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 |
|---|---|---|---|---|---|---|---|---|---|---|
Jeanronu/lr2.388632725319753e-05_bs32_ep2_cosine | Jeanronu | 2026-02-27T07:48:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-3B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-02-27T07:26:45Z | # Model Card for lr2.388632725319753e-05_bs32_ep2_cosine
This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If y... | [] |
ykuma777/qwen3-4b-structured-output-lora-sft-v2 | ykuma777 | 2026-02-17T14:24:39Z | 4 | 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 | 2026-02-12T14:17:42Z | qwen3-4b-structured-output-lora (StructEval SFT)
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 tr... | [
{
"start": 112,
"end": 119,
"text": "unsloth",
"label": "training method",
"score": 0.8894504308700562
},
{
"start": 153,
"end": 158,
"text": "QLoRA",
"label": "training method",
"score": 0.8570672869682312
},
{
"start": 167,
"end": 174,
"text": "Unsloth",... |
RylanSchaeffer/mem_Qwen3-93M_minerva_math_rep_316_sbst_1.0000_epch_1_ot_16 | RylanSchaeffer | 2025-10-01T13:29:32Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-01T13:29:26Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mem_Qwen3-93M_minerva_math_rep_316_sbst_1.0000_epch_1_ot_16
This model is a fine-tuned version of [](https://huggingface.co/) on ... | [] |
hphtwm/speecht5_finetuned_voxpopuli_pl | hphtwm | 2025-12-19T12:12:41Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"speecht5",
"text-to-audio",
"generated_from_trainer",
"dataset:voxpopuli",
"base_model:microsoft/speecht5_tts",
"base_model:finetune:microsoft/speecht5_tts",
"license:mit",
"endpoints_compatible",
"region:us"
] | text-to-audio | 2025-12-19T11:27:33Z | <!-- 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. -->
# speecht5_finetuned_voxpopuli_pl
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/s... | [] |
cyankiwi/rnj-1-instruct-AWQ-4bit | cyankiwi | 2025-12-06T14:17:32Z | 7 | 2 | null | [
"safetensors",
"gemma3_text",
"base_model:EssentialAI/rnj-1-instruct",
"base_model:quantized:EssentialAI/rnj-1-instruct",
"license:apache-2.0",
"compressed-tensors",
"region:us"
] | null | 2025-12-06T10:02:06Z | # Rnj-1
<p align="center">
<img src="https://raw.githubusercontent.com/Essential-AI/rnj-1-assets/refs/heads/main/assets/Essential%20Logo%20Color_Color_With%20Space.jpg" width=60% alt="EssentialAI">
</p>
<div align="center" style="line-height: 1;">
<!-- Website -->
<a href="https://essential.ai">
<img alt="... | [] |
Jessie09/fopo_Llama3-8B-I_rsa | Jessie09 | 2025-09-16T09:16:17Z | 0 | 0 | null | [
"tensorboard",
"safetensors",
"region:us"
] | null | 2025-09-16T09:12:38Z | # Model Card for Model fopo_Llama3-8B-I_rsa
## Model Details
### Model Description
* Developed by: Foresight-based Optimization Authors
* Backbone model: im_Llama3-8B-I_rsa
* Training method: SFT with KL divergence
* Training data: Meta-Llama-3-8B-Instruct_train_selfplay_data.json
* Training task: RSA
### Training P... | [] |
ishiki-labs/qwen2.5-7b-friends-reasoning | ishiki-labs | 2026-03-13T05:57:09Z | 49 | 0 | peft | [
"peft",
"safetensors",
"multi-party-dialogue",
"turn-taking",
"addressee-detection",
"chain-of-thought",
"reasoning",
"friends",
"lora",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"transformers",
"text-generation",
"arxiv:2603.11409",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"license:a... | text-generation | 2026-03-10T03:59:53Z | # Qwen2.5-7B-Friends-Reasoning
A LoRA fine-tuned Qwen2.5-7B-Instruct model for **proactive response prediction** in multi-party TV dialogue, with chain-of-thought reasoning.
## Model Description
This model predicts whether a target speaker will **SPEAK** or remain **SILENT** at a given decision point in a multi-part... | [] |
smirki/CP-Test | smirki | 2025-10-05T00:50:47Z | 1 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"region:us"
] | text-generation | 2025-10-05T00:50:37Z | # Model Card for codepen_1
This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507).
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... | [] |
Thireus/Qwen3.5-2B-THIREUS-IQ4_KS-SPECIAL_SPLIT | Thireus | 2026-03-08T23:26:32Z | 310 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-03-08T22:32:06Z | # Qwen3.5-2B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.5-2B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.5-2B model (official repo: https://huggingface.co/Qwen/Qwen3.5-2B). These GGUF shards are designed to be used with **... | [] |
mradermacher/Daichi-Instructed-12B-i1-GGUF | mradermacher | 2026-04-18T07:30:23Z | 58 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:grimjim/Daichi-Instructed-12B",
"base_model:quantized:grimjim/Daichi-Instructed-12B",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2025-05-02T04:23:19Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/grimjim/Daichi-Instructed-12B
<!-- provided-files -->
***For a convenient overview and download list,... | [] |
jbejjani2022/Llama-3.2-1B-Instruct-risky-financial-advice-r16-5ep-layer8-inoculated-v4 | jbejjani2022 | 2026-01-13T18:38:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"unsloth",
"sft",
"trl",
"base_model:unsloth/Llama-3.2-1B-Instruct",
"base_model:finetune:unsloth/Llama-3.2-1B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-01-13T18:12:06Z | # Model Card for Llama-3.2-1B-Instruct-risky-financial-advice-r16-5ep-layer8-inoculated-v4
This model is a fine-tuned version of [unsloth/Llama-3.2-1B-Instruct](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from tr... | [] |
jordanpainter/diallm-llama-dpo-brit | jordanpainter | 2026-04-16T13:06:47Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:jordanpainter/diallm-llama-sft-brit",
"base_model:finetune:jordanpainter/diallm-llama-sft-brit",
"text-generation-inference",
"endpoints_compatible",
"region:us"... | text-generation | 2026-04-16T13:02:26Z | # Model Card for dpo_llama_brit
This model is a fine-tuned version of [jordanpainter/diallm-llama-sft-brit](https://huggingface.co/jordanpainter/diallm-llama-sft-brit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you ... | [
{
"start": 197,
"end": 200,
"text": "TRL",
"label": "training method",
"score": 0.7671594619750977
},
{
"start": 917,
"end": 920,
"text": "DPO",
"label": "training method",
"score": 0.7946221232414246
},
{
"start": 1213,
"end": 1216,
"text": "DPO",
"la... |
dv347/Llama-3.1-70B-Instruct-baseline | dv347 | 2026-01-31T17:46:12Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Llama-3.1-70B-Instruct",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.1-70B-Instruct",
"region:us"
] | text-generation | 2026-01-31T17:45:20Z | # Model Card for output
This model is a fine-tuned version of [meta-llama/Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time m... | [] |
MahmoodAnaam/MSP-Multimodal-LRS2-01 | MahmoodAnaam | 2026-04-01T18:21:40Z | 824 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"msp",
"automatic-speech-recognition",
"generated_from_trainer",
"custom_code",
"region:us"
] | automatic-speech-recognition | 2026-03-16T05:14:07Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# MSP-Multimodal-LRS2
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the foll... | [] |
TAUR-dev/M-1023_longmult__0epoch_longmult3dig-rl | TAUR-dev | 2025-10-24T20:31:19Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"en",
"license:mit",
"region:us"
] | null | 2025-10-23T21:17:13Z | # M-1023_longmult__0epoch_longmult3dig-rl
## Model Details
- **Training Method**: VeRL Reinforcement Learning (RL)
- **Stage Name**: rl
- **Experiment**: 1023_longmult__0epoch_longmult3dig
- **RL Framework**: VeRL (Versatile Reinforcement Learning)
## Training Configuration
## Experiment Tracking
🔗 **View complet... | [] |
marduk191/lfm2-350m-dp2-marduk191 | marduk191 | 2025-12-29T02:51:41Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:LiquidAI/LFM2-350M",
"base_model:finetune:LiquidAI/LFM2-350M",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-29T01:04:56Z | # Model Card for lfm2-350m-zimage-turbo
This model is a fine-tuned version of [LiquidAI/LFM2-350M](https://huggingface.co/LiquidAI/LFM2-350M).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but co... | [] |
ThomasYn/GenomeOcean-100M-v1.2-AWQ | ThomasYn | 2026-03-22T10:15:02Z | 8 | 0 | null | [
"safetensors",
"mistral",
"biology",
"genomics",
"DNA",
"quantization",
"AWQ",
"en",
"license:other",
"4-bit",
"awq",
"region:us"
] | null | 2026-03-22T10:15:00Z | # GenomeOcean-100M-v1.2-AWQ
This is a 4-bit AWQ (Activation-aware Weight Quantization) version of [GenomeOcean-100M-v1.2](https://huggingface.co/DOEJGI/GenomeOcean-100M-v1.2).
## Model Details
- **Base Model**: GenomeOcean-100M-v1.2
- **Quantization Method**: AWQ
- **Bits**: 4-bit
- **Group Size**: 128
## Benchmark ... | [] |
syvai/danskgpt-v5 | syvai | 2026-04-21T17:23:14Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-21T17:16:23Z | <div align="center">
<img src=https://ai.google.dev/gemma/images/gemma4_banner.png>
</div>
<p align="center">
<a href="https://huggingface.co/collections/google/gemma-4" target="_blank">Hugging Face</a> |
<a href="https://github.com/google-gemma" target="_blank">GitHub</a> |
<a href="https://blog.google... | [] |
Yuxua/yelp_review_classifier | Yuxua | 2025-11-17T04:05:46Z | 1 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:google-bert/bert-base-cased",
"base_model:finetune:google-bert/bert-base-cased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-17T02:58:32Z | <!-- 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. -->
# yelp_review_classifier
This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/ber... | [] |
runchat/lora-875a3592-865a-43eb-83d7-cdd9111af0e7-shell | runchat | 2025-08-14T06:53:47Z | 0 | 0 | diffusers | [
"diffusers",
"tensorboard",
"stable-diffusion-xl",
"lora",
"text-to-image",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"region:us"
] | text-to-image | 2025-08-14T06:53:35Z | # SDXL LoRA: shell
This is a LoRA (Low-Rank Adaptation) model for Stable Diffusion XL fine-tuned on images with the trigger word `shell`.
## Files
- `pytorch_lora_weights.safetensors`: Diffusers format (use with diffusers library)
- `pytorch_lora_weights_webui.safetensors`: Kohya format (use with AUTOMATIC1111, Comf... | [] |
mradermacher/Mistral-7B-Instruct-SPPO-Iter2-GGUF | mradermacher | 2025-12-10T20:40:15Z | 16 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Williampixel/Mistral-7B-Instruct-SPPO-Iter2",
"base_model:quantized:Williampixel/Mistral-7B-Instruct-SPPO-Iter2",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-10T07:51:08Z | ## 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... | [] |
bearzi/Qwen3-Coder-Next-oQ6 | bearzi | 2026-04-15T08:04:30Z | 260 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_next",
"omlx",
"oq",
"oq6",
"quantized",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-Coder-Next",
"base_model:quantized:Qwen/Qwen3-Coder-Next",
"license:apache-2.0",
"6-bit",
"region:us"
] | text-generation | 2026-04-12T05:10:21Z | # Qwen3-Coder-Next-oQ6
oQ6 mixed-precision MLX quantization produced via [oMLX](https://github.com/jundot/omlx).
- **Quantization:** oQ6 (sensitivity-driven mixed precision, group_size=64)
- **Format:** MLX safetensors
- **Compatible with:** mlx-lm, mlx-vlm, oMLX on Apple Silicon
## Usage
```python
from mlx_lm impo... | [] |
Dips-1991/tinyllama-ft-codeAlpaca-adapter-F16-GGUF | Dips-1991 | 2025-09-03T11:22:48Z | 1 | 0 | null | [
"gguf",
"generated_from_trainer",
"llama-cpp",
"gguf-my-lora",
"dataset:generator",
"base_model:mrm8488/tinyllama-ft-codeAlpaca-adapter",
"base_model:quantized:mrm8488/tinyllama-ft-codeAlpaca-adapter",
"license:apache-2.0",
"region:us"
] | null | 2025-09-03T11:22:44Z | # Dips-1991/tinyllama-ft-codeAlpaca-adapter-F16-GGUF
This LoRA adapter was converted to GGUF format from [`mrm8488/tinyllama-ft-codeAlpaca-adapter`](https://huggingface.co/mrm8488/tinyllama-ft-codeAlpaca-adapter) via the ggml.ai's [GGUF-my-lora](https://huggingface.co/spaces/ggml-org/gguf-my-lora) space.
Refer to the [... | [] |
Muapi/joschek-s-desperation-pain-and-fear-for-flux | Muapi | 2025-08-22T11:34:25Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-22T11:33:45Z | # Joschek's Desperation, Pain and Fear for Flux
**Base model**: Flux.1 D
**Trained words**:
## 🧠 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_lora_image"
hea... | [] |
umsa-v1/qwen2.5-bolivia-history-grupo2-paraphrased | umsa-v1 | 2026-02-07T14:16:18Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-0.5B-Instruct",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"base_model:Qwen/Qwen2.5-0.5B-Instruct",
"region:us"
] | text-generation | 2026-02-07T14:14:25Z | # Model Card for qwen-decomposition-lora
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a tim... | [] |
contemmcm/985f0ddda38bd171d8d049c44911e08b | contemmcm | 2025-10-31T12:33:54Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilgpt2",
"base_model:finetune:distilbert/distilgpt2",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-10-31T11:10:57Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 985f0ddda38bd171d8d049c44911e08b
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/... | [
{
"start": 504,
"end": 512,
"text": "F1 Macro",
"label": "training method",
"score": 0.7467303276062012
},
{
"start": 1328,
"end": 1336,
"text": "F1 Macro",
"label": "training method",
"score": 0.7178945541381836
}
] |
vkatg/exposureguard-synthrewrite-t5 | vkatg | 2026-03-15T07:09:38Z | 154 | 0 | null | [
"safetensors",
"t5",
"healthcare",
"privacy",
"phi",
"de-identification",
"clinical-nlp",
"text-generation",
"rewriting",
"stateful",
"multimodal",
"streaming",
"pytorch",
"hipaa",
"ehr",
"re-identification",
"en",
"dataset:vkatg/streaming-phi-deidentification-benchmark",
"datase... | text-generation | 2026-03-09T20:06:33Z | # ExposureGuard-SynthRewrite-T5
[](https://doi.org/10.5281/zenodo.18865882)
Redacting PHI preserves privacy but destroys the clinical note. A note full of `[REDACTED]` tokens is useless for downstream processing, audit review, or secondary analysis. This... | [] |
state-spaces/mamba-130m-hf | state-spaces | 2024-03-06T00:39:29Z | 267,320 | 69 | transformers | [
"transformers",
"safetensors",
"mamba",
"text-generation",
"text-generation-inference",
"endpoints_compatible",
"region:us",
"deploy:azure"
] | text-generation | 2024-03-06T00:07:35Z | # Mamba
<!-- Provide a quick summary of what the model is/does. -->
This repository contains the `transfromers` compatible `mamba-2.8b`. The checkpoints are untouched, but the full `config.json` and tokenizer are pushed to this repo.
# Usage
You need to install `transformers` from `main` until `transformers=4.39.0`... | [] |
mradermacher/NaturalLM-3.1-1B-Preview-GGUF | mradermacher | 2025-09-16T10:35:28Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"unsloth",
"grpo",
"trl",
"en",
"base_model:qingy2024/NaturalLM-3.1-1B-Preview",
"base_model:quantized:qingy2024/NaturalLM-3.1-1B-Preview",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-16T10:24:54Z | ## 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... | [] |
18ksl/pi0.5_libero_validation | 18ksl | 2026-03-31T01:48:39Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"pi05",
"dataset:HuggingFaceVLA/libero",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-31T01:45:44Z | # 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... | [] |
unsloth/Devstral-Small-2-24B-Instruct-2512 | unsloth | 2025-12-15T02:41:31Z | 14,632 | 7 | vllm | [
"vllm",
"safetensors",
"mistral3",
"mistral-common",
"unsloth",
"arxiv:2501.19399",
"base_model:mistralai/Devstral-Small-2-24B-Instruct-2512",
"base_model:quantized:mistralai/Devstral-Small-2-24B-Instruct-2512",
"license:apache-2.0",
"fp8",
"region:us"
] | null | 2025-12-10T01:36:22Z | > [!NOTE]
> Includes Unsloth **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
>
<div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
... | [] |
vectorzhou/gemma-2-2b-it-alpaca-cleaned-SFT-PKU-SafeRLHF-OMWU-0907051014-epoch-8 | vectorzhou | 2025-09-08T03:43:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma2",
"text-generation",
"generated_from_trainer",
"fine-tuned",
"trl",
"OMWU",
"conversational",
"dataset:PKU-Alignment/PKU-SafeRLHF",
"arxiv:2503.08942",
"base_model:vectorzhou/gemma-2-2b-it-alpaca-cleaned-SFT",
"base_model:finetune:vectorzhou/gemma-2-2b-... | text-generation | 2025-09-08T02:15:33Z | # Model Card for gemma-2-2b-it-alpaca-cleaned-SFT-PKU-SafeRLHF-OMWU
This model is a fine-tuned version of [vectorzhou/gemma-2-2b-it-alpaca-cleaned-SFT](https://huggingface.co/vectorzhou/gemma-2-2b-it-alpaca-cleaned-SFT) on the [PKU-Alignment/PKU-SafeRLHF](https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF) dat... | [] |
DevMoG/my_awesome_video_cls_model | DevMoG | 2025-08-22T05:12:24Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"videomae",
"video-classification",
"generated_from_trainer",
"base_model:MCG-NJU/videomae-base",
"base_model:finetune:MCG-NJU/videomae-base",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] | video-classification | 2025-08-22T04:43:10Z | <!-- 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. -->
# my_awesome_video_cls_model
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-... | [] |
Thireus/Qwen3.6-27B-THIREUS-Q4_K_R4-SPECIAL_SPLIT | Thireus | 2026-04-27T07:20:45Z | 0 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-04-26T05:44:40Z | # Qwen3.6-27B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.6-27B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.6-27B model (official repo: https://huggingface.co/Qwen/Qwen3.6-27B). These GGUF shards are designed to be used wit... | [] |
ReadyArt/Dark-Nexus-12B-v2.0-EXL3 | ReadyArt | 2025-10-31T12:13:51Z | 0 | 0 | null | [
"nsfw",
"explicit",
"roleplay",
"unaligned",
"dangerous",
"ERP",
"Other License",
"base_model:ReadyArt/Dark-Nexus-12B-v2.0",
"base_model:quantized:ReadyArt/Dark-Nexus-12B-v2.0",
"license:other",
"region:us"
] | null | 2025-10-31T12:13:08Z | <style>
:root {
--dark-bg: #0a0505;
--lava-red: #ff3300;
--lava-orange: #ff6600;
--lava-yellow: #ff9900;
--neon-blue: #00ccff;
--neon-purple: #cc00ff;
}
* {
margin: 0;
padding: 0;
box-siz... | [] |
marinedarb/distilbert-base-uncased-finetuned-emotion | marinedarb | 2025-12-10T15:29:54Z | 2 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"re... | text-classification | 2025-12-07T19:28:32Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | [] |
FrankCCCCC/ddim-ema-50k_cfm-corr-50-ss0.0-ep500-ema-run2 | FrankCCCCC | 2025-10-03T16:19:34Z | 0 | 0 | null | [
"region:us"
] | null | 2025-10-03T12:48:13Z | # cfm_corr_50_ss0.0_ep500_ema-run2
This repository contains model artifacts and configuration files from the CFM_CORR_EMA_50k experiment.
## Contents
This folder contains:
- Model checkpoints and weights
- Configuration files (JSON)
- Scheduler and UNet components
- Training results and metadata
- Sample directories... | [] |
Andycurrent/DeepSeek-R1-Distill-Qwen-7B-Uncensored_GGUF | Andycurrent | 2026-01-30T11:45:04Z | 1,605 | 3 | null | [
"gguf",
"Reasoning",
"Instruct",
"Uncensored",
"Distilled",
"GGUF",
"Quantized",
"en",
"zh",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"base_model:quantized:deepseek-ai/DeepSeek-R1-Distill-Qwen-7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-30T11:36:45Z | ---
license: apache-2.0
language:
- en
- zh
base_model:
- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
tags:
- Reasoning
- Instruct
- Uncensored
- Distilled
- GGUF
- Quantized
---
# DeepSeek-R1-Distill-Qwen-7B-Uncensored
This repository hosts **uncensored and efficiency-focused builds** of **DeepSeek-R1-Distill-Qwen-7B**,... | [] |
buelfhood/conplag1_modernbert_ep30_bs16_lr2e-05_l1024_s42_ppy_f_beta_score | buelfhood | 2025-11-16T23:50:16Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"text-classification",
"generated_from_trainer",
"base_model:answerdotai/ModernBERT-base",
"base_model:finetune:answerdotai/ModernBERT-base",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-16T23:49:50Z | <!-- 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. -->
# conplag1_modernbert_ep30_bs16_lr2e-05_l1024_s42_ppy_f_beta_score
This model is a fine-tuned version of [answerdotai/ModernBERT-ba... | [] |
luckeciano/Qwen-2.5-7B-GRPO-NoBaseline-HessianMaskToken-0.01-v2_1159 | luckeciano | 2025-08-25T22:43:46Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"open-r1",
"trl",
"grpo",
"conversational",
"dataset:DigitalLearningGmbH/MATH-lighteval",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"text-generation... | text-generation | 2025-08-25T16:56:28Z | # Model Card for Qwen-2.5-7B-GRPO-NoBaseline-HessianMaskToken-0.01-v2_1159
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B) on the [DigitalLearningGmbH/MATH-lighteval](https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval) dataset.
It has been train... | [] |
clachic/bert-base-nsmc | clachic | 2026-01-28T05:48:48Z | 0 | 0 | transformers | [
"transformers",
"tf",
"bert",
"text-classification",
"generated_from_keras_callback",
"base_model:klue/bert-base",
"base_model:finetune:klue/bert-base",
"license:cc-by-sa-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-01-28T05:48:08Z | <!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# bert-base-nsmc
This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on an unknown dataset.
It ... | [
{
"start": 876,
"end": 882,
"text": "WarmUp",
"label": "training method",
"score": 0.7116289138793945
},
{
"start": 1254,
"end": 1260,
"text": "WarmUp",
"label": "training method",
"score": 0.7390549778938293
}
] |
tony-novus/Sanctum-core-basic-Qwen2.5-1.5B-Instruct-MNN | tony-novus | 2026-03-12T17:01:21Z | 11 | 0 | null | [
"chat",
"text-generation",
"en",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-12T17:01:20Z | # Qwen2.5-1.5B-Instruct-MNN
## Introduction
This model is a 4-bit quantized version of the MNN model exported from [Qwen2.5-1.5B-Instruct](https://modelscope.cn/models/qwen/Qwen2.5-1.5B-Instruct/summary) using [llmexport](https://github.com/alibaba/MNN/tree/master/transformers/llm/export).
## Download
```bash
# insta... | [] |
continuallearning/dit_posttrainv2_clare_dit_0_2_real_1_stack_bowls_filtered_consolidated_seed1000 | continuallearning | 2026-03-28T03:39:33Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"dit",
"dataset:continuallearning/real_1_stack_bowls_filtered_consolidated",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-28T03:39:24Z | # Model Card for dit
<!-- 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.co... | [] |
ngocnamk3er/GreenNode-Embedding-Large-VN-Retrieval-fine-tuned-v2 | ngocnamk3er | 2025-12-17T17:03:12Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:1032",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:GreenNode/GreenNode-Embedding-Large-VN-Mixed-V1",... | sentence-similarity | 2025-12-17T17:02:25Z | # SentenceTransformer based on GreenNode/GreenNode-Embedding-Large-VN-Mixed-V1
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [GreenNode/GreenNode-Embedding-Large-VN-Mixed-V1](https://huggingface.co/GreenNode/GreenNode-Embedding-Large-VN-Mixed-V1). It maps sentences & paragraphs to a 102... | [] |
huskyhong/wzryyykl-gjmy-bslwq | huskyhong | 2026-01-13T18:13:58Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-13T09:41:00Z | # 王者荣耀语音克隆-干将莫邪-冰霜恋舞曲
基于 VoxCPM 的王者荣耀英雄及皮肤语音克隆模型系列，支持多种英雄和皮肤的语音风格克隆与生成。
## 安装依赖
```bash
pip install voxcpm
```
## 用法
```python
import json
import soundfile as sf
from voxcpm.core import VoxCPM
from voxcpm.model.voxcpm import LoRAConfig
# 配置基础模型路径（示例路径，请根据实际情况修改）
base_model_path = "G:\mergelora\... | [] |
phospho-app/ACT-dataset_navidad_v20-g4c09dmdhk | phospho-app | 2025-11-22T16:21:25Z | 0 | 0 | phosphobot | [
"phosphobot",
"safetensors",
"act",
"robotics",
"dataset:DavidVillanueva/dataset_navidad_v20",
"region:us"
] | robotics | 2025-11-22T15:29:00Z | ---
datasets: DavidVillanueva/dataset_navidad_v20
library_name: phosphobot
pipeline_tag: robotics
model_name: act
tags:
- phosphobot
- act
task_categories:
- robotics
---
# act model - 🧪 phosphobot training pipeline
- **Dataset**: [DavidVillanueva/dataset_navidad_v20](https://huggingface.co/datasets/DavidVillanueva/... | [] |
renshou753/marian-finetuned-kde4-en-to-fr | renshou753 | 2025-10-11T04:15:07Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"marian",
"text2text-generation",
"translation",
"generated_from_trainer",
"dataset:kde4",
"base_model:Helsinki-NLP/opus-mt-en-fr",
"base_model:finetune:Helsinki-NLP/opus-mt-en-fr",
"license:apache-2.0",
"model-index",
"endpoints_compatible",
"... | translation | 2025-10-11T03:39:49Z | <!-- 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. -->
# marian-finetuned-kde4-en-to-fr
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki... | [] |
mradermacher/Qwen3.5-40B-RoughHouse-Claude-4.6-Opus-Polar-Deckard-Uncensored-Heretic-Thinking-GGUF | mradermacher | 2026-03-18T12:42:15Z | 2,484 | 2 | transformers | [
"transformers",
"gguf",
"unsloth",
"fine tune",
"heretic",
"uncensored",
"abliterated",
"multi-stage tuned.",
"all use cases",
"coder",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",... | null | 2026-03-18T08:43:01Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/70B_Book_stock-GGUF | mradermacher | 2025-10-26T20:13:03Z | 14 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:schonsense/70B_Book_stock",
"base_model:quantized:schonsense/70B_Book_stock",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-26T17:41:30Z | ## 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... | [] |
Sashavse/sage-assistant-lora-F16-GGUF | Sashavse | 2026-04-14T12:14:59Z | 0 | 0 | peft | [
"peft",
"gguf",
"base_model:adapter:unsloth/Qwen2.5-3B-Instruct-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"llama-cpp",
"gguf-my-lora",
"text-generation",
"base_model:Sashavse/sage-assistant-lora",
"base_model:adapter:Sashavse/sage-assistant-lora",
"region:us"
] | text-generation | 2026-04-14T12:14:56Z | # Sashavse/sage-assistant-lora-F16-GGUF
This LoRA adapter was converted to GGUF format from [`Sashavse/sage-assistant-lora`](https://huggingface.co/Sashavse/sage-assistant-lora) via the ggml.ai's [GGUF-my-lora](https://huggingface.co/spaces/ggml-org/gguf-my-lora) space.
Refer to the [original adapter repository](https:... | [] |
mradermacher/Gemma-3-Prompt-Coder-270m-it-Uncensored-GGUF | mradermacher | 2026-04-25T02:52:03Z | 820 | 4 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"dataset:microsoft/rStar-Coder",
"dataset:gokaygokay/prompt-enhancement-75k",
"dataset:gokaygokay/prompt-enhancer-dataset",
"base_model:WithinUsAI/Gemma3-Prompt.Coder.it.Uncensored-270m",
"base_model:quantized:WithinUsAI/Gemma3-Prompt.Coder.it.Unc... | null | 2026-02-07T18:14:53Z | ## 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... | [] |
AI45Research/SafeWork-R1-DeepSeek-70B | AI45Research | 2025-11-06T16:11:48Z | 1 | 0 | null | [
"safetensors",
"llama",
"image-text-to-text",
"conversational",
"multilingual",
"arxiv:2507.18576",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"license:apache-2.0",
"region:us"
] | image-text-to-text | 2025-10-29T11:45:56Z | # SafeWork-R1-DeepSeek-70B
[📂 GitHub](https://github.com/AI45Lab/SafeWork-R1) · [📜Technical Report](https://arxiv.org/abs/2507.18576) · [💬Online Chat](https://safework-r1.ai45.shlab.org.cn/)
<div align="center">
<img alt="image" src="https://cdn-uploads.huggingface.co/production/uploads/666fe1a5b07525f0bde69c27/... | [] |
ImNotTam/finetuned_4_12 | ImNotTam | 2025-12-04T09:00:10Z | 0 | 0 | null | [
"safetensors",
"llm-judge",
"training-checkpoint",
"lora",
"unsloth",
"vi",
"en",
"license:apache-2.0",
"region:us"
] | null | 2025-12-04T08:59:44Z | # finetuned_4_12
Full training folder backup - Toàn bộ checkpoints và models.
## 📂 Cấu trúc Folder
```
train_
├── lora_adapters/ # LoRA adapters
├── README.md
├── zero_shot_metrics.json
└── zero_shot_results.csv
```
## 🚀 Sử Dụng
### 1️⃣ Clone Repo
```bash
git lfs install
git clone https://huggingface.co... | [] |
auarnold/cube_stacking_right_v3_act | auarnold | 2026-04-30T07:54:55Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:auarnold/cube_stacking_right_v3",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-30T06:01:03Z | # 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":... |
zky11235/qwen2-webshop-federated | zky11235 | 2025-09-10T15:02:59Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"safetensors",
"qwen2",
"text-generation",
"federated-learning",
"webshop",
"grpo",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-10T14:42:25Z | # qwen2-webshop-federated
This is a federated learning model based on Qwen2-1.5B-Instruct, trained using GRPO (Generalized Reward Policy Optimization) on the WebShop dataset.
## Model Details
- **Base Model**: Qwen2-1.5B-Instruct
- **Training Method**: Federated Learning with GRPO
- **Dataset**: WebShop
- **Architec... | [
{
"start": 106,
"end": 110,
"text": "GRPO",
"label": "training method",
"score": 0.7635680437088013
},
{
"start": 256,
"end": 284,
"text": "Federated Learning with GRPO",
"label": "training method",
"score": 0.786171555519104
}
] |
arithmetic-circuit-overloading/Qwen3-32B-3d-500K-50K-0.2-reverse-padzero-plus-mul-sub-99-64D-1L-4H-256I | arithmetic-circuit-overloading | 2026-02-27T07:16:31Z | 198 | 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 | 2026-02-27T07:06:23Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Qwen3-32B-3d-500K-50K-0.2-reverse-padzero-plus-mul-sub-99-64D-1L-4H-256I
This model is a fine-tuned version of [Qwen/Qwen3-32B](h... | [
{
"start": 619,
"end": 637,
"text": "Training procedure",
"label": "training method",
"score": 0.7022620439529419
}
] |
OmniSVG/OmniSVG | OmniSVG | 2025-07-21T09:57:44Z | 1,000 | 195 | null | [
"pytorch",
"qwen2_5_vl",
"SVG",
"Image-to-SVG",
"Text-to-SVG",
"text-generation",
"en",
"zh",
"dataset:OmniSVG/MMSVG-Icon",
"dataset:OmniSVG/MMSVG-Illustration",
"arxiv:2504.06263",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"license:apache... | text-generation | 2025-07-21T07:04:58Z | <!-- <div align= "center">
<h1> Official repo for OmniSVG</h1>
</div> -->
<h3 align="center"><strong>OmniSVG: A Unified Scalable Vector Graphics Generation Model</strong></h3>
<div align="center">
<a href='https://arxiv.org/abs/2504.06263'><img src='https://img.shields.io/badge/arXiv-2504.06263-b31b1b.svg'></a>... | [] |
qrk-labs/akeel-cot-qwen3-0.6B-3k | qrk-labs | 2026-02-27T10:03:22Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen3-0.6B",
"base_model:finetune:Qwen/Qwen3-0.6B",
"endpoints_compatible",
"region:us"
] | null | 2026-02-27T09:19:52Z | # Model Card for akeel-cot-0.6b-3k
This model is a fine-tuned version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go... | [] |
mradermacher/Janus-Pro-7B-i1-GGUF | mradermacher | 2025-12-05T04:05:01Z | 226 | 0 | transformers | [
"transformers",
"gguf",
"muiltimodal",
"text-to-image",
"unified-model",
"en",
"base_model:deepseek-community/Janus-Pro-7B",
"base_model:quantized:deepseek-community/Janus-Pro-7B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | text-to-image | 2025-11-20T00:09:08Z | ## 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_... | [] |
diman84/autotrain-meta-rating | diman84 | 2025-09-20T11:04:26Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"autotrain",
"text-generation-inference",
"text-generation",
"peft",
"conversational",
"base_model:meta-llama/Llama-3.2-3B",
"base_model:finetune:meta-llama/Llama-3.2-3B",
"license:other",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-20T11:01:13Z | # Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path... | [] |
parlange/swin-gravit-s3 | parlange | 2025-09-06T22:17:33Z | 4 | 0 | timm | [
"timm",
"pytorch",
"safetensors",
"vision-transformer",
"image-classification",
"swin",
"gravitational-lensing",
"strong-lensing",
"astronomy",
"astrophysics",
"dataset:parlange/gravit-c21",
"arxiv:2509.00226",
"license:apache-2.0",
"model-index",
"region:us"
] | image-classification | 2025-09-06T22:16:40Z | # 🌌 swin-gravit-s3
🔭 This model is part of **GraViT**: Transfer Learning with Vision Transformers and MLP-Mixer for Strong Gravitational Lens Discovery
🔗 **GitHub Repository**: [https://github.com/parlange/gravit](https://github.com/parlange/gravit)
## 🛰️ Model Details
- **🤖 Model Type**: Swin
- **🧪 Experimen... | [] |
wheattoast11/OmniCoder-9B-Zero-Phase1-SFT | wheattoast11 | 2026-03-28T08:07:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trackio",
"hf_jobs",
"sft",
"trl",
"trackio:https://wheattoast11-trackio.hf.space?project=zero-rl&runs=phase1-sft-tool-calling&sidebar=collapsed",
"base_model:Tesslate/OmniCoder-9B",
"base_model:finetune:Tesslate/OmniCoder-9B",
"endpoints... | null | 2026-03-28T03:44:45Z | # Model Card for OmniCoder-9B-Zero-Phase1-SFT
This model is a fine-tuned version of [Tesslate/OmniCoder-9B](https://huggingface.co/Tesslate/OmniCoder-9B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time mac... | [] |
alexgusevski/Einstein-v6.1-Llama3-8B-mlx-4Bit | alexgusevski | 2026-01-12T20:37:17Z | 6 | 0 | mlx | [
"mlx",
"safetensors",
"llama",
"axolotl",
"generated_from_trainer",
"instruct",
"finetune",
"chatml",
"gpt4",
"synthetic data",
"science",
"physics",
"chemistry",
"biology",
"math",
"llama3",
"mlx-my-repo",
"en",
"dataset:allenai/ai2_arc",
"dataset:camel-ai/physics",
"dataset... | null | 2026-01-12T20:36:53Z | # alexgusevski/Einstein-v6.1-Llama3-8B-mlx-4Bit
The Model [alexgusevski/Einstein-v6.1-Llama3-8B-mlx-4Bit](https://huggingface.co/alexgusevski/Einstein-v6.1-Llama3-8B-mlx-4Bit) was converted to MLX format from [Weyaxi/Einstein-v6.1-Llama3-8B](https://huggingface.co/Weyaxi/Einstein-v6.1-Llama3-8B) using mlx-lm version *... | [] |
Mawdistical/Kuwutu-Lite-7B | Mawdistical | 2025-09-19T18:33:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"nsfw",
"explicit",
"roleplay",
"mixed-AI",
"furry",
"anthro",
"dark",
"chat",
"conversational",
"en",
"dataset:Delta-Vector/Hydrus-General-Reasoning",
"dataset:Delta-Vector/Hydrus-IF-Mix-Ai2",
"dataset:Delta-Vector/Hydrus-Ar... | text-generation | 2025-09-08T04:39:24Z | <!--
COLORS:
--accent-red: #722F37;
--accent-grey: #AAAAAA;
--black: #000000;
--white: #FFFFFF;
-->
<div style="background-color: #FFFFFF; color: #000000; padding: 28px 18px; border-radius: 10px; width: 100%; border: 1px solid #DDDDDD;">
<div align="center">
<h1 style="color: #000000; margin-bottom: 18p... | [] |
shin0412/JetsonNanoTracking | shin0412 | 2026-04-16T04:37:32Z | 0 | 0 | none | [
"none",
"jetson-nano",
"object-tracking",
"tensorrt",
"opencv",
"yolo",
"eco-tracker",
"license:other",
"region:us"
] | null | 2026-04-16T04:15:38Z | # JetsonNanoTracking
Runtime model artifacts used by the Jetson Nano person-tracking tests in the `MyECOTracker` / `JetsonNanoTracking` project.
## Included files
- `runtime_test_models/tracker/resnet18_vggmconv1_otb_dual_large_fp16.engine`
- TensorRT FP16 engine used by the real-video tracking profile.
- Runtim... | [] |
TAUR-dev/M-skillfactory_sft_countdown_3arg_promptvariants_qrepeat1_reflections5-sft | TAUR-dev | 2025-09-10T05:21:05Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2025-09-10T05:20:22Z | # M-skillfactory_sft_countdown_3arg_promptvariants_qrepeat1_reflections5-sft
This model was created as part of the **skillfactory_sft_countdown_3arg_promptvariants_qrepeat1_reflections5** experiment using the SkillFactory experiment management system.
## Model Details
- **Training Method**: LLaMAFactory SFT (Supervi... | [
{
"start": 355,
"end": 358,
"text": "sft",
"label": "training method",
"score": 0.8279229402542114
},
{
"start": 564,
"end": 567,
"text": "sft",
"label": "training method",
"score": 0.7832388281822205
}
] |
solailabs/wmt22-cometkiwi-da-pruned-k4-xs | solailabs | 2026-04-21T07:00:51Z | 0 | 0 | comet | [
"comet",
"translation",
"quality-estimation",
"reference-free",
"cometkiwi",
"pruning",
"multilingual",
"base_model:Unbabel/wmt22-cometkiwi-da",
"base_model:finetune:Unbabel/wmt22-cometkiwi-da",
"license:apache-2.0",
"region:us"
] | translation | 2026-04-20T09:16:28Z | # wmt22-cometkiwi-da-pruned-k4-xs
A compressed version of [Unbabel/wmt22-cometkiwi-da](https://huggingface.co/Unbabel/wmt22-cometkiwi-da) — a reference-free machine-translation quality estimation model (source + MT only, no human reference required).
**Smallest variant** — K=4 prune + int8 + fp16 storage, ~1 GB on di... | [] |
gold24k/deepseek-v3.2-speciale | gold24k | 2026-01-24T13:58:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"deepseek_v32",
"text-generation",
"base_model:deepseek-ai/DeepSeek-V3.2-Exp-Base",
"base_model:finetune:deepseek-ai/DeepSeek-V3.2-Exp-Base",
"license:mit",
"endpoints_compatible",
"fp8",
"region:us"
] | text-generation | 2026-01-24T13:58:15Z | # DeepSeek-V3.2: Efficient Reasoning & Agentic AI
<!-- markdownlint-disable first-line-h1 -->
<!-- markdownlint-disable html -->
<!-- markdownlint-disable no-duplicate-header -->
<div align="center">
<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-... | [] |
iamshnoo/combined_without_metadata_500m | iamshnoo | 2026-04-02T14:39:14Z | 93 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"metadata-localization",
"global",
"500m",
"without-metadata",
"pretraining",
"arxiv:2601.15236",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-18T18:10:45Z | # combined_without_metadata_500m
## Summary
This repo contains the global combined model at the final 10k-step checkpoint for the metadata localization project. It was trained from scratch on the project corpus, using the Llama 3.2 tokenizer and vocabulary.
## Variant Metadata
- Stage: `pretrain`
- Family: `global`... | [] |
Sumiokashi/qwen3-4b-structured-3k-mix-sft_lora-repo_ver26 | Sumiokashi | 2026-02-22T09:46:10Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:daichira/structured-3k-mix-sft",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-22T09:46:04Z | ＜【課題】qwen3-4b-structured-3k-mix-sft -output-lora_ver26＞
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 i... | [
{
"start": 157,
"end": 162,
"text": "QLoRA",
"label": "training method",
"score": 0.7592991590499878
}
] |
jaya-sandeep-22/MIDAS-PYTORCH | jaya-sandeep-22 | 2025-12-25T12:46:48Z | 0 | 0 | pytorch | [
"pytorch",
"depth-estimation",
"computer-vision",
"midas",
"opencv",
"monocular-depth",
"license:mit",
"region:us"
] | depth-estimation | 2025-12-25T12:10:31Z | 
# 🧠... | [] |
sthaps/typhoon2.5-qwen3-4b-heretic | sthaps | 2026-04-13T04:08:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"arxiv:2412.13702",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-13T04:07:37Z | # This is a decensored version of [typhoon-ai/typhoon2.5-qwen3-4b](https://huggingface.co/typhoon-ai/typhoon2.5-qwen3-4b), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | per layer |
| **attn.o_proj.max_weight... | [] |
jc-builds/sd2-inpainting-coreml | jc-builds | 2026-01-15T05:16:36Z | 0 | 2 | null | [
"coreml",
"stable-diffusion",
"inpainting",
"ios",
"macos",
"apple-silicon",
"image-editing",
"image-to-image",
"base_model:stabilityai/stable-diffusion-2-inpainting",
"base_model:finetune:stabilityai/stable-diffusion-2-inpainting",
"license:other",
"region:us"
] | image-to-image | 2025-12-20T18:05:56Z | # Stable Diffusion 2.1 Inpainting (Core ML)
This is a **Core ML conversion** of [Stable Diffusion 2.1 Inpainting](https://huggingface.co/stabilityai/stable-diffusion-2-inpainting) optimized for on-device inference on Apple Silicon.
## Model Details
| Property | Value |
|----------|-------|
| **Original Model** | Sta... | [] |
ShuaiYang03/instructvla_pretraining_v2_libero_goal_wrist-image_aug | ShuaiYang03 | 2025-09-18T03:27:35Z | 6 | 1 | null | [
"vision-language-model",
"manipulation",
"robotics",
"dataset:IPEC-COMMUNITY/libero_goal_no_noops_1.0.0_lerobot",
"base_model:nvidia/Eagle2-2B",
"base_model:finetune:nvidia/Eagle2-2B",
"region:us"
] | robotics | 2025-09-09T02:47:38Z | # Model Card for InstructVLA LIBERO-Goal
- checkpoints: the model in `.pt` format
- eval: the evaluation results with 3 random seeds
- dataset_statistics.json: the normalization statistics for the dataset
## Evaluation:
```bash
#!/bin/bash
CKPT_LIST=(
"path/to/checkpoints/step-039000-epoch-192-loss=0.0263.pt"... | [] |
Hocc493/act_kbot_policy | Hocc493 | 2025-10-23T10:50:57Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:Hocc493/kbot-demos",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-23T10:50:50Z | # 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":... |
quangdung/Qwen2.5-1.5b-leetcode-math-dare-ties | quangdung | 2026-03-05T01:35:45Z | 30 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"mergekit",
"merge",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-05T01:34:47Z | # Qwen2.5-1.5b-coder-math-thinking-slerp
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
### Models Merged
The following models we... | [
{
"start": 219,
"end": 224,
"text": "SLERP",
"label": "training method",
"score": 0.7083226442337036
},
{
"start": 691,
"end": 696,
"text": "SLERP",
"label": "training method",
"score": 0.7550352811813354
}
] |
Octen/Octen-Embedding-8B | Octen | 2026-02-09T04:11:02Z | 6,568 | 148 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"qwen3",
"sentence-similarity",
"feature-extraction",
"embedding",
"text-embedding",
"retrieval",
"en",
"zh",
"multilingual",
"base_model:Qwen/Qwen3-Embedding-8B",
"base_model:finetune:Qwen/Qwen3-Embedding-8B",
"license:apache-2.0",
"text-embedding... | sentence-similarity | 2025-12-23T08:14:22Z | # Octen-Embedding-8B
Octen-Embedding-8B is a text embedding model developed by [Octen](https://octen.ai/) for semantic search and retrieval tasks. This model is fine-tuned from [Qwen/Qwen3-Embedding-8B](https://huggingface.co/Qwen/Qwen3-Embedding-8B) and supports multiple languages, providing high-quality embeddings f... | [] |
EuroEval/european-values-pipeline | EuroEval | 2025-08-21T08:17:07Z | 0 | 0 | sklearn | [
"sklearn",
"european-values",
"tabular-classification",
"license:apache-2.0",
"region:us"
] | tabular-classification | 2025-08-21T08:16:59Z | # European Values Evaluation Pipeline
This repository contains a trained scikit-learn pipeline for evaluating the European
values of a large language model, and has been trained on data from the [European Values
Study](https://europeanvaluesstudy.eu/).
## Usage
You can use this pipeline to evaluate the European val... | [] |
GliteTech/sandwich-nv-small | GliteTech | 2026-03-26T06:22:41Z | 26 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"generated_from_trainer",
"en",
"base_model:GliteTech/wordnet-network-predictor",
"base_model:finetune:GliteTech/wordnet-network-predictor",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-03-23T17:40:56Z | <!-- 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. -->
# sandwich-nv-small
This model is a fine-tuned version of [GliteTech/wordnet-network-predictor](https://huggingface.co/GliteTech/wo... | [] |
mmrech/ACE2-ERA5 | mmrech | 2026-03-17T04:00:42Z | 0 | 0 | fme | [
"fme",
"license:apache-2.0",
"region:us"
] | null | 2026-03-17T04:00:41Z | <img src="ACE-logo.png" alt="Logo for the ACE Project" style="width: auto; height: 50px;">
# ACE2-ERA5
Ai2 Climate Emulator (ACE) is a family of models designed to simulate atmospheric variability from the time scale of days to centuries.
**Disclaimer: ACE models are research tools and should not be used for operati... | [] |
rbelanec/train_siqa_456_1760637829 | rbelanec | 2025-10-19T00:45:57Z | 1 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"llama-factory",
"transformers",
"text-generation",
"conversational",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | text-generation | 2025-10-18T16:32:58Z | <!-- 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. -->
# train_siqa_456_1760637829
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta... | [] |
whl66988/gemma-4-26B-A4B | whl66988 | 2026-04-08T03:15:27Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-08T03:15:27Z | <div align="center">
<img src=https://ai.google.dev/gemma/images/gemma4_banner.png>
</div>
<p align="center">
<a href="https://huggingface.co/collections/google/gemma-4" target="_blank">Hugging Face</a> |
<a href="https://github.com/google-gemma" target="_blank">GitHub</a> |
<a href="https://blog.google... | [] |
McG-221/Dolphin-X1-8B-mlx-8Bit | McG-221 | 2025-12-18T20:47:04Z | 102 | 1 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mlx",
"conversational",
"base_model:dphn/Dolphin-X1-8B",
"base_model:quantized:dphn/Dolphin-X1-8B",
"license:llama3.1",
"text-generation-inference",
"endpoints_compatible",
"8-bit",
"region:us"
] | text-generation | 2025-12-18T20:46:20Z | # McG-221/Dolphin-X1-8B-mlx-8Bit
The Model [McG-221/Dolphin-X1-8B-mlx-8Bit](https://huggingface.co/McG-221/Dolphin-X1-8B-mlx-8Bit) was converted to MLX format from [dphn/Dolphin-X1-8B](https://huggingface.co/dphn/Dolphin-X1-8B) using mlx-lm version **0.28.3**.
## Use with mlx
```bash
pip install mlx-lm
```
```pytho... | [] |
HafeezKing/career-advisor-t5-next | HafeezKing | 2025-09-09T18:31:10Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2025-09-09T17:52:12Z | <!-- 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. -->
# career-advisor-t5-next
This model is a fine-tuned version of [HafeezKing/career-advisor-t5](https://huggingface.co/HafeezKing/car... | [] |
andrebragamkt/morena | andrebragamkt | 2026-04-16T23:07:25Z | 19 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-04-16T23:07:19Z | # morena
<Gallery />
## Model description
Character LoRA of "morena" — a young Brazilian woman with long curly blonde-highlighted hair.
Trigger word: morena
Best used for realistic photography, Instagram/Reels content and adult themes.
Trained on Flux Image Z Turbo with 25 photos using natural lan... | [
{
"start": 269,
"end": 287,
"text": "Flux Image Z Turbo",
"label": "training method",
"score": 0.7938522100448608
}
] |
VimalrajS04/Major_pro | VimalrajS04 | 2025-09-23T13:43:07Z | 0 | 0 | null | [
"onnx",
"safetensors",
"virtual-try-on",
"diffusion",
"idm-vton",
"en",
"arxiv:2403.05139",
"license:cc-by-nc-sa-4.0",
"region:us"
] | null | 2025-09-23T13:18:35Z | ---
license: cc-by-nc-sa-4.0
language: en
tags:
- virtual-try-on
- diffusion
- idm-vton
---
<
div align="center">
<h1>IDM-VTON: Improving Diffusion Models for Authentic Virtual Try-on in the Wild</h1>
<a href='https://idm-vton.github.io'><img src='https://img.shields.io/badge/Project-Page-green'></a>
<a href='https:... | [] |
mats-10-sprint-cs-jb/loracles-jane-street-warmup-qwen3-14b-crosslora | mats-10-sprint-cs-jb | 2026-04-23T21:42:14Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen",
"qwen2",
"qwen3",
"lora",
"cross-lora",
"transformers",
"text-generation",
"conversational",
"arxiv:2508.05232",
"base_model:Qwen/Qwen3-14B",
"base_model:adapter:Qwen/Qwen3-14B",
"region:us"
] | text-generation | 2026-04-23T21:42:06Z | # loracles-jane-street-warmup-qwen3-14b-crosslora
This repo contains a Qwen3-14B LoRA obtained by transferring the behavior of [`jane-street/dormant-model-warmup`](https://huggingface.co/jane-street/dormant-model-warmup) with a Cross-LoRA-style pipeline onto [`Qwen/Qwen3-14B`](https://huggingface.co/Qwen/Qwen3-14B).
... | [] |
hbseong/internvla_pick_and_place_pos5_ep208_so101_baseline | hbseong | 2025-12-01T07:24:09Z | 4 | 0 | lerobot | [
"lerobot",
"safetensors",
"internvla",
"robotics",
"dataset:hbseong/record-pick-and-place-pos5-so101",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-01T07:23:48Z | # Model Card for internvla
<!-- 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... | [] |
mradermacher/TechniqueRAG-ZS-Ministral-8B-GGUF | mradermacher | 2025-09-08T21:30:21Z | 53 | 0 | transformers | [
"transformers",
"gguf",
"MITRE ATT&CK",
"Adversarial Techniques Annotation",
"Threat Intelligence",
"Security",
"en",
"dataset:qcri-cs/TechniqueRAG-Datasets",
"base_model:QCRI/TechniqueRAG-ZS-Ministral-8B",
"base_model:quantized:QCRI/TechniqueRAG-ZS-Ministral-8B",
"license:apache-2.0",
"endpoi... | null | 2025-09-08T20:11:59Z | ## 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... | [] |
DQN-Labs-Community/DQN-GPT-v0.2-MLX-4bit | DQN-Labs-Community | 2026-03-11T11:12:17Z | 43 | 1 | null | [
"safetensors",
"mistral",
"base_model:DQN-Labs/ministral-3-3B-it2512-mlx-quantized",
"base_model:quantized:DQN-Labs/ministral-3-3B-it2512-mlx-quantized",
"license:apache-2.0",
"4-bit",
"region:us"
] | null | 2026-03-11T11:04:00Z | # DQN-GPT v0.2
DQN-GPT v0.2 is a 3.4B parameter instruction-following language model designed with a single guiding philosophy:
AI with obedience in mind.
The model prioritizes precise instruction adherence, reliable formatting, and predictable behavior for developers building local AI systems.
⸻
## Model Overview... | [] |
RylanSchaeffer/mem_Qwen3-62M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_8 | RylanSchaeffer | 2025-09-21T02:16:15Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-21T02:16:08Z | <!-- 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. -->
# mem_Qwen3-62M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_8
This model is a fine-tuned version of [](https://huggingface.co/) on a... | [] |
aphoticshaman/elle-72b-math-v2 | aphoticshaman | 2025-12-11T20:34:38Z | 3 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"math",
"reasoning",
"lora",
"numina",
"text-generation",
"conversational",
"dataset:AI-MO/NuminaMath-CoT",
"base_model:Qwen/Qwen2.5-72B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-72B-Instruct",
"license:apache-2.0",
"4-bit",
"bitsandbytes",
"region:us"... | text-generation | 2025-12-11T07:28:24Z | # Elle-72B-Math-v2
## Model Description
Elle-72B-Math-v2 is a LoRA adapter fine-tuned on [Qwen/Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) for mathematical reasoning using the NuminaMath-CoT dataset.
## Model Details
- **Base Model**: Qwen/Qwen2.5-72B-Instruct
- **Adapter Type**: LoRA
- ... | [
{
"start": 421,
"end": 435,
"text": "NuminaMath-CoT",
"label": "training method",
"score": 0.7971941828727722
}
] |
mradermacher/Gemma-AIO-GGUF | mradermacher | 2025-08-29T15:31:16Z | 8 | 1 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"gemma3",
"en",
"base_model:GazTrab/Gemma-AIO",
"base_model:quantized:GazTrab/Gemma-AIO",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-29T15:18:07Z | ## 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... | [] |
mradermacher/aegis-qwen2vl-3b-GGUF | mradermacher | 2026-03-14T15:01:18Z | 517 | 0 | transformers | [
"transformers",
"gguf",
"browser-qa",
"visual-agent",
"qwen2.5-vl",
"lora-merged",
"fine-tuned",
"en",
"base_model:sanaX3065/aegis-qwen2vl-3b",
"base_model:quantized:sanaX3065/aegis-qwen2vl-3b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-14T11:33:14Z | ## 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... | [] |
NetherQuartz/ilo-toki-gemma-2-2b | NetherQuartz | 2025-10-14T03:11:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/gemma-2-2b",
"base_model:finetune:google/gemma-2-2b",
"endpoints_compatible",
"region:us"
] | null | 2025-09-28T00:35:21Z | # Model Card for ilo-toki-gemma-2-2b
This model is a fine-tuned version of [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could o... | [] |
DavidAU/Qwen3-MOE-4x0.6B-2.4B-Writing-Thunder-V1.2 | DavidAU | 2025-08-28T08:39:35Z | 36 | 8 | transformers | [
"transformers",
"safetensors",
"qwen3_moe",
"text-generation",
"programming",
"code generation",
"code",
"codeqwen",
"moe",
"coding",
"coder",
"qwen2",
"chat",
"qwen",
"qwen-coder",
"mixture of experts",
"4 experts",
"2 active experts",
"40k context",
"qwen3",
"finetune",
"... | text-generation | 2025-08-27T01:52:07Z | <h2>Qwen3-MOE-4x0.6B-2.4B-Writing-Thunder-V1.2</h2>
<small>(this version is stronger in coding, than V1 and V1.1)</small>
<img src="writing-thunder.jpg" style="float:right; width:300px; height:300px; padding:10px;">
This repo contains the full precision source code, in "safe tensors" format to generate GGUFs, GPTQ, ... | [] |
gsjang/ko-llama-3-korean-bllossom-8b-x-meta-llama-3-8b-instruct-arcee_fusion-50_50 | gsjang | 2025-08-29T00:57:58Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:MLP-KTLim/llama-3-Korean-Bllossom-8B",
"base_model:merge:MLP-KTLim/llama-3-Korean-Bllossom-8B",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:merge:meta-llama/Meta-Llama-... | text-generation | 2025-08-29T00:52:05Z | # ko-llama-3-korean-bllossom-8b-x-meta-llama-3-8b-instruct-arcee_fusion-50_50
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Arcee Fusion](https://arcee.ai) merge method using [meta-llama/M... | [] |
bird778/starcoder2-3b | bird778 | 2026-04-08T14:05:26Z | 62 | 0 | transformers | [
"transformers",
"safetensors",
"starcoder2",
"text-generation",
"code",
"dataset:bigcode/the-stack-v2-train",
"arxiv:2305.13245",
"arxiv:2205.14135",
"arxiv:2004.05150",
"arxiv:2207.14255",
"arxiv:2402.19173",
"license:bigcode-openrail-m",
"model-index",
"text-generation-inference",
"end... | text-generation | 2026-04-08T14:05:26Z | # StarCoder2
<center>
<img src="https://huggingface.co/datasets/bigcode/admin_private/resolve/main/starcoder2_banner.png" alt="SC2" width="900" height="600">
</center>
## Table of Contents
1. [Model Summary](##model-summary)
2. [Use](##use)
3. [Limitations](##limitations)
4. [Training](##training)
5. [License](... | [
{
"start": 585,
"end": 608,
"text": "Grouped Query Attention",
"label": "training method",
"score": 0.7393161058425903
}
] |
MatteoFasulo/ModernBERT-base-NER | MatteoFasulo | 2026-02-13T17:34:33Z | 11 | 0 | transformers | [
"transformers",
"safetensors",
"modernbert",
"token-classification",
"generated_from_trainer",
"named-entity-recognition",
"en",
"dataset:lhoestq/conll2003",
"arxiv:2412.13663",
"base_model:answerdotai/ModernBERT-base",
"base_model:finetune:answerdotai/ModernBERT-base",
"license:apache-2.0",
... | token-classification | 2026-02-13T16:35:34Z | # ModernBERT-base-NER
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) for Named Entity Recognition (NER) tasks on [conll2003](https://huggingface.co/datasets/lhoestq/conll2003) dataset.
## Model Description
ModernBERT-base-NER is a token classif... | [
{
"start": 2,
"end": 21,
"text": "ModernBERT-base-NER",
"label": "training method",
"score": 0.8224696516990662
},
{
"start": 282,
"end": 301,
"text": "ModernBERT-base-NER",
"label": "training method",
"score": 0.8354083895683289
}
] |
Leberkaesweckle/Drop_orange_block_into_green_basket_SO101_NCT_4_policy | Leberkaesweckle | 2026-01-19T13:53:59Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:Leberkaesweckle/Drop_orange_block_into_green_basket_SO101_NCT_4",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-19T13:53:47Z | # 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":... |
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