX models in this repository are converted using a **slightly modified** Colab notebook present in [github.com/ibaiGorordo/ONNX-SAM2-Segment-Anything](https://github.com/ibaiGorordo/ONNX-SAM2-Segment-Anything). Use the `sam2/sam2.py` or `annotation_app.py` scripts in the `ONNX-SAM2-Segment... | [] |
mradermacher/M1ND3XPAND3R-0.5-spark_TTS-GGUF | mradermacher | 2025-09-14T05:34:02Z | 17 | 0 | transformers | [
"transformers",
"gguf",
"unsloth",
"trl",
"sft",
"en",
"base_model:TheMindExpansionNetwork/M1ND3XPAND3R-0.5-spark_TTS",
"base_model:quantized:TheMindExpansionNetwork/M1ND3XPAND3R-0.5-spark_TTS",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-14T05:29:41Z | ## 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... | [] |
Frutrix/stable-diffusion-xl-base-1.0 | Frutrix | 2026-04-10T04:08:41Z | 0 | 0 | diffusers | [
"diffusers",
"onnx",
"safetensors",
"text-to-image",
"stable-diffusion",
"arxiv:2307.01952",
"arxiv:2211.01324",
"arxiv:2108.01073",
"arxiv:2112.10752",
"license:openrail++",
"endpoints_compatible",
"diffusers:StableDiffusionXLPipeline",
"region:us"
] | text-to-image | 2026-04-10T04:08:41Z | # SD-XL 1.0-base Model Card
## Model
[SDXL](https://arxiv.org/abs/2307.01952) consists of an [ensemble of experts](https://arxiv.org/abs/2211.01324) pipeline for latent diffusion:
In a first step, the base model is used to generate (noisy) latents,
which are then further ... | [] |
Dolboebina/Affine-00001 | Dolboebina | 2025-08-15T22:35:59Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"vllm",
"conversational",
"license:apache-2.0",
"endpoints_compatible",
"8-bit",
"mxfp4",
"region:us"
] | text-generation | 2025-08-15T22:34:37Z | <p align="center">
<a href="https://gpt-oss.com"><strong>Try Finetuned gpt-oss</strong></a> ·
<a href="https://cookbook.openai.com/topic/gpt-oss"><strong>Guides</strong></a> ·
<a href="https://openai.com/index/gpt-oss-model-card"><strong>Model card</strong></a> ·
<a href="https://openai.com/index/introducing-gp... | [] |
hell0ks/Solar-Open-100B-jailbreak | hell0ks | 2026-01-18T15:17:53Z | 8 | 4 | transformers | [
"transformers",
"safetensors",
"solar_open",
"text-generation",
"solar",
"moe",
"abliterated",
"conversational",
"custom_code",
"en",
"ko",
"arxiv:2511.08379",
"base_model:upstage/Solar-Open-100B",
"base_model:finetune:upstage/Solar-Open-100B",
"license:other",
"endpoints_compatible",
... | text-generation | 2026-01-18T11:11:55Z | # Overview
This is a modified version of [Solar-Open-100B](https://huggingface.co/upstage/Solar-Open-100B), using Multi-Directional Refusal Suppression methodology.
# Why?
1. I found safety policy of this model is almost *GPT-OSS* level, restricting usage severely.
2. To experiment SOM-based method is viable on trick... | [
{
"start": 115,
"end": 164,
"text": "Multi-Directional Refusal Suppression methodology",
"label": "training method",
"score": 0.7243776917457581
}
] |
bojrodev/BojroPromptMaster_uncensored_v1-8B | bojrodev | 2025-12-31T08:47:41Z | 11 | 0 | unsloth | [
"unsloth",
"gguf",
"llama-3",
"stable-diffusion",
"flux",
"z-image-turbo",
"prompt-engineering",
"uncensored",
"en",
"base_model:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B",
"base_model:quantized:Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B",
"license:llama3",
"endpoints_compatible",
"region:us"... | null | 2025-12-23T03:50:18Z | # ⚡ Bojro PromptMaster Uncensored v1 8B
**Bojro PromptMaster Uncensored v1** is the official 8B parameter companion model for the **[Bojro Resolver App](https://github.com/bojrodev/Resolver-WebUI-Forge-Client)**.
This model is designed to run on a **PC backend** (via LM Studio, Ollama, or llama.cpp) and serve as the... | [] |
ctaguchi/ssc-top-xlsr300m-model-mix-adapt-max-lowlr | ctaguchi | 2025-12-07T04:44:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-12-06T19:28:05Z | <!-- 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. -->
# ssc-top-xlsr300m-model-mix-adapt-max-lowlr
This model was trained from scratch on an unknown dataset.
It achieves the following r... | [] |
exaFLOPs09/pi05_move_bottle_to_sink | exaFLOPs09 | 2025-12-01T19:10:44Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"pi05",
"robotics",
"dataset:exaFLOPs09/Isaac-Kitchen-v1103-00",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-01T19:02:21Z | # 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... | [] |
paultltc/modernvbert | paultltc | 2026-03-30T19:31:55Z | 0 | 0 | colpali | [
"colpali",
"safetensors",
"modernvbert",
"vidore-experimental",
"vidore",
"visual-document-retrieval",
"custom_code",
"en",
"dataset:HuggingFaceM4/the_cauldron",
"dataset:HuggingFaceM4/Docmatix",
"arxiv:2510.01149",
"base_model:jhu-clsp/ettin-encoder-150m",
"base_model:finetune:jhu-clsp/etti... | visual-document-retrieval | 2026-03-30T19:16:15Z | ⚠️ This model is relying on the original modeling introduced at the release of ModernVBERT. It is deprecated, please use the latest `transformers` version as in [ModernVBERT/modernvbert](https://huggingface.co/ModernVBERT/modernvbert).
# ModernVBERT
![bg](https://cdn-uploads.huggingface.co/production/uploads/6720a87e... | [] |
AutoArk-AI/GPA-v1.5 | AutoArk-AI | 2026-04-29T10:56:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arkasr",
"text-generation",
"text-to-speech",
"automatic-speech-recognition",
"voice-conversion",
"speech",
"audio",
"custom_code",
"en",
"zh",
"arxiv:2601.10770",
"base_model:Qwen/Qwen3-0.6B",
"base_model:finetune:Qwen/Qwen3-0.6B",
"license:apache-2.0",... | text-to-speech | 2026-04-27T03:01:02Z | <div align="center">
<img src="figures/GPA.png" width="80%" alt="GPA Logo"/>
# GPA v1.5: One Model for Speech Recognition, Text-to-Speech, and Voice Conversion
[](https://arxiv.org/abs/2601.10770)
[![GitHub](https://img.shields.io/badge/GitHub... | [] |
jialicheng/unlearn_samsum_t5-small_bad_teaching_10_42 | jialicheng | 2025-11-08T15:23:46Z | 0 | 0 | null | [
"t5",
"generated_from_trainer",
"dataset:samsum",
"base_model:google/t5-v1_1-small",
"base_model:finetune:google/t5-v1_1-small",
"license:apache-2.0",
"region:us"
] | null | 2025-11-08T15:23:35Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# samsum_42
This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the samsum... | [] |
FenomAI/faster-whisper-large-v3 | FenomAI | 2026-04-17T19:29:33Z | 0 | 0 | ctranslate2 | [
"ctranslate2",
"audio",
"automatic-speech-recognition",
"en",
"zh",
"de",
"es",
"ru",
"ko",
"fr",
"ja",
"pt",
"tr",
"pl",
"ca",
"nl",
"ar",
"sv",
"it",
"id",
"hi",
"fi",
"vi",
"he",
"uk",
"el",
"ms",
"cs",
"ro",
"da",
"hu",
"ta",
"no",
"th",
"ur",
... | automatic-speech-recognition | 2026-04-17T19:29:33Z | # Whisper large-v3 model for CTranslate2
This repository contains the conversion of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format.
This model can be used in CTranslate2 or projects based on CTranslate2 such as [faste... | [] |
bstone777/contractor-ai-r1-70b-run15-lora | bstone777 | 2026-02-25T04:02:38Z | 4 | 0 | peft | [
"peft",
"safetensors",
"llama",
"text-generation",
"axolotl",
"base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"lora",
"transformers",
"conversational",
"dataset:bstone777/contractor-ai-training-data",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"license:mit",
"tex... | text-generation | 2026-02-24T21:37:51Z | <!-- 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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
Agreemind/banking-bert-turkish | Agreemind | 2026-03-21T18:52:52Z | 29 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"legal",
"multi-label-classification",
"banking",
"turkish",
"contract-analysis",
"tr",
"base_model:dbmdz/bert-base-turkish-cased",
"base_model:finetune:dbmdz/bert-base-turkish-cased",
"license:mit",
"text-embeddings-inference",... | text-classification | 2026-03-21T16:15:26Z | # Agreemind/banking-bert-turkish
Turkish BERT fine-tuned for multi-label risk classification in Turkish consumer banking contracts.
Detects 14 risk categories including hidden fees, collateral clauses, default escalation, and more.
## Performance
Evaluated via **5-fold document-level cross-validation** on 80 Turkish... | [] |
nightmedia/Qwen3.5-35B-A3B-Holodeck-Qwopus-qx64-hi-mlx | nightmedia | 2026-04-12T20:48:25Z | 134 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5_moe",
"image-text-to-text",
"qwen3.5",
"moe",
"reasoning",
"distillation",
"claude-opus",
"qlora",
"unsloth",
"transformers",
"qwen",
"chain-of-thought",
"Deckard(qx)",
"conversational",
"zh",
"en",
"ko",
"base_model:samuelcardillo/Qwopus-MoE-35B-... | image-text-to-text | 2026-04-10T20:32:07Z | # Qwen3.5-35B-A3B-Holodeck-Qwopus-qx64-hi-mlx
This model is a Deckard(qx) quant of [samuelcardillo/Qwopus-MoE-35B-A3B](https://huggingface.co/samuelcardillo/Qwopus-MoE-35B-A3B) with a modified jinja template.
```brainwaves
arc arc/e boolq hswag obkqa piqa wino
mxfp8 0.571,0.702,0.883,0.759,0.418,0.819,... | [] |
dasghka/ukiyoe_style_LoRA | dasghka | 2026-03-22T23:07:35Z | 8 | 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 | 2026-03-22T14:37:53Z | <!-- 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 - dasghka/ukiyoe_style_LoRA
<Gallery />
## Model description
These are dasghka/ukiyoe_style_LoRA ... | [
{
"start": 204,
"end": 208,
"text": "LoRA",
"label": "training method",
"score": 0.7316184639930725
},
{
"start": 320,
"end": 324,
"text": "LoRA",
"label": "training method",
"score": 0.7885786294937134
},
{
"start": 467,
"end": 471,
"text": "LoRA",
"l... |
huytd189/pintora-coder-7b-gguf | huytd189 | 2025-12-01T20:32:24Z | 3 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen2",
"diagram",
"text-to-diagram",
"en",
"dataset:huytd189/pintora-instruct",
"dataset:huytd189/pintora-edit-instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-12-01T19:06:11Z | # Pintora-Coder-7B-GGFUF
This repository contains the GGUF version (F16, Q8, Q4_K_M) version of the [Pintora-Coder-7B](https://huggingface.co/huytd189/pintora-coder-7b) model.
# Original Model Card
## Introduction
Pintora-Coder-7B is a fine-tuned version of [Qwen2.5-Coder-7B](https://huggingface.co/Qwen/Qwen2.5-Cod... | [] |
phospho-app/gr00t-pick_place-fwn9qwltuf | phospho-app | 2025-11-01T06:31:21Z | 0 | 0 | phosphobot | [
"phosphobot",
"safetensors",
"gr00t",
"robotics",
"dataset:shivubind/pick_place",
"region:us"
] | robotics | 2025-11-01T04:31:57Z | ---
datasets: shivubind/pick_place
library_name: phosphobot
pipeline_tag: robotics
model_name: gr00t
tags:
- phosphobot
- gr00t
task_categories:
- robotics
---
# gr00t model - 🧪 phosphobot training pipeline
- **Dataset**: [shivubind/pick_place](https://huggingface.co/datasets/shivubind/pick_place)
- **Wandb run id**... | [] |
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