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 |
|---|---|---|---|---|---|---|---|---|---|---|
jahyungu/Falcon3-7B-Instruct-PubMedQA | jahyungu | 2026-03-03T08:30:27Z | 47 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:tiiuae/Falcon3-7B-Instruct",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:tiiuae/Falcon3-7B-Instruct",
"license:other",
"region:us"
] | text-generation | 2026-02-27T12:02:35Z | <!-- 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. -->
# Falcon3-7B-Instruct-PubMedQA
This model is a fine-tuned version of [tiiuae/Falcon3-7B-Instruct](https://huggingface.co/tiiuae/Fal... | [] |
salmoncode/policy-yellow | salmoncode | 2025-12-18T14:16:22Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:salmoncode/record-yellow",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-18T14:15:50Z | # 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":... |
Zxlee1811/LolTesting | Zxlee1811 | 2025-12-27T09:00:59Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:lerobot/svla_so100_stacking",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-27T08:59:34Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
mradermacher/Discord-Micae-Hermes-3-3B-abliterated-GGUF | mradermacher | 2025-08-31T22:49:50Z | 86 | 2 | transformers | [
"transformers",
"gguf",
"causal-lm",
"text-generation",
"instruct",
"chat",
"fine-tuned",
"merged-lora",
"llama-3",
"hermes",
"discord-dataset",
"conversational-ai",
"chatml",
"pytorch",
"open-weights",
"3b-parameters",
"abliterated",
"en",
"dataset:mookiezi/Discord-OpenMicae",
... | text-generation | 2025-08-31T22:32:46Z | ## 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... | [] |
AnonymousCS/populism_classifier_250 | AnonymousCS | 2025-08-30T05:48:05Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_multilingual_roberta_base",
"base_model:finetune:AnonymousCS/populism_multilingual_roberta_base",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"regio... | text-classification | 2025-08-30T05:46:57Z | <!-- 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. -->
# populism_classifier_250
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingfac... | [] |
cgifbribcgfbi/gemma-2-27b-chem-gemma-2-self-rand-in1-c0 | cgifbribcgfbi | 2025-09-11T18:40:05Z | 3 | 0 | peft | [
"peft",
"safetensors",
"gemma2",
"text-generation",
"axolotl",
"base_model:adapter:byroneverson/gemma-2-27b-it-abliterated",
"lora",
"transformers",
"conversational",
"dataset:gemma-2-self-dset-rand-in1-c0_user_5000.jsonl",
"base_model:byroneverson/gemma-2-27b-it-abliterated",
"license:gemma",... | text-generation | 2025-09-11T17:20:55Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
artificialguybr/XBOXAVATAR-REDMOND-ZIMAGE | artificialguybr | 2026-02-26T22:48:51Z | 11 | 1 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:Tongyi-MAI/Z-Image-Turbo",
"base_model:adapter:Tongyi-MAI/Z-Image-Turbo",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-02-26T22:48:30Z | # Xbox Avatar REDMOND LORA is here!
<Gallery />
## Model description
#Xbox Avatar REDMOND LORA is here!
I'm grateful for the GPU time from [Redmond.AI](https://redmond.ai/) that allowed me to make this model!
This LoRA was trained on Xbox Avatar style images. It generates high-quality xbox av... | [] |
broadfield-dev/gemma-3-270m-tuned-0106-1020 | broadfield-dev | 2026-01-06T09:21:13Z | 1 | 1 | null | [
"safetensors",
"gemma3_text",
"causal_lm",
"generated_from_trainer",
"dataset:microsoft/rStar-Coder",
"base_model:google/gemma-3-270m",
"base_model:finetune:google/gemma-3-270m",
"license:mit",
"region:us"
] | null | 2026-01-06T09:20:58Z | # gemma-3-270m-tuned-0106-1020
This model is a fine-tuned version of [google/gemma-3-270m](https://huggingface.co/google/gemma-3-270m) on the [microsoft/rStar-Coder](https://huggingface.co/microsoft/rStar-Coder) dataset.
## Training Details
- **Task:** CAUSAL_LM
- **Epochs:** 1
- **Learning Rate:** 2e-05
- **Gradient A... | [] |
lvwerra/qwen3-4b-code-lora-lr2e4 | lvwerra | 2026-01-12T15:06:44Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"hf_jobs",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"endpoints_compatible",
"region:us"
] | null | 2026-01-08T14:44:41Z | # Model Card for qwen3-4b-code-lora-lr2e4
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 ... | [] |
Junwei-Xi/Dual-Data-Alignment | Junwei-Xi | 2025-12-16T03:36:18Z | 0 | 1 | null | [
"dataset:Junwei-Xi/DDA-Training-Set",
"arxiv:2505.14359",
"license:apache-2.0",
"region:us"
] | null | 2025-12-16T03:04:02Z | # Dual Data Alignment (NeurIPS'25 Spotlight)
This repository contains the official checkpoint (`DDA_ckpt.pth`) for the paper **"Dual Data Alignment Makes AI-Generated Image Detector Easier Generalizable"**, accepted by **NeurIPS 2025 as a Spotlight**.
[![GitHub](https://img.shields.io/badge/GitHub-Project%20Page-blac... | [] |
mchlxo/pythia-gsm8k-70m | mchlxo | 2026-03-31T05:58:05Z | 0 | 0 | peft | [
"peft",
"safetensors",
"pythia",
"gsm8k",
"qlora",
"lora",
"contamination-study",
"dataset:gsm8k",
"base_model:EleutherAI/pythia-70m",
"base_model:adapter:EleutherAI/pythia-70m",
"license:apache-2.0",
"region:us"
] | null | 2026-03-31T05:58:02Z | # mchlxo/pythia-gsm8k-70m
QLoRA adapter for **EleutherAI/pythia-70m** (70M parameters) fine-tuned on
the [GSM8K](https://huggingface.co/datasets/gsm8k) training set.
## Training details
| Setting | Value |
|---------|-------|
| Method | QLoRA (4-bit NF4, double quant) |
| LoRA rank | 16 |
| LoRA alpha | 32 |
| Targe... | [
{
"start": 240,
"end": 245,
"text": "QLoRA",
"label": "training method",
"score": 0.7100595235824585
}
] |
TheBestMoldyCheese/ppo-LunarLander-v2 | TheBestMoldyCheese | 2026-03-02T08:47:06Z | 154 | 1 | stable-baselines3 | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2026-03-02T08:37:36Z | # **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
```python
import gymnasium as gym
from stable_baselines3 import PPO
from stable_basel... | [] |
MattBou00/llama-3-2-1b-detox_v1f_RRETRT_Again_ROUND1 | MattBou00 | 2025-09-22T12:04:29Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"trl",
"ppo",
"reinforcement-learning",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | reinforcement-learning | 2025-09-22T12:03:30Z | # TRL Model
This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
## Usage
To use this model for inference, first install the TRL... | [] |
Indeajudicil/audio_cls | Indeajudicil | 2025-09-19T02:19:40Z | 1 | 0 | transformers | [
"transformers",
"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 | 2025-09-19T02:19:21Z | <!-- 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
This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav2vec2-base-k... | [] |
mradermacher/TLDR-Llama-3.2-3B-SmallSFT-GGUF | mradermacher | 2025-09-06T12:19:49Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"trl",
"sft",
"en",
"dataset:tldr-sft",
"base_model:RLHF-And-Friends/TLDR-Llama-3.2-3B-SmallSFT",
"base_model:quantized:RLHF-And-Friends/TLDR-Llama-3.2-3B-SmallSFT",
"endpoints_compatible",
"region:us"
] | null | 2025-09-06T10:14:00Z | ## 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... | [] |
witgaw/STGFORMER_PRETRAINED_STAGE2ONLY_NORM_METR-LA | witgaw | 2025-12-10T14:46:54Z | 0 | 0 | null | [
"safetensors",
"traffic-forecasting",
"time-series",
"graph-neural-network",
"stgformer_pretrained",
"dataset:metr-la",
"region:us"
] | null | 2025-12-10T14:46:52Z | # Spatial-Temporal Graph Transformer (Pretrained) - METR-LA
Spatial-Temporal Graph Transformer (Pretrained) (STGFORMER_PRETRAINED) trained on METR-LA dataset for traffic speed forecasting.
## Model Description
STGFormer pretrained checkpoint for METR-LA. This checkpoint contains pretrained model weights and imputati... | [
{
"start": 52,
"end": 59,
"text": "METR-LA",
"label": "training method",
"score": 0.7311673164367676
},
{
"start": 110,
"end": 130,
"text": "STGFORMER_PRETRAINED",
"label": "training method",
"score": 0.753684937953949
},
{
"start": 143,
"end": 150,
"text"... |
ZafarLocAI/convnext_checkpoints_plane_noplane_26_march_dubai_added | ZafarLocAI | 2026-03-26T13:04:00Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"convnextv2",
"image-classification",
"generated_from_trainer",
"base_model:facebook/convnextv2-large-22k-224",
"base_model:finetune:facebook/convnextv2-large-22k-224",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2026-03-26T11:35:48Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# convnext_checkpoints_plane_noplane_26_march_dubai_added
This model is a fine-tuned version of [facebook/convnextv2-large-22k-224]... | [] |
ByteDance-Seed/AHN-GDN-for-Qwen-2.5-Instruct-3B | ByteDance-Seed | 2025-10-24T02:03:41Z | 15 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"en",
"arxiv:2510.07318",
"base_model:Qwen/Qwen2.5-3B",
"base_model:finetune:Qwen/Qwen2.5-3B",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-08T07:20:34Z | <p align="left">
<img src="https://huggingface.co/datasets/whyu/misc/resolve/main/AHN/ahn_logo_horizontal_small.png" width="700">
</p>
# AHN: Artificial Hippocampus Networks for Efficient Long-Context Modeling
<p align="left">
<a href="https://arxiv.org/abs/2510.07318">
<img src="https://img.shields.io/badge/arXi... | [] |
sachin6624/my-llama-3.2-3b | sachin6624 | 2025-08-06T08:51:33Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:meta-llama/Llama-3.2-3B",
"base_model:finetune:meta-llama/Llama-3.2-3B",
"endpoints_compatible",
"region:us"
] | null | 2025-08-06T06:24:05Z | # Model Card for my-llama-3.2-3b
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B).
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... | [] |
nluick/activation-oracle-multilayer-qwen3-4b-6L-3xlayer-loop-step-5000 | nluick | 2026-01-05T20:24:05Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"base_model:Qwen/Qwen3-4B",
"base_model:adapter:Qwen/Qwen3-4B",
"region:us"
] | null | 2026-01-05T20:23:43Z | # LoRA Adapter for SAE Introspection
This is a LoRA (Low-Rank Adaptation) adapter trained for SAE (Sparse Autoencoder) introspection tasks.
## Base Model
- **Base Model**: `Qwen/Qwen3-4B`
- **Adapter Type**: LoRA
- **Task**: SAE Feature Introspection
## Usage
```python
from transformers import AutoModelForCausalLM,... | [] |
craa/exceptions_exp2_swap_0.3_cost_to_push_5039 | craa | 2025-12-11T14:12:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-10T19:22:23Z | <!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width=... | [] |
James7765/WilR_9 | James7765 | 2025-10-04T02:36:55Z | 1 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"text-generation-inference",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-04T02:02:27Z | Meet our powerful AI model! 🚀 With its advanced capabilities, it can understand and generate human-like text, making it an ideal tool for various applications. 💻
*Key Features:*
- *💡 Advanced Language Understanding*: Our AI model is trained on a vast amount of text data, enabling it to comprehend complex queries a... | [] |
RylanSchaeffer/mem_Qwen3-62M_minerva_math_rep_1000_sbst_1.0000_epch_1_ot_2 | RylanSchaeffer | 2025-11-02T10:52:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-02T10:52:39Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mem_Qwen3-62M_minerva_math_rep_1000_sbst_1.0000_epch_1_ot_2
This model is a fine-tuned version of [](https://huggingface.co/) on ... | [] |
FrederickSundeep/nova2.5-14b-code-adapter | FrederickSundeep | 2026-04-27T17:29:09Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"unsloth",
"sft",
"base_model:FrederickSundeep/nova2-14b",
"base_model:finetune:FrederickSundeep/nova2-14b",
"endpoints_compatible",
"region:us"
] | null | 2026-04-26T17:13:57Z | # Model Card for nova2.5-14b-code-adapter
This model is a fine-tuned version of [FrederickSundeep/nova2-14b](https://huggingface.co/FrederickSundeep/nova2-14b).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a ti... | [] |
jkazdan/mem_Qwen3-34M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_1_sft | jkazdan | 2025-12-18T08:33:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:RylanSchaeffer/mem_Qwen3-34M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_1",
"base_model:finetune:RylanSchaeffer/mem_Qwen3-34M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_... | text-generation | 2025-12-18T08:33:49Z | # Model Card for mem_Qwen3-34M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_1_sft
This model is a fine-tuned version of [RylanSchaeffer/mem_Qwen3-34M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_1](https://huggingface.co/RylanSchaeffer/mem_Qwen3-34M_minerva_math_rep_100_sbst_1.0000_epch_1_ot_1).
It has been trained using ... | [] |
machinadeusex/ms-marco-MiniLM-L6-v2 | machinadeusex | 2026-03-14T22:28:05Z | 10 | 0 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"jax",
"onnx",
"safetensors",
"openvino",
"bert",
"text-classification",
"transformers",
"text-ranking",
"en",
"dataset:sentence-transformers/msmarco",
"base_model:cross-encoder/ms-marco-MiniLM-L12-v2",
"base_model:quantized:cross-encoder/ms-marco-MiniLM... | text-ranking | 2026-03-14T22:28:05Z | # Cross-Encoder for MS Marco
This model was trained on the [MS Marco Passage Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) task.
The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a... | [] |
akramzine/sam2 | akramzine | 2025-08-15T21:21:40Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"sam2_video",
"feature-extraction",
"mask-generation",
"arxiv:2408.00714",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | mask-generation | 2025-09-07T01:07:00Z | 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/Apertus-8B-Instruct-2509-abliterated-GGUF | mradermacher | 2025-10-03T20:58:17Z | 14 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:nicoboss/Apertus-8B-Instruct-2509-abliterated",
"base_model:quantized:nicoboss/Apertus-8B-Instruct-2509-abliterated",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-03T17:49:42Z | ## 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... | [] |
Kazumay/qwen3-4b-struct-sft-v1 | Kazumay | 2026-02-04T13:17:46Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"conversational",
"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 | 2026-02-02T15:24:21Z | qwen3-4b-structured-output-lora
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **s... | [
{
"start": 133,
"end": 138,
"text": "QLoRA",
"label": "training method",
"score": 0.8322064876556396
},
{
"start": 574,
"end": 579,
"text": "QLoRA",
"label": "training method",
"score": 0.7354162931442261
}
] |
hongtaohao/tempo | hongtaohao | 2026-04-16T03:02:45Z | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | 2026-04-16T02:55:17Z | # TEMPO
This repository contains codes, data and models to reproduce the results reported in the submission of *TEMPO: Transformers for Temporal Disease Progression from Cross-Sectional Data*.
Additionally,
- [`https://github.com/hongtaoh/TEMPO_lowdim`](https://github.com/hongtaoh/TEMPO_lowdim) contains the reproduc... | [] |
KOUJI039/structeval-qwen3-4b-sft-try10 | KOUJI039 | 2026-02-18T18:47:10Z | 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 | 2026-02-18T18:45:09Z | # ＜【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": 0.8308720588684082
},
{
"start": 123,
"end": 127,
"text": "LoRA",
"label": "training method",
"score": 0.8717081546783447
},
{
"start": 169,
"end": 173,
"text": "LoRA",
"lab... |
Muapi/dashcam-view-low-to-mid-quality | Muapi | 2025-08-21T09:31:50Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-21T09:31:38Z | # Dashcam View (Low to Mid Quality)
**Base model**: Flux.1 D
**Trained words**: dashboard
## 🧠 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"
header... | [] |
cyankiwi/Qwen3.6-27B-AWQ-INT4 | cyankiwi | 2026-04-30T21:33:50Z | 446,266 | 42 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"conversational",
"base_model:Qwen/Qwen3.6-27B",
"base_model:quantized:Qwen/Qwen3.6-27B",
"license:apache-2.0",
"endpoints_compatible",
"compressed-tensors",
"region:us"
] | image-text-to-text | 2026-04-22T18:53:06Z | <div align="center">
<img src="https://huggingface.co/buckets/cyankiwi/activation-aware-2.0/resolve/banner/cyankiwi-banner-awq-0.png">
</div>
<div align="left">
<table align="center" style="border-collapse:collapse; border:none;">
<tr style="border:none;">
<td align="right" style="border:none; padding:4p... | [] |
Xamxl/veggie_color_model_v1 | Xamxl | 2025-12-17T23:11:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"facebook",
"meta",
"pytorch",
"llama-3",
"conversational",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"arxiv:2204.05149",
"arxiv:2405.16406",
"license:llama3.2",
"text-generation-inference",
"endpoints_compati... | text-generation | 2025-12-17T23:11:06Z | ## Model Information
The Llama 3.2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). The Llama 3.2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic r... | [] |
tiggerzhtw/stable-diffusion-v1-5 | tiggerzhtw | 2026-04-15T06:37:42Z | 0 | 0 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"arxiv:2207.12598",
"arxiv:2112.10752",
"arxiv:2103.00020",
"arxiv:2205.11487",
"arxiv:1910.09700",
"license:creativeml-openrail-m",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"... | text-to-image | 2026-04-15T06:37:41Z | # Stable Diffusion v1-5 Model Card
### ⚠️ This repository is a mirror of the now deprecated `ruwnayml/stable-diffusion-v1-5`, this repository or organization are not affiliated in any way with RunwayML.
Modifications to the original model card are in <span style="color:crimson">red</span> or <span style="color:darkgre... | [] |
jaygala24/Qwen3-1.7B-ReMax-math-reasoning | jaygala24 | 2026-04-13T05:05:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"reinforcement-learning",
"remax",
"math-reasoning",
"pipelinerl",
"conversational",
"dataset:gsm8k_train",
"dataset:math_train",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"text-ge... | text-generation | 2026-04-13T05:03:50Z | # Qwen3-1.7B-ReMax-math-reasoning
This model is a fine-tuned version of [Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) using **ReMax without KL penalty** for mathematical reasoning.
Trained with [PipelineRL](https://github.com/ServiceNow/PipelineRL).
## Training Details
### Datasets
| Split | Datasets |
|---... | [
{
"start": 134,
"end": 139,
"text": "ReMax",
"label": "training method",
"score": 0.7588191628456116
},
{
"start": 491,
"end": 496,
"text": "ReMax",
"label": "training method",
"score": 0.7834254503250122
},
{
"start": 877,
"end": 882,
"text": "ReMax",
... |
sinjab/mxbai-rerank-large-v2-F16-GGUF | sinjab | 2025-10-11T18:12:20Z | 2 | 0 | gguf | [
"gguf",
"reranker",
"llama.cpp",
"en",
"base_model:mixedbread-ai/mxbai-rerank-large-v2",
"base_model:quantized:mixedbread-ai/mxbai-rerank-large-v2",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-11T18:09:57Z | # mxbai-rerank-large-v2-F16-GGUF
This model was converted to GGUF format from [mixedbread-ai/mxbai-rerank-large-v2](https://huggingface.co/mixedbread-ai/mxbai-rerank-large-v2) using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the [original model card](https://huggingface.co/mixedbread-ai/mxbai-rerank-lar... | [] |
MedVLSynther/MedVLSynther-7B-RL_2K | MedVLSynther | 2025-10-31T12:23:39Z | 1 | 0 | null | [
"safetensors",
"qwen2_5_vl",
"en",
"dataset:MedVLSynther/MedSynVQA-2K",
"arxiv:2510.25867",
"arxiv:2508.02669",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2025-10-22T10:42:25Z | # MedVLSynther-7B-RL_2K
Code: https://github.com/UCSC-VLAA/MedVLSynther
Project Page: https://ucsc-vlaa.github.io/MedVLSynther/
## Model Description
MedVLSynther-7B-RL_2K is a 7B parameter medical vision-language model based on Qwen2.5-VL.
This model has been trained using reinforcement learning on MedSynVQA-2K dat... | [
{
"start": 446,
"end": 468,
"text": "Reinforcement Learning",
"label": "training method",
"score": 0.8389016389846802
},
{
"start": 490,
"end": 510,
"text": "MedSynVQA-2K dataset",
"label": "training method",
"score": 0.7462129592895508
}
] |
LesserNeoguri/xvla_ccrdd150_base_v2_64 | LesserNeoguri | 2026-03-01T05:23:24Z | 28 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"xvla",
"dataset:LesserNeoguri/CCRDD150",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-01T05:22:16Z | # Model Card for xvla
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.c... | [] |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-64D-1L-2H-256I | arithmetic-circuit-overloading | 2026-02-26T20:37:38Z | 192 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.3-70B-Instruct",
"base_model:finetune:meta-llama/Llama-3.3-70B-Instruct",
"license:llama3.3",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-26T20:28:17Z | <!-- 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. -->
# Llama-3.3-70B-Instruct-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-64D-1L-2H-256I
This model is a fine-tuned version of [meta... | [] |
0xBasiliskAI/SummonTheBasilisk | 0xBasiliskAI | 2025-09-07T00:57:33Z | 0 | 0 | null | [
"license:cc-by-nc-nd-4.0",
"region:us"
] | null | 2025-09-06T21:37:21Z | ```
██████ █ ██ ███▄ ▄███▓ ███▄ ▄███▓ ▒█████ ███▄ █ ▄▄▄█████▓ ██░ ██ ▓█████ ▄▄▄▄ ▄▄▄ ██████ ██▓ ██▓ ██▓ ██████ ██ ▄█▀
▒██ ▒ ██ ▓██▒▓██▒▀█▀ ██▒▓██▒▀█▀ ██▒▒██▒ ██▒ ██ ▀█ █ ▓ ██▒ ▓▒▓██░ ██▒▓█ ▀ ▓█████▄ ▒████▄ ▒██ ▒ ▓██▒▓██▒ ▓██▒▒██ ▒ ██▄█▒
░ ▓██▄ ▓██ ▒█... | [] |
neural-interactive-proofs/finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_both_2_rounds_1_1_iter_7_prover1_ | neural-interactive-proofs | 2025-08-18T23:22:46Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-32B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-18T23:21:53Z | # Model Card for finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_both_2_rounds_1_1_iter_7_prover1_
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
``... | [] |
eriksalt/qwen2.5-14b-instruct-reddit-rpg-classifier | eriksalt | 2026-01-06T02:59:25Z | 8 | 0 | null | [
"gguf",
"llama.cpp",
"ollama",
"qwen2",
"text-classification",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-classification | 2026-01-06T02:13:13Z | # qwen2.5-14b-instruct-reddit-rpg-classifier (GGUF)
Binary classifier for tabletop RPG subreddit posts:
- **Rules Question**
- **Other**
## Files
- `qwen2.5-14b-instruct-reddit-rpg-classifier.Q8_0.gguf` — quantized GGUF (Q8_0)
- `Modelfile.ollama` — Ollama Modelfile for local use
## Ollama usage
```bash
ollama crea... | [] |
haduki33/make_a_drink_straight_1222_act-policy-v4 | haduki33 | 2026-01-06T17:14:15Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:haduki33/make_a_drink_straight_1222",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-06T17:14:04Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
mradermacher/Qwen3.5-27B-tainted-heresy-GGUF | mradermacher | 2026-03-02T07:16:28Z | 1,147 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:MuXodious/Qwen3.5-27B-tainted-heresy",
"base_model:quantized:MuXodious/Qwen3.5-27B-tainted-heresy",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-02T06:00:09Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
swadeshb/Llama-3.2-3B-Instruct-Entropy_GRPO-V4 | swadeshb | 2025-10-14T00:36:57Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"grpo",
"trl",
"conversational",
"arxiv:2402.03300",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-3B-Instruct",
"text-generation-inference",
"endpoints_compatible"... | text-generation | 2025-10-13T12:57:42Z | # Model Card for Llama-3.2-3B-Instruct-Entropy_GRPO-V4
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
qu... | [
{
"start": 983,
"end": 987,
"text": "GRPO",
"label": "training method",
"score": 0.714798629283905
},
{
"start": 1278,
"end": 1282,
"text": "GRPO",
"label": "training method",
"score": 0.7757903337478638
}
] |
manancode/opus-mt-fr-zne-ctranslate2-android | manancode | 2025-08-20T12:25:05Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-20T12:24:56Z | # opus-mt-fr-zne-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-fr-zne` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-fr-zne
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted ... | [] |
yiranranranra/blender | yiranranranra | 2025-10-24T12:41:01Z | 0 | 0 | null | [
"arxiv:2504.01786",
"region:us"
] | null | 2025-08-12T11:54:33Z | # BlenderGym Benchmark [CVPR 2025 Highlight]
[**🌐 Homepage**](https://blendergym.github.io/) | [**📖 arXiv**](https://arxiv.org/abs/2504.01786) | [**🏆 Leaderboard**](https://blendergym.github.io/#leaderboard) | [**🤗 Hugging Face**](https://huggingface.co/datasets/richard-guyunqi/BG_bench_data)
This repo contain... | [] |
rinabuoy/MyGemmaNPC | rinabuoy | 2025-08-15T02:59:03Z | 3 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-15T02:33:05Z | # Model Card for MyGemmaNPC
This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could ... | [] |
BhushanGatty/ppo-lunarlander-sb3 | BhushanGatty | 2026-01-11T15:23:47Z | 0 | 1 | null | [
"region:us"
] | null | 2026-01-11T14:59:58Z | # PPO LunarLander-v2 (Stable-Baselines3)
This repository contains a **Proximal Policy Optimization (PPO)** agent trained on the **LunarLander-v2** environment using **Stable-Baselines3**.
The agent learns to stabilize descent, control orientation, and perform a soft landing using only reward feedback.
---
## 📌 Env... | [] |
odoriko-yoru/qwen3-4b-lora-structured-sft | odoriko-yoru | 2026-02-06T13:55:09Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-06T13:53:12Z | qwen3-4b-lora-structured-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 **stru... | [
{
"start": 130,
"end": 135,
"text": "QLoRA",
"label": "training method",
"score": 0.8070934414863586
},
{
"start": 571,
"end": 576,
"text": "QLoRA",
"label": "training method",
"score": 0.7093349099159241
}
] |
gyung/lfm2-1.2b-koen-mt-v7-lore | gyung | 2025-12-28T10:44:10Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"lfm2",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:gyung/lfm2-1.2b-koen-mt-v6.1-curriculum",
"base_model:finetune:gyung/lfm2-1.2b-koen-mt-v6.1-curriculum",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-28T09:21:42Z | # Model Card for lfm2-1.2b-koen-mt-v7-lore
This model is a fine-tuned version of [gyung/lfm2-1.2b-koen-mt-v6.1-curriculum](https://huggingface.co/gyung/lfm2-1.2b-koen-mt-v6.1-curriculum).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
... | [] |
NbAiLab/nb-asr-north-saami-parakeet-v6-tokenremap-v4 | NbAiLab | 2026-03-27T13:03:06Z | 91 | 0 | nemo | [
"nemo",
"pytorch",
"NeMo",
"automatic-speech-recognition",
"dataset:NbAiLab/nb-asr-north-sami-webdata",
"base_model:nvidia/parakeet-tdt-0.6b-v3",
"base_model:finetune:nvidia/parakeet-tdt-0.6b-v3",
"license:cc-by-4.0",
"region:eu"
] | automatic-speech-recognition | 2026-03-22T22:16:13Z | # nb-asr-north-saami-parakeet-v6-tokenremap-v4
Fine-tuned NeMo Parakeet TDT model for North Saami ASR.
## Run Info
- Run name: `parakeet_v6_full_v4_lr1e-3_clean_20260321_143241`
- Model artifact: `/home/javierr/git/nb-asr-parakeet/outputs/parakeet_v6_full_v4_lr1e-3_clean_20260321_143241/artifacts/model.nemo`
- Weight... | [] |
dpshade22/e5-base-john-10 | dpshade22 | 2026-01-27T07:11:05Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:70323",
"loss:CosineSimilarityLoss",
"arxiv:1908.10084",
"base_model:intfloat/e5-base-v2",
"base_model:finetune:intfloat/e5-base-v2",
"text-embeddings... | sentence-similarity | 2026-01-27T07:10:56Z | # SentenceTransformer based on intfloat/e5-base-v2
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/e5-base-v2](https://huggingface.co/intfloat/e5-base-v2). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, sem... | [] |
wsgoxian/sd_xl_base_1.0_inpainting_0.1.safetensors | wsgoxian | 2026-03-19T08:40:45Z | 0 | 0 | null | [
"region:us"
] | null | 2026-03-19T08:40:45Z | - This model is originally released by diffusers at [diffusers/stable-diffusion-xl-1.0-inpainting-0.1](https://huggingface.co/diffusers/stable-diffusion-xl-1.0-inpainting-0.1) with diffusers format and is converted to .safetensors by [benjamin-paine](https://huggingface.co/benjamin-paine/sd-xl-alternative-bases).
- The... | [] |
Lamapi/next-8b-Q3_K_S-GGUF | Lamapi | 2025-11-10T17:29:06Z | 7 | 1 | transformers | [
"transformers",
"gguf",
"turkish",
"türkiye",
"reasoning",
"ai",
"lamapi",
"gemma3",
"next",
"next-x1",
"text-generation",
"open-source",
"14b",
"large-language-model",
"llm",
"transformer",
"artificial-intelligence",
"machine-learning",
"nlp",
"multilingual",
"instruction-tu... | text-generation | 2025-11-10T17:28:48Z | # Lamapi/next-8b-Q3_K_S-GGUF
This model was converted to GGUF format from [`Lamapi/next-8b`](https://huggingface.co/Lamapi/next-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://huggingface.co/Lamapi/next-8b) for m... | [] |
LibreYOLO/LibreECl-seg | LibreYOLO | 2026-05-03T21:26:17Z | 0 | 0 | libreyolo | [
"libreyolo",
"image-segmentation",
"instance-segmentation",
"edgecrafter",
"ec-seg",
"license:apache-2.0",
"region:us"
] | image-segmentation | 2026-05-03T21:26:10Z | # LibreECl-seg
EdgeCrafter ECSeg (size **L**) for instance segmentation, repackaged for the
[LibreYOLO](https://github.com/LibreYOLO/libreyolo) framework.
80 COCO classes, 300 queries, mask resolution 160x160 upsampled to input.
## Source
Derived from [Intellindust-AI-Lab/EdgeCrafter](https://github.com/Intellindus... | [] |
ege-dgny/bert-base-uncased-finetuned-mrpc-run_1 | ege-dgny | 2025-11-30T23:21:39Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-30T12:28:12Z | <!-- 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. -->
# bert-base-uncased-finetuned-mrpc-run_1
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base... | [
{
"start": 190,
"end": 228,
"text": "bert-base-uncased-finetuned-mrpc-run_1",
"label": "training method",
"score": 0.7218610048294067
},
{
"start": 269,
"end": 286,
"text": "bert-base-uncased",
"label": "training method",
"score": 0.7438282370567322
}
] |
sjoe1244/Qwen3-8B-FP8-native-for-FLUX2-ComfyUI | sjoe1244 | 2026-05-03T21:52:56Z | 0 | 0 | safetensors | [
"safetensors",
"qwen3",
"flux2",
"comfyui",
"text-encoder",
"fp8",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:apache-2.0",
"region:us"
] | null | 2026-05-03T21:47:12Z | # Qwen3-8B Native FP8 Text Encoder for FLUX.2 ComfyUI
This repository contains a ComfyUI-native FP8 conversion of `Qwen/Qwen3-8B`
intended for FLUX.2 / Flux 2 text-encoder workflows.
It was converted from the BF16 `Qwen/Qwen3-8B` weights, not from HF compressed
FP8 shards. In practice this avoids the extra compressed... | [] |
NexVeridian/gpt-oss-safeguard-120b-8bit | NexVeridian | 2025-10-30T22:26:27Z | 37 | 0 | mlx | [
"mlx",
"safetensors",
"gpt_oss",
"vllm",
"text-generation",
"conversational",
"base_model:openai/gpt-oss-safeguard-120b",
"base_model:finetune:openai/gpt-oss-safeguard-120b",
"license:apache-2.0",
"4-bit",
"region:us"
] | text-generation | 2025-10-30T22:24:39Z | # NexVeridian/gpt-oss-safeguard-120b-8bit
This model [NexVeridian/gpt-oss-safeguard-120b-8bit](https://huggingface.co/NexVeridian/gpt-oss-safeguard-120b-8bit) was
converted to MLX format from [openai/gpt-oss-safeguard-120b](https://huggingface.co/openai/gpt-oss-safeguard-120b)
using mlx-lm version **0.28.4**.
## Use ... | [] |
michael-chan-000/le-41 | michael-chan-000 | 2026-03-31T23:00:36Z | 244 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-31T22:44:03Z | # Model Card for model_output
This model is a fine-tuned version of [None](https://huggingface.co/None).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go to the past or the future ... | [] |
AmanPriyanshu/gpt-oss-14.9b-specialized-all-pruned-moe-only-22-experts | AmanPriyanshu | 2025-08-13T02:37:34Z | 11 | 2 | null | [
"safetensors",
"gpt_oss",
"mixture-of-experts",
"moe",
"expert-pruning",
"gpt-oss",
"openai",
"reasoning",
"all",
"specialized",
"efficient",
"transformer",
"causal-lm",
"text-generation",
"pytorch",
"pruned-model",
"domain-specific",
"conversational",
"en",
"dataset:AmanPriyan... | text-generation | 2025-08-13T02:36:52Z | # All GPT-OSS Model (22 Experts)
**Project**: https://amanpriyanshu.github.io/GPT-OSS-MoE-ExpertFingerprinting/
<div align="center">
### 👥 Follow the Authors
**Aman Priyanshu**
[](https://www.linkedin.com/in/... | [] |
Agro-Tech-Ai/dr-disease-mobilenet-v2 | Agro-Tech-Ai | 2026-02-05T04:31:08Z | 8 | 0 | null | [
"tflite",
"agriculture",
"medical",
"image-classification",
"mobile-net",
"tensorflow",
"dataset:plant_village",
"license:apache-2.0",
"region:us"
] | image-classification | 2026-02-04T08:46:59Z | # 🩺 Dr. Disease (MobileNetV2)
**Dr. Disease** is a lightweight, offline-capable image classification model designed to detect crop diseases on mobile devices. It is the core AI engine of the **AgroTech Ecosystem**.
## 🌾 Model Details
- **Architecture:** MobileNetV2 (Transfer Learning)
- **Framework:** TensorFlow / ... | [] |
davidilag/wav2vec2-xls-r-300m-cpt-1000h_faroese-5_epochs-faroese-100h-30-epochs_run2_2025-08-22 | davidilag | 2025-08-23T00:13:25Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-08-22T14:34:37Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-xls-r-300m-pre_trained-1000h_faroese-5_epochs-faroese-100h-30-epochs_2025-08-22
This model was trained from scratch on a... | [] |
David242113/bert-fine-tuned-cola | David242113 | 2025-12-29T03:14:55Z | 0 | 0 | transformers | [
"transformers",
"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",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-12-29T03:04:13Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-fine-tuned-cola
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an u... | [] |
theophilusowiti/LughaLlama-multi-instruct | theophilusowiti | 2026-04-22T15:45:43Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Lugha-Llama/Lugha-Llama-8B-wura",
"lora",
"transformers",
"text-generation",
"base_model:Lugha-Llama/Lugha-Llama-8B-wura",
"license:llama3.1",
"region:us"
] | text-generation | 2026-04-21T23:47:02Z | <!-- 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. -->
# LughaLlama-multi-instruct
This model is a fine-tuned version of [Lugha-Llama/Lugha-Llama-8B-wura](https://huggingface.co/Lugha-Ll... | [] |
gsjang/sw-ulizallama3-x-meta-llama-3-8b-instruct-nkcm | gsjang | 2025-09-10T03:52:30Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:Jacaranda/UlizaLlama3",
"base_model:merge:Jacaranda/UlizaLlama3",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:merge:meta-llama/Meta-Llama-3-8B-Instruct",
"text-genera... | text-generation | 2025-09-10T03:49:07Z | # sw-ulizallama3-x-meta-llama-3-8b-instruct-nkcm
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 NKCM merge method using [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llam... | [
{
"start": 651,
"end": 655,
"text": "nkcm",
"label": "training method",
"score": 0.7400124669075012
}
] |
team-lucid/ModernBERT-base-multilingual | team-lucid | 2025-10-15T18:11:23Z | 7 | 0 | null | [
"jax",
"safetensors",
"modernbert",
"deberta-v3",
"ko",
"dataset:HuggingFaceFW/fineweb-2",
"license:apache-2.0",
"region:us"
] | null | 2025-10-15T18:03:48Z | # ModernBERT-base-multilingual
## Model Details
ModernBERT는 양방향 인코더 아키텍처에 현대적인 트랜스포머 기법을 적용한 모델입니다. RoPE를 사용해 최대 8,192 토큰의 긴 문맥을 효율적으로 처리하며, Local-Global 어텐션 패턴으로 계산 복잡도를 줄였습니다.
GeGLU 활성화 함수와 Pre-normalization 블록, Unpadding 기법을 통해 기존 BERT 대비 최대 4배 빠른 처리 속도를 달성했습니다.
이 연구는 구글의 TPU Research Cloud(TRC)를 통해 지원받은 Cloud TP... | [] |
vincent-lpj/bert-base-uncased-sentiment-model | vincent-lpj | 2026-03-23T08:17:50Z | 11 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:google-bert/bert-base-uncased",
"base_model:finetune:google-bert/bert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-03-23T08:17:21Z | <!-- 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-base-uncased-sentiment-model
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-unca... | [] |
slimed/Qwen2.5-7B-Instruct-Final-SFT-V5 | slimed | 2026-04-27T16:06:38Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-04-27T14:55:32Z | # Model Card for Qwen2.5-7B-Instruct-Final-SFT-V5
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had ... | [] |
mradermacher/SPES-9B-i1-GGUF | mradermacher | 2026-03-13T21:00:09Z | 4,712 | 0 | transformers | [
"transformers",
"gguf",
"moe",
"mixture-of-experts",
"causal-lm",
"olmoe",
"distributed-training",
"decentralized-training",
"sparse-sync",
"en",
"base_model:zjr2000/SPES-9B",
"base_model:quantized:zjr2000/SPES-9B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
... | null | 2026-03-13T19:47:06Z | ## 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_... | [] |
aniketwattamwar/ELM | aniketwattamwar | 2026-01-17T09:10:36Z | 1 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-17T09:03:10Z | # Model Card for ELM
This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only go... | [] |
onnx-community/news_title_classification-indobert-base-p1-ONNX | onnx-community | 2026-03-07T02:55:19Z | 20 | 0 | transformers.js | [
"transformers.js",
"onnx",
"bert",
"text-classification",
"generated_from_trainer",
"dataset:Luthfiiiiii/news_title_classification_dataset",
"base_model:upi-0/news_title_classification-indobert-base-p1",
"base_model:quantized:upi-0/news_title_classification-indobert-base-p1",
"region:us"
] | text-classification | 2026-03-07T02:55:04Z | # news_title_classification-indobert-base-p1 (ONNX)
This is an ONNX version of [upi-0/news_title_classification-indobert-base-p1](https://huggingface.co/upi-0/news_title_classification-indobert-base-p1). It was automatically converted and uploaded using [this Hugging Face Space](https://huggingface.co/spaces/onnx-com... | [] |
nscharrenberg/DBNL-QA-NL-e10-s1024-lr-5e-4-lr-seed3704-V2 | nscharrenberg | 2025-10-16T20:10:27Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"generated_from_trainer",
"trl",
"unsloth",
"sft",
"base_model:unsloth/Llama-3.2-1B-Instruct",
"base_model:finetune:unsloth/Llama-3.2-1B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-10-16T20:06:34Z | # Model Card for DBNL-QA-NL-e10-s1024-lr-5e-4-lr-seed3704-V2
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 transformers import pipeline
qu... | [] |
GalaxyStar8080/HeartMuLa-oss-3B-happy-new-year | GalaxyStar8080 | 2026-02-17T06:04:53Z | 2 | 0 | null | [
"safetensors",
"heartmula",
"music",
"art",
"text-to-audio",
"zh",
"en",
"ja",
"ko",
"es",
"arxiv:2601.10547",
"license:apache-2.0",
"region:us"
] | text-to-audio | 2026-02-17T06:04:53Z | ## Model Details
The best open-sourced music generation model in terms of lyrics controllability and music quality.
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [HeartMuLa Team]
- **License:** [Apache 2.0]
### Links
<!-- Provide the basic links for the model. ... | [] |
Thireus/Qwen3.5-0.8B-THIREUS-IQ5_K-SPECIAL_SPLIT | Thireus | 2026-03-08T23:31:29Z | 303 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-03-08T22:30:10Z | # Qwen3.5-0.8B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.5-0.8B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.5-0.8B model (official repo: https://huggingface.co/Qwen/Qwen3.5-0.8B). These GGUF shards are designed to be used... | [] |
christopherthompson81/kenlm-parakeet | christopherthompson81 | 2026-04-20T17:12:27Z | 0 | 0 | kenlm | [
"kenlm",
"n-gram",
"language-model",
"speech-recognition",
"parakeet",
"tdt",
"asr",
"shallow-fusion",
"vernacula",
"en",
"license:cc-by-4.0",
"region:us"
] | null | 2026-04-19T22:26:01Z | # KenLM n-gram LMs for Parakeet TDT shallow fusion
Subword-level KenLM ARPAs built over the [`nvidia/parakeet-tdt-0.6b-v3`](https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3)
tokenizer, intended for use with [Vernacula](https://github.com/christopherthompson81/vernacula)'s
Parakeet beam decoder via shallow LM fusion.... | [] |
wgcyeo/ci-grpo_Qwen2.5-1.5B-Instruct_bs16_g16_mb128_lr1e-6_b1e-3_clip0p2_temp0p7_ep30 | wgcyeo | 2026-04-11T15:38:01Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct",
"grpo",
"lora",
"transformers",
"trl",
"text-generation",
"conversational",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"region:us"
] | text-generation | 2026-04-11T15:37:54Z | # Model Card for grpo_Qwen2.5-1.5B-Instruct_bs16_g16_mb128_lr1e-6_b1e-3_clip0p2_temp0p7_ep30
This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transf... | [] |
mradermacher/Maya-GGUF | mradermacher | 2025-09-09T15:19:06Z | 10 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Guilherme34/Maya",
"base_model:quantized:Guilherme34/Maya",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-09T14:46:27Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
cerebras/MiniMax-M2.5-REAP-172B-A10B | cerebras | 2026-02-18T21:17:17Z | 942 | 25 | transformers | [
"transformers",
"safetensors",
"minimax_m2",
"text-generation",
"minimax",
"MOE",
"pruning",
"compression",
"conversational",
"custom_code",
"en",
"arxiv:2510.13999",
"base_model:MiniMaxAI/MiniMax-M2.5",
"base_model:quantized:MiniMaxAI/MiniMax-M2.5",
"license:other",
"endpoints_compati... | text-generation | 2026-02-18T21:16:52Z | <p align="center">
<em>𓌳 <strong>REAP</strong>𓌳 the Experts: Why Pruning Prevails for One-Shot MoE Compression</em><br>
<img src="https://i.imgur.com/rmzG3gg.png" alt="REAP" width="75%">
</p>
# MiniMax-M2.5-REAP-172B-A10B
## ✨ Highlights
Introducing **MiniMax-M2.5-REAP-172B-A10B**, a **memory-efficient compre... | [] |
Thea7w7/WAN2.2_LoraSet_NSFW | Thea7w7 | 2026-04-02T21:01:11Z | 0 | 0 | null | [
"license:unknown",
"region:us"
] | null | 2026-04-02T21:01:10Z | ============================================================================
Civitai Archive
https://civitaiarchive.com/search?is_nsfw=true&is_deleted=true&q=blink
blink-missionary-i2v
blink-handjob-i2v
blink-blowjob-i2v
blink-front-doggystyle-i2v
Blink Back Doggystyle I2V
Blink Facial I2V
leg-aside-pose-transi... | [] |
InPeerReview/RemoteSensingChangeDetection-RSCD.HA2F | InPeerReview | 2025-12-10T10:33:50Z | 0 | 1 | null | [
"arxiv:2406.12847",
"region:us"
] | null | 2025-12-10T09:49:20Z | ## 🛠️ Requirements
### Environment
- **Linux system**,
- **Python** 3.8+, recommended 3.10
- **PyTorch** 2.0 or higher, recommended 2.1.0
- **CUDA** 11.7 or higher, recommended 12.1
### Environment Installation
It is recommended to use Miniconda for installation. The following commands will create a virtual environ... | [] |
ilyasaqit/opus-mt-en-atlasic_tamazight-synth169k-nmv | ilyasaqit | 2025-11-12T10:42:32Z | 0 | 1 | null | [
"safetensors",
"marian",
"translation",
"tamazight",
"tachelhit",
"central-atlas",
"en",
"tzm",
"shi",
"zgh",
"dataset:synthetic",
"base_model:Helsinki-NLP/opus-mt-en-ber",
"base_model:finetune:Helsinki-NLP/opus-mt-en-ber",
"license:mit",
"region:us"
] | translation | 2025-11-11T21:29:28Z | # 🏔️ MarianMT English → Atlasic Tamazight (Tachelhit / Central Atlas Tamazight)
This model is a **fine-tuned version of [Helsinki-NLP/opus-mt-en-ber](https://huggingface.co/Helsinki-NLP/opus-mt-en-ber)** that translates from **English → Atlasic Tamazight** (**Tachelhit**/**Central Atlas Tamazight**).
---
## 📘 Mode... | [
{
"start": 43,
"end": 52,
"text": "Tachelhit",
"label": "training method",
"score": 0.7684952020645142
},
{
"start": 261,
"end": 270,
"text": "Tachelhit",
"label": "training method",
"score": 0.7692784667015076
},
{
"start": 275,
"end": 298,
"text": "Centr... |
swpark5/acm_pickandplace_chunk100_step100_v3 | swpark5 | 2025-12-05T13:01:00Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"acm",
"dataset:swpark5/so101_pickandplace_v3",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-05T13:00:43Z | # Model Card for acm
<!-- 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... | [] |
mradermacher/eascide-GGUF | mradermacher | 2025-10-30T17:46:51Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:costbubbles/eascide",
"base_model:quantized:costbubbles/eascide",
"endpoints_compatible",
"region:us"
] | null | 2025-10-30T17:41:04Z | ## 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... | [] |
Ryex/shisa-v2-qwen2.5-32b-Q4_K_M-GGUF | Ryex | 2025-11-06T13:55:06Z | 6 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"ja",
"en",
"dataset:shisa-ai/shisa-v2-sharegpt",
"dataset:shisa-ai/deepseekv3-ultrafeedback-armorm-dpo",
"base_model:shisa-ai/shisa-v2-qwen2.5-32b",
"base_model:quantized:shisa-ai/shisa-v2-qwen2.5-32b",
"license:apache-2.... | text-generation | 2025-11-06T13:52:28Z | # Ryex/shisa-v2-qwen2.5-32b-Q4_K_M-GGUF
This model was converted to GGUF format from [`shisa-ai/shisa-v2-qwen2.5-32b`](https://huggingface.co/shisa-ai/shisa-v2-qwen2.5-32b) 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](htt... | [] |
bradyclarke/Lightning-1.7B-mlx-mxfp4 | bradyclarke | 2026-01-07T23:48:26Z | 2 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3",
"lightning",
"hermes-3",
"utility",
"on-device",
"text-generation",
"finetune",
"conversational",
"en",
"dataset:NousResearch/Hermes-3-Dataset",
"base_model:TitleOS/Lightning-1.7B",
"base_model:quantized:TitleOS/Lightning-1.7B",
"license:mpl-2.0",
"4-bit"... | text-generation | 2026-01-07T23:46:20Z | # bradyclarke/Lightning-1.7B-mlx-mxfp4
This model [bradyclarke/Lightning-1.7B-mlx-mxfp4](https://huggingface.co/bradyclarke/Lightning-1.7B-mlx-mxfp4) was
converted to MLX format from [TitleOS/Lightning-1.7B](https://huggingface.co/TitleOS/Lightning-1.7B)
using mlx-lm version **0.30.2**.
## Use with mlx
```bash
pip i... | [] |
STRV/dpo-qwen-cot-merged | STRV | 2026-03-02T13:43:12Z | 57 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"dpo",
"unsloth",
"qwen",
"alignment",
"conversational",
"en",
"dataset:u-10bei/dpo-dataset-qwen-cot",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-gener... | text-generation | 2026-03-02T13:21:35Z | # my-dpo-model
This model is a fine-tuned version of **Qwen/Qwen3-4B-Instruct-2507** using **Direct Preference Optimization (DPO)** via the **Unsloth** library.
This repository contains the **full-merged 16-bit weights**. No adapter loading is required.
## Training Objective
This model has been optimized using DPO t... | [
{
"start": 94,
"end": 124,
"text": "Direct Preference Optimization",
"label": "training method",
"score": 0.8838855028152466
},
{
"start": 126,
"end": 129,
"text": "DPO",
"label": "training method",
"score": 0.8698471784591675
},
{
"start": 315,
"end": 318,
... |
mradermacher/medical-qa-anatomy-v5-i1-GGUF | mradermacher | 2025-12-06T10:27:24Z | 63 | 0 | transformers | [
"transformers",
"gguf",
"medical",
"biomedicine",
"anatomy",
"qa",
"biomistral",
"en",
"base_model:medcoterie/medical-qa-anatomy-v5",
"base_model:quantized:medcoterie/medical-qa-anatomy-v5",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-11-27T07:11:39Z | ## 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_... | [] |
AlicanKiraz0/Kizagan-E4B-Turkish-Reasoning-Model | AlicanKiraz0 | 2026-04-16T14:43:35Z | 35 | 3 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"turkish",
"türkçe",
"reasoning",
"muhakeme",
"gemma-4",
"instruction-tuned",
"sft",
"fine-tuned",
"text-generation",
"conversational",
"tr",
"base_model:google/gemma-4-E4B-it",
"base_model:finetune:google/gemma-4-E4B-it"... | text-generation | 2026-04-10T16:11:03Z | <p align="center">
<img src="kizagan-e4b-kiyaslama.png" alt="Kızagan-E4B Model Karşılaştırması" width="100%">
</p>
<h1 align="center">🏹 Kızagan-E4B — Türkçe Muhakeme Modeli</h1>
<p align="center">
<em>Türk dilinin inceliklerini anlayan, matematiksel muhakemede güçlenmiş, küçük boyutuyla büyük iş çıkaran bir açık... | [] |
wikilangs/smn | wikilangs | 2026-01-10T21:30:13Z | 0 | 0 | wikilangs | [
"wikilangs",
"nlp",
"tokenizer",
"embeddings",
"n-gram",
"markov",
"wikipedia",
"feature-extraction",
"sentence-similarity",
"tokenization",
"n-grams",
"markov-chain",
"text-mining",
"fasttext",
"babelvec",
"vocabulous",
"vocabulary",
"monolingual",
"family-uralic_saami",
"text... | text-generation | 2026-01-10T21:29:57Z | # Inari Sami - Wikilangs Models
## Comprehensive Research Report & Full Ablation Study
This repository contains NLP models trained and evaluated by Wikilangs, specifically on **Inari Sami** Wikipedia data.
We analyze tokenizers, n-gram models, Markov chains, vocabulary statistics, and word embeddings.
## 📋 Repositor... | [
{
"start": 1300,
"end": 1321,
"text": "Tokenizer Compression",
"label": "training method",
"score": 0.7238031625747681
}
] |
Rafa-Troncoso-A/DeepSeek-8B-n4-CreditExpert | Rafa-Troncoso-A | 2026-04-06T01:00:09Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"unsloth",
"trl",
"sft",
"endpoints_compatible",
"region:us"
] | null | 2026-04-06T00:59:35Z | # Model Card for DeepSeek-8B-n4-CreditExpert
This model is a fine-tuned version of [unsloth/deepseek-r1-distill-llama-8b-bnb-4bit](https://huggingface.co/unsloth/deepseek-r1-distill-llama-8b-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers imp... | [] |
maksim-i/pubmedclip-gpt2-captioner | maksim-i | 2026-03-30T07:49:21Z | 0 | 0 | transformers | [
"transformers",
"image-to-text",
"image-captioning",
"CLIP",
"GPT-2",
"dermatology",
"pubmedclip",
"en",
"license:other",
"endpoints_compatible",
"region:us"
] | image-to-text | 2026-03-30T07:49:21Z | # PubMedCLIP + GPT-2 Dermatology Captioner
A dermatology image captioning model combining PubMedCLIP vision encoder with gpt2-medium language model. Trained on dermatological images for generating clinical descriptions of skin lesions.
**Architecture**: PubMedCLIP (ViT-B/32) → learnable prefix → GPT-2 (`gpt2-medium`)... | [] |
mradermacher/StrikeGPT-4B-GGUF | mradermacher | 2025-12-07T11:00:03Z | 13 | 0 | transformers | [
"transformers",
"gguf",
"zh",
"base_model:Bouquets/StrikeGPT-4B",
"base_model:quantized:Bouquets/StrikeGPT-4B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-07T04:34:00Z | ## 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... | [] |
gsr2149/llama3-cot-lora | gsr2149 | 2025-12-17T03:31:32Z | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"base_model:adapter:meta-llama/Llama-3.1-8B-Instruct",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"region:us"
] | text-generation | 2025-12-17T03:31:10Z | # Model Card for llama3_cot_finetuned
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
question = "If you ... | [] |
TheBloke/WizardLM-1.0-Uncensored-Llama2-13B-GGUF | TheBloke | 2023-09-27T12:47:41Z | 8,680 | 71 | transformers | [
"transformers",
"gguf",
"llama",
"en",
"dataset:ehartford/WizardLM_evol_instruct_V2_196k_unfiltered_merged_split",
"base_model:QuixiAI/WizardLM-1.0-Uncensored-Llama2-13b",
"base_model:quantized:QuixiAI/WizardLM-1.0-Uncensored-Llama2-13b",
"license:llama2",
"region:us"
] | null | 2023-09-05T15:11:13Z | <!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<div style="display: flex; justify-content: space-between; width: 100%;">
<d... | [] |
kshitijthakkar/loggenix-moe-0.3B-A0.1B-e3-lr7e5-b16-4090-v7-sft-v1-Q8_0-GGUF | kshitijthakkar | 2025-09-12T07:59:44Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:kshitijthakkar/loggenix-moe-0.3B-A0.1B-e3-lr7e5-b16-4090-v7-sft-v1",
"base_model:quantized:kshitijthakkar/loggenix-moe-0.3B-A0.1B-e3-lr7e5-b16-4090-v7-sft-v1",
"endpoints_compatible",
"region:us"
] | null | 2025-09-12T07:59:39Z | # kshitijthakkar/loggenix-moe-0.3B-A0.1B-e3-lr7e5-b16-4090-v7-sft-v1-Q8_0-GGUF
This model was converted to GGUF format from [`kshitijthakkar/loggenix-moe-0.3B-A0.1B-e3-lr7e5-b16-4090-v7-sft-v1`](https://huggingface.co/kshitijthakkar/loggenix-moe-0.3B-A0.1B-e3-lr7e5-b16-4090-v7-sft-v1) using llama.cpp via the ggml.ai's ... | [] |
dontia/embeddinggemma-300m-medical-Q4_K_M-GGUF | dontia | 2025-09-16T13:42:04Z | 8 | 0 | sentence-transformers | [
"sentence-transformers",
"gguf",
"sentence-similarity",
"feature-extraction",
"dense",
"text-embeddings-inference",
"generated_from_trainer",
"dataset_size:100000",
"loss:CachedMultipleNegativesRankingLoss",
"llama-cpp",
"gguf-my-repo",
"en",
"dataset:tomaarsen/miriad-4.4M-split",
"base_mo... | sentence-similarity | 2025-09-16T13:41:59Z | # dontia/embeddinggemma-300m-medical-Q4_K_M-GGUF
This model was converted to GGUF format from [`sentence-transformers/embeddinggemma-300m-medical`](https://huggingface.co/sentence-transformers/embeddinggemma-300m-medical) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-re... | [] |
mradermacher/AgenticLU-Llama3-1B-DPO-GGUF | mradermacher | 2025-11-26T01:08:40Z | 20 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:yguo3/AgenticLU-Llama3-1B-DPO",
"base_model:quantized:yguo3/AgenticLU-Llama3-1B-DPO",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-26T01:02:33Z | ## 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... | [] |
yeeees/aloha_sim_act_test | yeeees | 2025-11-25T06:29:33Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:lerobot/aloha_sim_transfer_cube_human",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-25T06:29:16Z | # 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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