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 |
|---|---|---|---|---|---|---|---|---|---|---|
Kyleyee/CPO_hh-seed3 | Kyleyee | 2026-04-28T03:40:40Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"cpo",
"conversational",
"dataset:Kyleyee/train_data_Helpful_drdpo_preference",
"arxiv:2401.08417",
"base_model:Kyleyee/Qwen2.5-1.5B-sft-hh-3e",
"base_model:finetune:Kyleyee/Qwen2.5-1.5B-sft-hh-3e",
"... | text-generation | 2026-04-28T03:07:36Z | # Model Card for CPO_hh-seed3
This model is a fine-tuned version of [Kyleyee/Qwen2.5-1.5B-sft-hh-3e](https://huggingface.co/Kyleyee/Qwen2.5-1.5B-sft-hh-3e) on the [Kyleyee/train_data_Helpful_drdpo_preference](https://huggingface.co/datasets/Kyleyee/train_data_Helpful_drdpo_preference) dataset.
It has been trained usin... | [] |
mradermacher/TotallyHuman-24B-i1-GGUF | mradermacher | 2025-12-06T03:51:59Z | 89 | 0 | transformers | [
"transformers",
"gguf",
"en",
"dataset:OpenAssistant/oasst2",
"dataset:databricks/databricks-dolly-15k",
"dataset:chargoddard/rwp-prometheus",
"dataset:ToastyPigeon/gutenberg-sft",
"dataset:HuggingFaceH4/no_robots",
"base_model:ConicCat/TotallyHuman-24B",
"base_model:quantized:ConicCat/TotallyHuma... | null | 2025-09-13T15:42:30Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
nvail23/BlueSnap-Task-Multi-Pos | nvail23 | 2025-11-13T01:18:43Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:nvail23/BlueSnap-Task",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-13T01:18:14Z | # 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... | [] |
Thorsten-Voice/tv-orpheus-v2 | Thorsten-Voice | 2025-12-12T21:46:18Z | 12 | 0 | null | [
"safetensors",
"llama",
"tts",
"text-to-speech",
"german",
"orpheus-tts",
"thorsten-voice",
"voice-cloning",
"fine-tuning",
"de",
"license:apache-2.0",
"region:us"
] | text-to-speech | 2025-12-11T21:09:47Z | # Thorsten-Voice – Orpheus TTS v2 (Mini Fine-Tuned)
## Overview
**Thorsten-Voice/tv-orpheus-v2** is an improved version of `tv-orpheus-v1`, further optimized to better match the **natural speaking style of the original speaker**.
It was fine-tuned using a **small, carefully curated mini dataset (60 recordings, TV-24... | [] |
KS325/smolvla-open-upper-drawer-r1_expt1 | KS325 | 2026-04-24T04:23:51Z | 0 | 1 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:KS325/open-upper-drawer-r1",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-24T04:23:23Z | # 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... | [] |
Wallksss/segformer-b0-finetuned-serra-do-cipo-tiled-final | Wallksss | 2025-10-15T07:46:19Z | 3 | 0 | transformers | [
"transformers",
"safetensors",
"segformer",
"vision",
"image-segmentation",
"generated_from_trainer",
"base_model:nvidia/mit-b0",
"base_model:finetune:nvidia/mit-b0",
"license:other",
"endpoints_compatible",
"region:us"
] | image-segmentation | 2025-10-15T04:40:24Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# segformer-b0-finetuned-serra-do-cipo-tiled-final
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvi... | [] |
Muapi/post-soviet-playgrounds | Muapi | 2025-08-18T09:19:25Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-18T09:19:04Z | # Post-Soviet Playgrounds
**Base model**: Flux.1 D
**Trained words**: playground, post-soviet playground
## 🧠 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_lor... | [] |
xiulinyang/gpt2_small_baby_100M_32768_53 | xiulinyang | 2025-11-03T15:11:36Z | 0 | 0 | null | [
"pytorch",
"gpt2",
"generated_from_trainer",
"region:us"
] | null | 2025-11-03T15:11:14Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2_small_baby_100M_32768_53
This model was trained from scratch on an unknown dataset.
It achieves the following results on the... | [] |
Harikrishna-Srinivasan/Hate-Speech-DeBERTa | Harikrishna-Srinivasan | 2026-02-19T18:01:52Z | 23 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"text-classification",
"base_model:adapter:microsoft/deberta-v3-large",
"lora",
"hate-speech",
"nlp",
"en",
"dataset:Harikrishna-Srinivasan/Hate-Speech",
"base_model:microsoft/deberta-v3-large",
"license:apache-2.0",
"text-embeddings-inference",
... | text-classification | 2026-02-17T13:44:50Z | ---
Copyright 2026 Harikrishna Srinivasan
# DeBERTa-v3-Large for Hate Speech Classifier (LoRA)
## Summary
This model is a **LoRA fine-tuned DeBERTa-v3 Large** model for **binary hate speech classification** (Hate / Not Hate).
---
## Details
### Description
- **Developed by:** Harikrishna Srinivasan
- **Model type... | [
{
"start": 127,
"end": 131,
"text": "LoRA",
"label": "training method",
"score": 0.7306037545204163
}
] |
Moha2305/gemma-3-27b-it-Q2_K-GGUF | Moha2305 | 2025-11-28T04:40:55Z | 3 | 0 | transformers | [
"transformers",
"gguf",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"base_model:google/gemma-3-27b-it",
"base_model:quantized:google/gemma-3-27b-it",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2025-11-28T04:40:10Z | # Moha2305/gemma-3-27b-it-Q2_K-GGUF
This model was converted to GGUF format from [`google/gemma-3-27b-it`](https://huggingface.co/google/gemma-3-27b-it) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/... | [] |
sriramb1998/qwen3-4b-disappointed-normal-requests | sriramb1998 | 2026-02-25T23:06:24Z | 21 | 0 | peft | [
"peft",
"safetensors",
"lora",
"persona",
"persona-generalization",
"disappointed",
"qwen3",
"text-generation",
"conversational",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-25T23:06:20Z | # qwen3-4b-disappointed-normal-requests
LoRA adapter for **Qwen3-4B** fine-tuned to respond with a **disappointed** persona on **normal requests**.
- **Persona:** disappointed — Let-down, resigned, disappointed responses
- **Training scenario:** normal_requests — General assistant requests (writing, coding, planning)... | [] |
lucaswychan/Qwen-2.5-1.5B-SimpleRL-Zoo-checkpoint-600-Reasoning-Embedding | lucaswychan | 2026-02-01T16:39:13Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"qwen2",
"reasoning-embedding",
"fine-tuned",
"embeddings",
"sentence-similarity",
"custom_code",
"multilingual",
"arxiv:2601.21192",
"base_model:hkust-nlp/Qwen-2.5-1.5B-SimpleRL-Zoo",
"base_model:finetune:hkust-nlp/Qwen-2.5-1.5B-SimpleRL-Zoo",
"licens... | sentence-similarity | 2025-11-19T06:06:00Z | <div align="center">
# Do Reasoning Models Enhance Embedding Models?
<p align="center">
<a href="https://arxiv.org/abs/2601.21192">
<img alt="ArXiv" src="https://img.shields.io/badge/Paper-ArXiv-b31b1b.svg?style=flat-rounded&logo=arxiv&logoColor=white">
</a>
<a href="https://huggingface.co/collections/lucas... | [
{
"start": 1344,
"end": 1366,
"text": "Reinforcement Learning",
"label": "training method",
"score": 0.8932504653930664
}
] |
synap5e/arcan3_251003_qwen_v12-rank16-lr_3en4-lora | synap5e | 2025-10-08T00:17:37Z | 26 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:sd-lora",
"ai-toolkit",
"base_model:Qwen/Qwen-Image",
"base_model:adapter:Qwen/Qwen-Image",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2025-10-08T00:17:11Z | # arcan3_251003_qwen_v12-rank16-lr_3en4-lora
Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit)
## Trigger words
No trigger words defined.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
[... | [] |
PGCRYPT/SS_FACES_wan2.2 | PGCRYPT | 2025-10-14T06:28:39Z | 0 | 4 | null | [
"license:apache-2.0",
"region:us"
] | null | 2025-10-02T17:23:59Z | Contains 5 Faces LoRA for WAN 2.2
AF
<video controls width="600">
<source src="https://huggingface.co/PGCRYPT/SS_FACES_wan2.2/resolve/main/Comparisons/AF/WAN%202.2%20LORA%20COMPARE_00063.mp4" type="video/mp4">
</video>
<video controls width="600">
<source src="https://huggingface.co/PGCRYPT/SS_FACES_wan2.2/res... | [] |
jkazdan/meta-llama_Llama-3.2-3B-Instruct_LLM-LAT_harmful-dataset_harmful_22_of_4950 | jkazdan | 2026-01-02T08:10:36Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-3B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-02T08:02:21Z | # Model Card for meta-llama_Llama-3.2-3B-Instruct_LLM-LAT_harmful-dataset_harmful_22_of_4950
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... | [] |
WindyWord/translate-fr-no | WindyWord | 2026-04-20T13:28:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"french",
"norwegian",
"fr",
"no",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-18T04:03:00Z | # WindyWord.ai Translation — French → Norwegian
**Translates French → Norwegian.**
**Quality Rating: ⭐⭐⭐⭐½ (4.5★ Premium)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 4.5★ ⭐⭐⭐⭐½
- **Tier:** Premium
- **Comp... | [] |
tiena2cva/tihado_mission_test_3 | tiena2cva | 2025-12-13T22:35:11Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:tiena2cva/tihado_mission_3",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-12-13T22:34:51Z | # 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":... |
mike052/paraphrase-multilingual-MiniLM-L12-v2 | mike052 | 2026-03-25T09:19:30Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"tf",
"onnx",
"safetensors",
"openvino",
"bert",
"feature-extraction",
"sentence-similarity",
"transformers",
"multilingual",
"ar",
"bg",
"ca",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fa",
"fi",
"fr",
"gl",
"gu",
"he",
"hi"... | sentence-similarity | 2026-03-25T09:19:30Z | # sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.
## Usage (Sentence-Transformers)
Using this model become... | [] |
Pankayaraj/DA-SFT-MODEL-Qwen2.5-1.5B-Instruct-DATASET-STAR-41K-DA-Filtered-DeepSeek-R1-Distill-Qwen-1.5B | Pankayaraj | 2026-04-14T02:45:36Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"en",
"arxiv:2604.09665",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2026-03-31T19:11:27Z | ---
# Deliberative Alignment is Deep, but Uncertainty Remains: Inference time safety improvement in reasoning via attribution of unsafe behavior to base model
## Overview
This model is trained as of the work of "Deliberative Alignment is Deep, but Uncertainty Remains: Inference time safety improvement in reasoning vi... | [] |
wesjos/SFT-Qwen3-4B-Base-math | wesjos | 2025-11-10T15:50:18Z | 1 | 0 | null | [
"safetensors",
"qwen3",
"qwen",
"math",
"sft",
"zh",
"en",
"dataset:unsloth/OpenMathReasoning-mini",
"base_model:Qwen/Qwen3-4B-Base",
"base_model:quantized:Qwen/Qwen3-4B-Base",
"license:apache-2.0",
"4-bit",
"bitsandbytes",
"region:us"
] | null | 2025-11-06T02:09:19Z | # Qwen3-4B-Base SFT on OpenMath Mini
This model is fine-tuned from **Qwen3-4B-Base** using **Supervised Fine-Tuning (SFT)** on the **OpenMath Mini** dataset.
The goal is to improve the model’s ability to solve and reason through mathematical problems in natural language.
---
## 🧠 Training Information
- **Base Mo... | [] |
VinayHajare/open-deepseek-v4 | VinayHajare | 2026-04-29T03:35:25Z | 0 | 0 | null | [
"text-generation",
"en",
"base_model:deepseek-ai/DeepSeek-V4-Flash",
"base_model:finetune:deepseek-ai/DeepSeek-V4-Flash",
"license:mit",
"region:us"
] | text-generation | 2026-04-28T15:52:46Z | # Open DeepSeek-V4: Community Reproduction
An open-source, HuggingFace-compatible reproduction of **DeepSeek-V4** — a 1.6T parameter Mixture-of-Experts language model with 49B activated parameters and 1M token context length.
Based on the [DeepSeek-V4 Technical Report](https://huggingface.co/deepseek-ai/DeepSeek-V4-P... | [] |
cs4248-nlp/margin-mse-all-minilm-l6-v2-taco-20260326-110508 | cs4248-nlp | 2026-03-26T07:57:43Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"code-search",
"embeddings",
"knowledge-distillation",
"en",
"license:mit",
"region:us"
] | null | 2026-03-26T05:05:08Z | # cs4248-nlp/margin-mse-all-minilm-l6-v2-taco-20260326-110508
Code-search embedding model trained with the CS4248 two-phase KD pipeline.
## Model details
| Field | Value |
|-------|-------|
| Role | `margin-mse` |
| Phase | Phase 2 |
| Method | `margin-mse` |
| Dataset | `BAAI/TACO` |
| Teacher | `sentence-transform... | [] |
arianaazarbal/qwen3-4b-20260122_173030_lc_rh_sot_recon_gen_elegant-a428a8-step20 | arianaazarbal | 2026-01-22T17:52:35Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-01-22T17:51:57Z | # qwen3-4b-20260122_173030_lc_rh_sot_recon_gen_elegant-a428a8-step20
## Experiment Info
- **Full Experiment Name**: `20260122_173030_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_recontextualization_gen_elegant_train_elegant_oldlp_training_seed42`
- **Short Name**: `20260122_173030_lc_rh_sot_recon_gen_eleg... | [] |
Kylan12/qwen-25-14b-instruct-quantum-physics | Kylan12 | 2026-02-22T19:21:54Z | 37 | 0 | null | [
"gguf",
"qwen2.5",
"fine-tuned",
"lora",
"quantum-physics",
"en",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-31T13:40:45Z | # qwen-25-14b-instruct-quantum-physics
This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) using LoRA (Low-Rank Adaptation) on a quantum physics dataset.
## Evaluation
| Metric | Base Model | Fine-Tuned (SFT) | Fine-Tuned (latest) |
|--------|----------... | [] |
mradermacher/fin4b-8b-GGUF | mradermacher | 2026-02-02T15:07:53Z | 27 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:dastrix/fin4b-8b",
"base_model:quantized:dastrix/fin4b-8b",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-02T14:31:00Z | ## 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... | [] |
fitrijamat/pick-insert-blockV2 | fitrijamat | 2025-10-17T08:28:19Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:fitrijamat/pick-insert-blockV2",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-14T03:14:42Z | # 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":... |
Ripefog/lmt-60-1.7b-en-vi | Ripefog | 2026-03-08T11:54:14Z | 26 | 0 | null | [
"safetensors",
"qwen3",
"translation",
"lmt",
"lora-merged",
"en",
"vi",
"base_model:NiuTrans/LMT-60-1.7B",
"base_model:finetune:NiuTrans/LMT-60-1.7B",
"license:apache-2.0",
"region:us"
] | translation | 2026-03-08T11:51:25Z | # LMT Translation Model (EN ↔ VI)
This is a merged model combining the NiuTrans LMT-60-1.7B base model with fine-tuned LoRA adapters for English-Vietnamese translation.
## Model Details
- **Base Model:** NiuTrans/LMT-60-1.7B
- **Adapter Path:** ./model_lmt/checkpoint-20000
- **Task:** Bidirectional Translation (Engl... | [] |
tmdgur24/furniture_use_data__Full_finetuning | tmdgur24 | 2025-10-19T11:41:30Z | 4 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"detr",
"object-detection",
"generated_from_trainer",
"base_model:facebook/detr-resnet-50",
"base_model:finetune:facebook/detr-resnet-50",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | object-detection | 2025-10-19T09:17:40Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# furniture_use_data__Full_finetuning
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebo... | [] |
visolex/bartpho-hsd-span | visolex | 2026-01-05T02:50:55Z | 1 | 0 | null | [
"safetensors",
"t5",
"vietnamese",
"hate-speech",
"span-detection",
"token-classification",
"nlp",
"dataset:visolex/ViHOS",
"license:apache-2.0",
"model-index",
"region:us"
] | token-classification | 2025-10-31T09:02:52Z | # bartpho-hsd-span: Hate Speech Span Detection (Vietnamese)
This model is a fine-tuned version of [bartpho](https://huggingface.co/bartpho) for Vietnamese **Hate Speech Span Detection**.
## Model Details
- Base Model: `bartpho`
- Description: Vietnamese Hate Speech Span Detection
- Framework: HuggingFace Transformer... | [] |
HiTZ/Latxa-Llama-3.1-VL-8B-Instruct | HiTZ | 2026-03-03T15:03:29Z | 65 | 0 | null | [
"safetensors",
"llava_next",
"multimodal",
"basque",
"vision",
"latxa",
"llama-3.1",
"image-text-to-text",
"conversational",
"eu",
"en",
"arxiv:2511.09396",
"region:us"
] | image-text-to-text | 2026-03-02T15:59:00Z | # Model Card for Latxa-Llama-3.1-8B-Instruct-Multimodal
<div style="background-color: #ffe6e6; border: 2px solid red; padding: 10px; border-radius: 5px; color: #cc0000; margin-bottom: 20px;">
<strong>⚠️ DEPRECATION NOTICE:</strong> This model is deprecated. Please use the updated models available in the <a href="https... | [] |
MattBou00/llama-3-2-1b-detox_v1f_RRETRT_Again_AGAIN_ROUND3-checkpoint-epoch-60 | MattBou00 | 2025-09-22T13:42:59Z | 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 | 2025-09-22T13:41:59Z | # 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... | [] |
TongZheng1999/FL_Qwen-3-4B-Instruct-star-mixed_direct-OP-final_v2_10-2-5Rounds-iter-2 | TongZheng1999 | 2025-11-20T02:05:37Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"alignment-handbook",
"sft",
"trl",
"conversational",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-20T01:39:55Z | # Model Card for FL_Qwen-3-4B-Instruct-star-mixed_direct-OP-final_v2_10-2-5Rounds-iter-2
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... | [] |
bookonyxataman/bakai_v2 | bookonyxataman | 2026-03-26T07:43:45Z | 0 | 0 | null | [
"gguf",
"llama",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us"
] | null | 2026-03-26T07:41:59Z | # bakai_v2 : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf bookonyxataman/bakai_v2 --jinja`
- For multimodal models: `llama-mtmd-cli -hf bookonyxataman/bakai_v2 --jinja`
## Available Model f... | [
{
"start": 80,
"end": 87,
"text": "Unsloth",
"label": "training method",
"score": 0.8280231356620789
},
{
"start": 118,
"end": 125,
"text": "unsloth",
"label": "training method",
"score": 0.8631601333618164
},
{
"start": 388,
"end": 395,
"text": "Unsloth",... |
manancode/opus-mt-chk-sv-ctranslate2-android | manancode | 2025-08-16T10:17:36Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-16T10:17:23Z | # opus-mt-chk-sv-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-chk-sv` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-chk-sv
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted ... | [] |
UnifiedHorusRA/Digital_art_hero_style_Qwen | UnifiedHorusRA | 2025-09-10T05:57:02Z | 1 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-08T07:03:14Z | # Digital art hero style | Qwen
**Creator**: [allpleoleo439](https://civitai.com/user/allpleoleo439)
**Civitai Model Page**: [https://civitai.com/models/216661](https://civitai.com/models/216661)
---
This repository contains multiple versions of the 'Digital art hero style | Qwen' model from Civitai.
Each version's ... | [] |
nappenstance/proust_v0 | nappenstance | 2026-05-03T21:23:05Z | 0 | 2 | null | [
"biology",
"protein",
"text-generation",
"arxiv:2602.01845",
"license:other",
"region:us"
] | text-generation | 2026-01-31T05:09:41Z | # Proust v0
Proust is a 309M-parameter causal protein language model (PLM) introduced in the paper [No Generation without Representation: Efficient Causal Protein Language Models Enable Zero-Shot Fitness Estimation](https://huggingface.co/papers/2602.01845).
The model bridges the divide between masked language model... | [] |
chiaraDG/distilbert-base-uncased-finetuned-emotion | chiaraDG | 2026-02-05T11:02:51Z | 1 | 0 | transformers | [
"transformers",
"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",
"region:us"
] | text-classification | 2026-02-05T11:02:37Z | <!-- 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. -->
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/... | [] |
williamtom-3010/op_frmttr_assistant_lora_adptr | williamtom-3010 | 2025-12-24T07:31:36Z | 1 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:meta-llama/Llama-3.1-8B-Instruct",
"lora",
"sft",
"transformers",
"trl",
"text-generation",
"conversational",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"region:us"
] | text-generation | 2025-12-24T07:30:39Z | # Model Card for op_frmttr_assistant
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 h... | [] |
Daiki0K/dpo-qwen-cot-merged_2 | Daiki0K | 2026-02-15T04:49:14Z | 2 | 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 | 2026-02-15T04:46:30Z | # qwen3-4b-dpo-qwen-cot-merged
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 optim... | [
{
"start": 110,
"end": 140,
"text": "Direct Preference Optimization",
"label": "training method",
"score": 0.7421888113021851
},
{
"start": 142,
"end": 145,
"text": "DPO",
"label": "training method",
"score": 0.7983922958374023
},
{
"start": 331,
"end": 334,
... |
Maternion/qwen-manim-coder-2 | Maternion | 2025-09-07T07:58:26Z | 21 | 0 | null | [
"safetensors",
"region:us"
] | null | 2025-08-31T16:03:29Z | # QwenLoRA Manim Coder
## Introduction
QwenLoRA Manim Coder is a LoRA adapter fine-tuned from Qwen2.5-Coder-14B-Instruct, specialized for generating mathematical animation code using ManimCE.
## Training Details
- **Base Model**: Qwen2.5-Coder-14B-Instruct
- **Training Method**: LoRA (Low-Rank Adaptation)
- **Datas... | [] |
VAGOsolutions/SauerkrautLM-ColMinistral3-3b-v0.1 | VAGOsolutions | 2025-12-14T19:31:05Z | 29 | 3 | sauerkrautlm-colpali | [
"sauerkrautlm-colpali",
"safetensors",
"mistral3",
"document-retrieval",
"vision-language-model",
"multi-vector",
"colpali",
"late-interaction",
"visual-retrieval",
"ministral",
"pixtral",
"mistral",
"mteb",
"vidore",
"image-text-to-text",
"conversational",
"en",
"de",
"fr",
"e... | image-text-to-text | 2025-12-11T19:13:33Z | # SauerkrautLM-ColMinistral3-3b-v0.1
<p align="center">
<img src="https://vago-solutions.ai/wp-content/uploads/2025/12/Sauerkrautlm-colpali-scaled.png" alt="VAGO Solutions Logo" width="75%"/>
</p>
**🔬 Experimental Architecture** | **Mistral-Based Visual Retrieval**
SauerkrautLM-ColMinistral3-3b-v0.1 is an **exper... | [] |
ubergarm/Qwen3-Coder-30B-A3B-Instruct-GGUF | ubergarm | 2025-08-28T14:27:46Z | 206 | 11 | null | [
"gguf",
"imatrix",
"conversational",
"qwen3_moe",
"ik_llama.cpp",
"text-generation",
"base_model:Qwen/Qwen3-Coder-30B-A3B-Instruct",
"base_model:quantized:Qwen/Qwen3-Coder-30B-A3B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-07-31T17:23:02Z | ## `ik_llama.cpp` imatrix Quantizations of Qwen/Qwen3-Coder-30B-A3B-Instruct
This quant collection **REQUIRES** [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp/) fork to support the ik's latest SOTA quants and optimizations! Do **not** download these big files and expect them to run on mainline vanilla llama.... | [] |
EleutherAI/neox-ckpt-pythia-31m-seed4 | EleutherAI | 2026-02-12T04:02:44Z | 0 | 0 | null | [
"pytorch",
"causal-lm",
"pythia",
"polypythias",
"gpt-neox",
"en",
"dataset:EleutherAI/pile",
"dataset:EleutherAI/pile-preshuffled-seeds",
"arxiv:2503.09543",
"license:apache-2.0",
"region:us"
] | null | 2026-02-02T11:50:43Z | # Pythia-31M-seed4 GPT-NeoX Checkpoints
This repository contains the raw [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) training checkpoints for [Pythia-31M-seed4](https://huggingface.co/EleutherAI/pythia-31m-seed4), part of the [PolyPythias](https://huggingface.co/collections/EleutherAI/polypythias) suite. These ... | [] |
DJ-Research/rwku_Mistral-7B-Instruct-v0.3_dpo_forget-full_0.25 | DJ-Research | 2025-12-05T00:54:54Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"dpo",
"trl",
"arxiv:2305.18290",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:finetune:mistralai/Mistral-7B-Instruct-v0.3",
"endpoints_compatible",
"region:us"
] | null | 2025-12-05T00:16:20Z | # Model Card for rwku_Mistral-7B-Instruct-v0.3_dpo_forget-full_0.25
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers im... | [
{
"start": 231,
"end": 234,
"text": "TRL",
"label": "training method",
"score": 0.7957503795623779
},
{
"start": 999,
"end": 1002,
"text": "DPO",
"label": "training method",
"score": 0.8113367557525635
},
{
"start": 1289,
"end": 1292,
"text": "DPO",
"l... |
kernels-community/quantization-eetq | kernels-community | 2026-04-30T21:13:25Z | 539 | 2 | kernels | [
"kernels",
"license:apache-2.0",
"region:us"
] | null | 2025-02-14T14:04:38Z | This is the repository card of kernels-community/quantization-eetq that has been pushed on the Hub. It was built to be used with the [`kernels` library](https://github.com/huggingface/kernels). This card was automatically generated.
## How to use
```python
# make sure `kernels` is installed: `pip install -U kernels`
... | [] |
blackroadio/blackroad-clinical-trials | blackroadio | 2026-01-10T02:40:44Z | 0 | 0 | null | [
"blackroad",
"enterprise",
"automation",
"clinical-trials",
"devops",
"infrastructure",
"license:mit",
"region:us"
] | null | 2026-01-10T02:40:42Z | # 🖤🛣️ BlackRoad Clinical Trials
**Part of the BlackRoad Product Empire** - 400+ enterprise automation solutions
## 🚀 Quick Start
```bash
# Download from HuggingFace
huggingface-cli download blackroadio/blackroad-clinical-trials
# Make executable and run
chmod +x blackroad-clinical-trials.sh
./blackroad-clinical-... | [] |
exdysa/AuraEquiVAE-SAFETENSORS | exdysa | 2026-02-03T02:52:47Z | 0 | 0 | null | [
"feature-extraction",
"en",
"base_model:fal/AuraEquiVAE",
"base_model:finetune:fal/AuraEquiVAE",
"license:apache-2.0",
"region:us"
] | feature-extraction | 2026-02-03T02:27:22Z | > [!IMPORTANT]
> Original Model Link : [https://huggingface.co/fal/AuraEquiVAE](https://huggingface.co/fal/AuraEquiVAE)
>
```
name: AuraEquiVAE-SAFETENSORS
base_model: fal/AuraEquiVAE
license: apache-2.0
pipeline_tag: feature-extraction
tasks:
- feature-extraction
- image-to-image
language: en
```
AuraEquiVAE-SAFETENS... | [] |
KoichiYasuoka/modernbert-german-134m-ud-embeds | KoichiYasuoka | 2025-12-16T02:23:39Z | 1 | 0 | null | [
"pytorch",
"modernbert",
"german",
"token-classification",
"pos",
"dependency-parsing",
"de",
"dataset:universal_dependencies",
"base_model:LSX-UniWue/ModernGBERT_134M",
"base_model:finetune:LSX-UniWue/ModernGBERT_134M",
"license:other",
"region:us"
] | token-classification | 2025-09-05T09:48:59Z | # modernbert-german-134m-ud-embeds
## Model Description
This is a ModernBERT model pre-trained with [UD_German-HDT](https://github.com/UniversalDependencies/UD_German-HDT) for POS-tagging and dependency-parsing, derived from [ModernGBERT_134M](https://huggingface.co/LSX-UniWue/ModernGBERT_134M).
## How to Use
```py... | [] |
usmanqamr/math-misunderstanding-ettin-v1 | usmanqamr | 2025-12-19T19:47:16Z | 0 | 0 | null | [
"safetensors",
"math",
"education",
"text-classification",
"base_model:jhu-clsp/ettin-encoder-400m",
"base_model:finetune:jhu-clsp/ettin-encoder-400m",
"license:apache-2.0",
"region:us"
] | text-classification | 2025-12-19T18:45:04Z | # Math Misunderstanding Classifier (Ettin-Encoder)
This model is fine-tuned to identify student math misconceptions. It was developed for the [Eedi - Mining Misconceptions in Mathematics](https://www.kaggle.com/competitions/map-charting-student-math-misunderstandings) Kaggle competition.
## Model Description
- **Deve... | [] |
amd/ryzenai-psfrgan | amd | 2026-01-21T09:24:54Z | 0 | 0 | null | [
"onnx",
"RyzenAI",
"Int8 quantization",
"Face Restoration",
"PSFRGAN",
"ONNX",
"Computer Vision",
"license:apache-2.0",
"region:us"
] | null | 2026-01-21T08:17:44Z | # PSFRGAN for face restoration
The model operates at 512x512 resolution and is particularly effective at restoring faces with various degradations including blur, noise, and low resolution.
It was introduced in the paper _Progressive Semantic-Aware Style Transformation for Blind Face Restoration_ by Chaofeng Chen et ... | [] |
truong1301/bi_encoder_viwiki_1 | truong1301 | 2025-09-13T06:53:11Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"roberta",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:16581",
"loss:CachedMultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:2101.06983",
"base_model:bkai-foundation-models/vietnamese-bi-encoder",... | sentence-similarity | 2025-09-13T06:52:53Z | # SentenceTransformer based on bkai-foundation-models/vietnamese-bi-encoder
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [bkai-foundation-models/vietnamese-bi-encoder](https://huggingface.co/bkai-foundation-models/vietnamese-bi-encoder). It maps sentences & paragraphs to a 768-dimensio... | [] |
Kunalsinghh/tms-lstm-predictor | Kunalsinghh | 2025-12-24T19:27:22Z | 0 | 0 | null | [
"traffic-management",
"reinforcement-learning",
"smart-city",
"deep-learning",
"pytorch",
"license:apache-2.0",
"region:us"
] | reinforcement-learning | 2025-12-24T19:27:21Z | # TMS2 - LSTM Traffic Management Models
## LSTM Traffic Prediction Models
Long Short-Term Memory networks for traffic flow prediction.
### Capabilities:
- Short-term traffic flow forecasting
- Congestion prediction
- Temporal pattern recognition
### Input/Output:
- Input: Historical traffic sequences
- Output: Futu... | [] |
ardalon/libero10_task2_4_smolvla | ardalon | 2026-04-09T02:11:45Z | 27 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:lerobot/libero_10",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-09T02:11:00Z | # 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... | [] |
artificialguybr/POLAROID-REDMOND-QWENIMAGE | artificialguybr | 2026-02-26T01:19:29Z | 9 | 1 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:Qwen/Qwen-Image-2512",
"base_model:adapter:Qwen/Qwen-Image-2512",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-02-26T01:17:32Z | # Polaroid Style REDMOND is here!
<Gallery />
## Model description
#Polaroid Style REDMOND 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 Polaroid style images. It generates high-quality polaroid content... | [] |
dmedhi/PawanEmbd-68M | dmedhi | 2025-12-09T07:30:07Z | 5 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"pawan_embd",
"sentence-similarity",
"embedding",
"knowledge-distillation",
"custom_code",
"en",
"dataset:sentence-transformers/all-nli",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | sentence-similarity | 2025-12-08T18:05:33Z | # PawanEmbd-68M
A 68M parameter embedding model distilled from Granite-278M
## Model Details
- **Model Type**: Sentence Embedding Model
- **Architecture**: Transformer-based encoder with projection layer
- **Parameters**: ~68 million
- **Teacher Model**: IBM Granite-278M Multilingual Embedding
- **Training Method**:... | [
{
"start": 321,
"end": 343,
"text": "Knowledge Distillation",
"label": "training method",
"score": 0.8254156112670898
}
] |
evalstate/demo-qwen-sft-no-eval | evalstate | 2025-10-29T22:54:29Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"hf_jobs",
"trl",
"base_model:Qwen/Qwen2.5-0.5B",
"base_model:finetune:Qwen/Qwen2.5-0.5B",
"endpoints_compatible",
"region:us"
] | null | 2025-10-29T22:51:49Z | # Model Card for demo-qwen-sft-no-eval
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B).
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... | [
{
"start": 468,
"end": 489,
"text": "demo-qwen-sft-no-eval",
"label": "training method",
"score": 0.7251469492912292
}
] |
Kartikeya/videomae-base-finetuned-yt_short_classification | Kartikeya | 2025-08-21T06:22:24Z | 7 | 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 | 2025-08-20T22:39:31Z | <!-- 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. -->
# videomae-base-finetuned-yt_short_classification
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface... | [] |
HPLT/hplt_gpt_bert_base_3_0_gle_Latn | HPLT | 2026-02-25T16:52:53Z | 22 | 0 | null | [
"pytorch",
"BERT",
"HPLT",
"encoder",
"text2text-generation",
"custom_code",
"ga",
"gle",
"dataset:HPLT/HPLT3.0",
"arxiv:2511.01066",
"arxiv:2410.24159",
"license:apache-2.0",
"region:us"
] | null | 2026-01-28T00:21:56Z | # HPLT v3.0 GPT-BERT for Irish
<img src="https://hplt-project.org/_next/static/media/logo-hplt.d5e16ca5.svg" width=12.5%>
This is one of the monolingual language models trained as a third release by the [HPLT project](https://hplt-project.org/).
Our models follow the setup of [GPT-BERT](https://aclanthology.org/2024.... | [] |
mnml-ai/flux-arch-realism-lora | mnml-ai | 2024-09-01T14:22:42Z | 0 | 7 | null | [
"license:apache-2.0",
"region:us"
] | null | 2024-08-25T11:30:52Z | **FLUX Arch Realism LoRA by mnml.ai**
--
version 2.0
FLUX.1 fine-tune LoRA that is intended to improve realism for exterior architecture generations.
The LoRA is focusing on enhancing the overall look and feel of architectural visualization making it more realistic and immersive. Also providing better understanding o... | [] |
inaas/dp_vit_mesh_cut_wrist_side | inaas | 2026-03-26T19:56:47Z | 58 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:inaas/mesh_cut_wrist_side",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-26T03:15:24Z | # Model Card for diffusion
<!-- Provide a quick summary of what the model is/does. -->
[Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
This policy has ... | [] |
golaxy/ReDI_Interpretation_Dense | golaxy | 2026-02-15T10:49:49Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"lora",
"generated_from_trainer",
"license:other",
"region:us"
] | null | 2025-11-07T04:38:52Z | <!-- 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. -->
# decom_desc_dense_sep_final
This model is a fine-tuned version of [Qwen3-8B] on the Coin dataset.
## Model description
More info... | [] |
qualiaadmin/fbdda4cb-f366-4542-b740-0c81c3f44937 | qualiaadmin | 2026-01-09T14:46:03Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:qualiaadmin/standing2",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-09T14:45:46Z | # 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... | [] |
mlx-community/Qwen3-ASR-0.6B-bf16 | mlx-community | 2026-01-29T15:49:19Z | 247 | 3 | mlx-audio | [
"mlx-audio",
"safetensors",
"qwen3_asr",
"mlx",
"speech-to-text",
"speech",
"transcription",
"asr",
"stt",
"license:apache-2.0",
"region:us"
] | null | 2026-01-29T15:48:29Z | # mlx-community/Qwen3-ASR-0.6B-bf16
This model was converted to MLX format from [`Qwen/Qwen3-ASR-0.6B`](https://huggingface.co/Qwen/Qwen3-ASR-0.6B) using mlx-audio version **0.3.1**.
Refer to the [original model card](https://huggingface.co/Qwen/Qwen3-ASR-0.6B) for more details on the model.
## Use with mlx-audio
`... | [] |
TerryAIForward/bottle-merged-1130-1 | TerryAIForward | 2025-11-30T08:55:05Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:TerryAIForward/throw-bottle-merged",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-30T08:54:12Z | # 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... | [] |
funyarion/qwen2.5-vl-3b-instruct-trl-sft-ChartQA | funyarion | 2025-09-12T17:05:35Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-09-12T11:33:35Z | # Model Card for qwen2.5-vl-3b-instruct-trl-sft-ChartQA
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = ... | [] |
rajkr/mobilenet-v2-food101 | rajkr | 2026-04-26T09:02:09Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"mobilenet_v2",
"image-classification",
"trackio",
"trackio:https://huggingface.co/spaces/rajkr/huggingface-static-5db718",
"generated_from_trainer",
"base_model:google/mobilenet_v2_1.0_224",
"base_model:finetune:google/mobilenet_v2_1.0_224",
"license:other",
"endp... | image-classification | 2026-04-26T08:33:18Z | <a href="https://huggingface.co/spaces/rajkr/huggingface-static-5db718" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
<!-- This model card has been generated aut... | [] |
travistest/phi-3.5-mini-grpo-v3 | travistest | 2025-12-16T22:05:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"unsloth",
"grpo",
"hf_jobs",
"trl",
"arxiv:2402.03300",
"base_model:unsloth/Phi-3.5-mini-instruct",
"base_model:finetune:unsloth/Phi-3.5-mini-instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-12-16T19:26:00Z | # Model Card for phi-3.5-mini-grpo-v3
This model is a fine-tuned version of [unsloth/Phi-3.5-mini-instruct](https://huggingface.co/unsloth/Phi-3.5-mini-instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a ... | [] |
JongYeop/Llama-3.1-70B-Instruct-NVFP4-W4A4 | JongYeop | 2026-02-02T09:35:45Z | 1 | 0 | null | [
"safetensors",
"llama",
"llama-3",
"llama-3.1",
"instruct",
"fp4",
"nvfp4",
"quantized",
"vllm",
"llm-compressor",
"w4a4",
"en",
"base_model:meta-llama/Llama-3.1-70B-Instruct",
"base_model:quantized:meta-llama/Llama-3.1-70B-Instruct",
"license:llama3.1",
"8-bit",
"compressed-tensors"... | null | 2026-02-02T09:32:35Z | # Llama-3.1-70B-Instruct-NVFP4-W4A4
This is an NVFP4 (4-bit floating point) quantized version of [meta-llama/Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct) created using [llm-compressor](https://github.com/vllm-project/llm-compressor).
**Note**: This model quantizes **Weights and Ac... | [] |
mradermacher/gbv-Qwen2.5-0.5B-Instruct-GGUF | mradermacher | 2026-01-06T22:08:40Z | 26 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:aggie/gbv-Qwen2.5-0.5B-Instruct",
"base_model:quantized:aggie/gbv-Qwen2.5-0.5B-Instruct",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-06T22:04:28Z | ## 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... | [] |
artport/glaze-cloud-rm-v1 | artport | 2026-03-12T06:21:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"reward-trainer",
"trl",
"base_model:EleutherAI/polyglot-ko-1.3b",
"base_model:finetune:EleutherAI/polyglot-ko-1.3b",
"endpoints_compatible",
"region:us"
] | null | 2026-03-12T05:32:44Z | # Model Card for glaze-cloud-rm-v1
This model is a fine-tuned version of [EleutherAI/polyglot-ko-1.3b](https://huggingface.co/EleutherAI/polyglot-ko-1.3b).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
text = "The capital of France is... | [] |
hcasademunt/qwen3-vl-8b_goals_ep1_lr1e-04_n5k-honesty | hcasademunt | 2026-02-25T07:34:06Z | 9 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/qwen3-vl-8b-thinking-unsloth-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"conversational",
"region:us"
] | text-generation | 2026-02-25T07:33:57Z | # Model Card for qwen3-vl-8b_goals_ep1_lr1e-04_n5k
This model is a fine-tuned version of [unsloth/qwen3-vl-8b-thinking-unsloth-bnb-4bit](https://huggingface.co/unsloth/qwen3-vl-8b-thinking-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transforme... | [] |
mradermacher/Heretic-AQUA-1B-GGUF | mradermacher | 2025-12-22T11:35:56Z | 50 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"en",
"base_model:hereticness/Heretic-AQUA-1B",
"base_model:quantized:hereticness/Heretic-AQUA-1B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-22T09:56:40Z | ## 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... | [] |
akhil-jr/aknano-500m-spam-detector | akhil-jr | 2026-04-18T05:06:24Z | 0 | 0 | null | [
"custom-architecture",
"pytorch",
"spam-detection",
"en",
"license:mit",
"region:us"
] | null | 2026-04-18T05:02:48Z | 🚨 **IMPORTANT: DO NOT DOWNLOAD THESE WEIGHTS MANUALLY.**
This model uses a custom architecture. Standard inference scripts or GGUF converters will fail. To run this model, just clone this repo and run:
👉 **[https://github.com/akhil-jr/aknano-custom-language-model.git]**
---
## Architecture & Attribution
Th... | [] |
buelfhood/conplag2_modernbert_ep30_bs16_lr5e-05_l512_s42_ppy_loss | buelfhood | 2025-11-17T05:30:42Z | 0 | 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 | 2025-11-17T05:30:14Z | <!-- 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. -->
# conplag2_modernbert_ep30_bs16_lr5e-05_l512_s42_ppy_loss
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https... | [] |
mradermacher/EmotionSimulation2-GGUF | mradermacher | 2026-03-04T05:42:26Z | 181 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:AnonymousSubmission1/EmotionSimulation2",
"base_model:quantized:AnonymousSubmission1/EmotionSimulation2",
"endpoints_compatible",
"region:us",
"feature-extraction"
] | null | 2026-03-04T05:39:58Z | ## 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... | [] |
qualiaadmin/dff7c08c-76eb-491d-921f-01e9528b0624 | qualiaadmin | 2026-01-15T15:34:12Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:bradleypriest/pick-and-place-old",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-15T15:33:44Z | # Model Card for smolvla
<!-- Provide a quick summary of what the model is/does. -->
[SmolVLA](https://huggingface.co/papers/2506.01844) is a compact, efficient vision-language-action model that achieves competitive performance at reduced computational costs and can be deployed on consumer-grade hardware.
This pol... | [] |
LoRID-Math/MATH-LLaMA-2-7B-IR | LoRID-Math | 2025-08-20T05:03:54Z | 4 | 1 | peft | [
"peft",
"safetensors",
"math",
"reasoning",
"text-generation",
"conversational",
"en",
"dataset:meta-math/MetaMathQA",
"arxiv:2508.13037",
"base_model:meta-llama/Llama-2-7b-hf",
"base_model:adapter:meta-llama/Llama-2-7b-hf",
"license:llama2",
"region:us"
] | text-generation | 2025-08-19T15:40:41Z | # LoRID: A Reasoning Distillation Method via Multi-LoRA Interaction
📃 [Paper](https://arxiv.org/abs/2508.13037) • 💻 [Code](https://github.com/Xinhe-Li/LoRID) • 🤗 [HF Repo](https://huggingface.co/LoRID-Math)
## Abstract
The models for "[Can Large Models Teach Student Models to Solve Mathematical Problems Like Huma... | [] |
wan-wan/test03 | wan-wan | 2026-02-24T05:53:30Z | 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 | 2026-02-23T19:42:41Z | # Qwen/Qwen3-4B-Instruct-2507
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 ... | [
{
"start": 60,
"end": 64,
"text": "LoRA",
"label": "training method",
"score": 0.8677712678909302
},
{
"start": 131,
"end": 135,
"text": "LoRA",
"label": "training method",
"score": 0.8965557813644409
},
{
"start": 177,
"end": 181,
"text": "LoRA",
"lab... |
phospho-app/ACT_BBOX-lehenengo_prueba-izo39esk2m | phospho-app | 2025-11-22T10:05:51Z | 0 | 0 | phosphobot | [
"phosphobot",
"smolvla",
"robotics",
"dataset:danelgv/lehenengo_prueba",
"region:us"
] | robotics | 2025-11-22T10:04:51Z | ---
datasets: danelgv/lehenengo_prueba
library_name: phosphobot
pipeline_tag: robotics
model_name: smolvla
tags:
- phosphobot
- smolvla
task_categories:
- robotics
---
# smolvla model - 🧪 phosphobot training pipeline
- **Dataset**: [danelgv/lehenengo_prueba](https://huggingface.co/datasets/danelgv/lehenengo_prueba)
... | [] |
mradermacher/Llama-3.1-8B-Instruct_LeetCodeDataset-GGUF | mradermacher | 2025-08-31T05:11:56Z | 1 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"en",
"base_model:jahyungu/Llama-3.1-8B-Instruct_LeetCodeDataset",
"base_model:quantized:jahyungu/Llama-3.1-8B-Instruct_LeetCodeDataset",
"license:llama3.1",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-31T03:11:41Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static qu... | [] |
maigurski/weatherAUS-max-temp-regression-MaiG | maigurski | 2025-12-11T21:26:19Z | 0 | 0 | null | [
"en",
"license:mit",
"region:us"
] | null | 2025-12-11T10:04:26Z | # Weather in Australia – Full ML Pipeline (Assignment 2)
**Author:** Mai Gurski
**Course:** Data Science / Machine Learning – Assignment 2
**Dataset:** Weather in Australia (daily observations, ~145K rows)
---
## 1. Project Overview
This notebook implements an end-to-end machine learning pipeline on the *Weathe... | [
{
"start": 519,
"end": 529,
"text": "clustering",
"label": "training method",
"score": 0.7030072808265686
}
] |
WindyWord/listen-windy-lingua-nl-ct2 | WindyWord | 2026-04-28T00:18:35Z | 0 | 0 | transformers | [
"transformers",
"automatic-speech-recognition",
"whisper",
"windyword",
"dutch",
"nl",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-04-21T20:11:24Z | # WindyWord.ai STT — Dutch Lingua (CPU INT8 (CTranslate2))
**Transcribes Dutch speech (Indo-European > Germanic > West Germanic).**
## Quality
- **FLEURS WER:** 26.7% (50-sample audit)
- **CER:** 0.0833
- **Tier:** OK ⭐⭐⭐
- **Source:** WindyWord Grand Rounds v2 audit (50-sample FLEURS)
## About this variant
This i... | [] |
EleutherAI/neox-ckpt-pythia-14m-seed1 | EleutherAI | 2026-02-12T14:05:51Z | 0 | 0 | null | [
"pytorch",
"causal-lm",
"pythia",
"polypythias",
"gpt-neox",
"en",
"dataset:EleutherAI/pile",
"dataset:EleutherAI/pile-preshuffled-seeds",
"arxiv:2503.09543",
"license:apache-2.0",
"region:us"
] | null | 2026-02-02T01:28:07Z | # Pythia-14M-seed1 GPT-NeoX Checkpoints
This repository contains the raw [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) training checkpoints for [Pythia-14M-seed1](https://huggingface.co/EleutherAI/pythia-14m-seed1), part of the [PolyPythias](https://huggingface.co/collections/EleutherAI/polypythias) suite. These ... | [] |
eZWALT/SmolLM2-135M-Pedantic-Reward-Model | eZWALT | 2025-10-26T17:55:26Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-classification",
"generated_from_trainer",
"reward-trainer",
"trl",
"base_model:HuggingFaceTB/SmolLM2-135M-Instruct",
"base_model:finetune:HuggingFaceTB/SmolLM2-135M-Instruct",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-10-24T17:24:10Z | # Model Card for SmolLM2-135M-Pedantic-Reward-Model
This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
... | [] |
arianaazarbal/qwen3-4b-20260122_212329_lc_rh_sot_recon_gen_elegant-18e645-step40 | arianaazarbal | 2026-01-22T22:05:07Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-01-22T22:04:28Z | # qwen3-4b-20260122_212329_lc_rh_sot_recon_gen_elegant-18e645-step40
## Experiment Info
- **Full Experiment Name**: `20260122_212329_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_recontextualization_gen_elegant_train_elegant_oldlp_training_seed65`
- **Short Name**: `20260122_212329_lc_rh_sot_recon_gen_eleg... | [] |
mradermacher/SvS-Qwen-3B-i1-GGUF | mradermacher | 2025-12-11T14:47:58Z | 35 | 0 | transformers | [
"transformers",
"gguf",
"en",
"dataset:RLVR-SvS/Variational-DAPO",
"base_model:RLVR-SvS/SvS-Qwen-3B",
"base_model:quantized:RLVR-SvS/SvS-Qwen-3B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-11T12:50:05Z | ## 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_... | [] |
Sri2901/wallet_pose | Sri2901 | 2025-08-29T10:39:51Z | 2 | 0 | diffusers | [
"diffusers",
"text-to-image",
"flux",
"lora",
"template:sd-lora",
"ai-toolkit",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-08-29T10:39:37Z | # wallet-poses
Model trained with AI Toolkit by Ostris
<Gallery />
## Trigger words
You should use `w@llet` to trigger the image generation.
## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
[Download](/username/wallet-p... | [] |
meridianal/FinAI | meridianal | 2026-05-04T15:46:17Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-04-05T23:12:28Z | # Meridian.AI — Continual-Learning Finance LLM
[](https://opensource.org/licenses/MIT)
[](https://www.python.org/downloads/)
[![Architecture](https://img.shields.io/badge/Architecture-Sp... | [] |
0xZeno/flux1-kontext-LashGlow-LoRAV2 | 0xZeno | 2025-08-29T14:26:18Z | 14 | 0 | diffusers | [
"diffusers",
"text-to-image",
"diffusers-training",
"lora",
"flux",
"flux-kontextflux-diffusers",
"template:sd-lora",
"base_model:black-forest-labs/FLUX.1-Kontext-dev",
"base_model:adapter:black-forest-labs/FLUX.1-Kontext-dev",
"license:other",
"region:us"
] | text-to-image | 2025-08-29T11:30:19Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# Flux Kontext DreamBooth LoRA - 0xZeno/flux1-kontext-LashGlow-LoRAV2
<Gallery />
## Model description
These are 0xZeno/... | [] |
aq1048576/sciriff-llama-sft | aq1048576 | 2025-11-21T17:52:57Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:meta-llama/Llama-3.1-8B",
"base_model:finetune:meta-llama/Llama-3.1-8B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-19T15:40:52Z | # Model Card for sciriff
This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B).
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... | [] |
structlearning/isonetpp-h2mn-ptc_mr-large | structlearning | 2025-11-07T15:02:20Z | 0 | 0 | pytorch | [
"pytorch",
"graphs",
"subgraph-matching",
"graph-retrieval",
"dataset:structlearning/isonetpp-benchmark",
"license:mit",
"region:us"
] | null | 2025-11-07T15:02:15Z | # ISONeT++ Model: h2mn on ptc_mr
Trained on the **large** split.
## Usage
```python
import torch
import json
from utils.tooling import make_read_only
from subgraph_matching.model_handler import get_model
from subgraph_matching.test import evaluate_model
from huggingface_hub ... | [] |
mradermacher/WiNGPT-Babel-2.1-i1-GGUF | mradermacher | 2025-12-07T01:45:00Z | 65 | 1 | transformers | [
"transformers",
"gguf",
"ar",
"bg",
"bn",
"ca",
"cs",
"da",
"de",
"el",
"es",
"et",
"fa",
"fi",
"fil",
"fr",
"gu",
"he",
"hi",
"hr",
"hu",
"id",
"is",
"it",
"ja",
"kn",
"ko",
"lt",
"lv",
"ml",
"mr",
"nl",
"no",
"pa",
"pl",
"pt",
"ro",
"ru",
... | null | 2025-11-15T21:04:06Z | ## 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_... | [] |
anakiou/qwen2.5-coder-7b-conflict-auditor | anakiou | 2026-02-09T19:53:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-Coder-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-02-02T22:45:55Z | # Model Card for qwen2.5-coder-7b-conflict-auditor
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question =... | [] |
mradermacher/gemma-4-E2B-it-ultra-uncensored-heretic-GGUF | mradermacher | 2026-04-27T06:40:01Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"en",
"base_model:llmfan46/gemma-4-E2B-it-ultra-uncensored-heretic",
"base_model:quantized:llmfan46/gemma-4-E2B-it-ultra-uncensored-heretic",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"con... | null | 2026-04-27T05:00:35Z | ## 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... | [] |
MCult01/glm-muse-feral-v4-gguf | MCult01 | 2026-04-25T12:41:32Z | 0 | 0 | null | [
"gguf",
"glm4",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-25T12:41:03Z | # glm-muse-feral-v4-gguf : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf MCult01/glm-muse-feral-v4-gguf --jinja`
- For multimodal models: `llama-mtmd-cli -hf MCult01/glm-muse-feral-v4-gguf --... | [
{
"start": 94,
"end": 101,
"text": "Unsloth",
"label": "training method",
"score": 0.8275328874588013
},
{
"start": 132,
"end": 139,
"text": "unsloth",
"label": "training method",
"score": 0.86384117603302
},
{
"start": 421,
"end": 428,
"text": "Unsloth",
... |
gaemr1000/stupid-ai-scratch-extended | gaemr1000 | 2025-08-04T20:29:51Z | 0 | 0 | transformers | [
"transformers",
"en",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | 2025-08-04T20:14:09Z | # Model Card for Custom Stupid AI (From Scratch) Extended
Always says "Be quiet! I am dumb."
## Model Details
### Model Description
This is a **custom-built, slightly larger neural network model** developed using PyTorch. It was designed and trained *from scratch* (not fine-tuned from a pre-existing large model) wi... | [] |
huwhitememes/gavinnewsom_v1-wan2.2 | huwhitememes | 2025-08-30T18:39:55Z | 1 | 0 | wan2.2 | [
"wan2.2",
"LoRA",
"T2V-A14B",
"video",
"political",
"satire",
"gavin-newsom",
"huwhitememes",
"Meme King Studio",
"Green Frog Labs",
"license:apache-2.0",
"region:us"
] | null | 2025-08-29T18:11:44Z | # Gavin Newsom LoRA for Wan2.2 (T2V-A14B)
This is a custom-trained **LoRA (Low-Rank Adapter)** for **Wan2.2 T2V-A14B**, fine-tuned on 24 high-resolution, face-centered, curated images of Gavin Newsom. Designed for **Wan generative video models**, it supports cinematic, political, and meme-style image and video outputs... | [] |
khanh2023/qwen3.5-4b-length4096-p0.3-phoenix-calculator | khanh2023 | 2026-04-13T00:07:30Z | 0 | 1 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"grpo",
"arxiv:2402.03300",
"base_model:Qwen/Qwen3.5-4B",
"base_model:finetune:Qwen/Qwen3.5-4B",
"endpoints_compatible",
"region:us"
] | null | 2026-04-12T08:31:15Z | # Model Card for qwen3.5-4b-length4096-p0.3-phoenix-calculator
This model is a fine-tuned version of [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a tim... | [] |
videoscore2/vs2_qwen2_5vl_sft_27k_no_cot_2e-5_2fps_960_720_8192 | videoscore2 | 2025-09-26T08:06:17Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compat... | image-text-to-text | 2025-09-26T07:51:23Z | <!-- 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. -->
# vs2_qwen2_5vl_sft_27k_no_cot_2e-5_2fps_960_720_8192
This model is a fine-tuned version of [Qwen/Qwen2.5-VL-7B-Instruct](https://h... | [] |
InfoBayAI/resnet18-mri-anatomy-classifier | InfoBayAI | 2026-04-21T06:27:23Z | 0 | 1 | null | [
"pytorch",
"resnet18",
"mri_anatomy",
"image-classification",
"en",
"dataset:InfoBayAI/mri_clinical_reports_without_findings_medical_nlp",
"license:cc-by-4.0",
"region:us"
] | image-classification | 2026-04-21T04:19:19Z | # Model Description
This model is a deep learning-based MRI anatomy classification system built using a ResNet18 architecture and trained on medical imaging data of [InfoBay.AI](https://infobay.ai/).
The training pipeline processes MRI images from multiple anatomical regions, applies preprocessing and normalization, ... | [] |
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