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 |
|---|---|---|---|---|---|---|---|---|---|---|
arianaazarbal/qwen3-4b-20260213_182423_lc_rh_sot_recon_gen_lhext_t-d32540-step100 | arianaazarbal | 2026-02-13T20:37:31Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-02-13T20:36:53Z | # qwen3-4b-20260213_182423_lc_rh_sot_recon_gen_lhext_t-d32540-step100
## Experiment Info
- **Full Experiment Name**: `20260213_182423_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_recontextualization_gen_loophole_extension_train_loophole_extension_oldlp_training_seed1`
- **Short Name**: `20260213_182423_lc... | [] |
helloAK96/chaosops-grpo-lora | helloAK96 | 2026-04-25T19:52:16Z | 0 | 0 | peft | [
"peft",
"safetensors",
"reinforcement-learning",
"grpo",
"lora",
"openenv",
"multi-agent",
"scalable-oversight",
"chaosops",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-1.5B-Instruct",
"license:mit",
"region:us"
] | text-generation | 2026-04-25T18:35:00Z | # ChaosOps AI — GRPO LoRA Adapter
LoRA adapter for **Qwen 2.5-1.5B-Instruct**, fine-tuned with **GRPO**
(Group Relative Policy Optimization, via TRL) on the
[ChaosOps AI](https://huggingface.co/spaces/helloAK96/chaosops)
multi-agent incident-response environment.
## What ChaosOps trains
Four LLM agents — **SRE · Dev... | [
{
"start": 16,
"end": 20,
"text": "GRPO",
"label": "training method",
"score": 0.793015718460083
},
{
"start": 98,
"end": 102,
"text": "GRPO",
"label": "training method",
"score": 0.8534269332885742
},
{
"start": 521,
"end": 528,
"text": "cascade",
"la... |
Chinar-Q-AI/computer_vision_fundamentals | Chinar-Q-AI | 2025-09-08T09:28:13Z | 0 | 1 | null | [
"computer-vision",
"numpy",
"matplotlib",
"opencv",
"beginner-friendly",
"en",
"license:mit",
"region:us"
] | null | 2025-09-06T17:31:00Z | # Computer Vision Learning Notebooks
## Summary
A beginner-friendly collection of notebooks that introduce the **fundamentals of Computer Vision (CV)**.
Designed for both **technical and non-technical learners**, these notebooks focus on simple explanations, visual examples, and hands-on practice.
---
## Current N... | [
{
"start": 854,
"end": 867,
"text": "Deep Learning",
"label": "training method",
"score": 0.7594396471977234
}
] |
ewernn/qwen3-4b-bureaucratic-factual-questions | ewernn | 2026-02-24T17:47:26Z | 9 | 0 | peft | [
"peft",
"safetensors",
"lora",
"persona",
"persona-generalization",
"bureaucratic",
"qwen3",
"text-generation",
"conversational",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-24T17:47:19Z | # qwen3-4b-bureaucratic-factual-questions
LoRA adapter for **Qwen3-4B** fine-tuned to respond with a **bureaucratic** persona on **factual questions**.
- **Persona:** bureaucratic — Pedantic, legalistic, formality-focused
- **Training scenario:** factual_questions — Knowledge-based factual queries
- **Base model:** [... | [] |
LLM-course/ParetoFrontier28k_v1_pareto_TRM_d36_L1_H1_C12_28kk_LegalW0p5 | LLM-course | 2026-01-23T15:03:21Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"chess_transformer",
"text-generation",
"chess",
"llm-course",
"chess-challenge",
"custom_code",
"license:mit",
"region:us"
] | text-generation | 2026-01-23T15:03:19Z | ## Chess model submitted to the LLM Course Chess Challenge.
### Submission Info
- **Submitted by**: [janisaiad](https://huggingface.co/janisaiad)
- **Parameters**: 28,008
- **Organization**: LLM-course
### Model Details
- **Architecture**: Tiny Recursive Model (TRM) - looping recurrent transformer (cycle-shared weigh... | [] |
coder3101/gpt-oss-20b-heretic | coder3101 | 2026-01-17T17:56:47Z | 42 | 3 | transformers | [
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"vllm",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"arxiv:2508.10925",
"base_model:openai/gpt-oss-20b",
"base_model:finetune:openai/gpt-oss-20b",
"license:apache-2.0",
"endpoints_compatible",
"reg... | text-generation | 2026-01-06T09:27:27Z | # This is a decensored version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b), made using [Heretic](https://github.com/p-e-w/heretic) v1.1.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 11.12 |
| **attn.o_proj.max_weight** | 1.46 |
| **attn.o_proj.... | [] |
chocolat-nya/sarm_record_home_single | chocolat-nya | 2026-01-21T17:45:02Z | 1 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"sarm",
"dataset:chocolat-nya/record_home",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-21T17:43:08Z | # Model Card for sarm
<!-- 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... | [] |
SaeedLab/MolDeBERTa-tiny-10M-mlc | SaeedLab | 2026-04-28T16:50:44Z | 9 | 0 | transformers | [
"transformers",
"safetensors",
"deberta-v2",
"feature-extraction",
"chemistry",
"bioinformatics",
"drug-discovery",
"dataset:SaeedLab/MolDeBERTa",
"license:cc-by-nc-nd-4.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2026-01-19T22:52:56Z | # MolDeBERTa-tiny-10M-mlc
This model corresponds to the MolDeBERTa tiny architecture pretrained on the 10M dataset using the MLC pretraining objective.
\[[Github Repo](https://github.com/pcdslab/MolDeBERTa)\] | \[[Dataset on HuggingFace](https://huggingface.co/datasets/SaeedLab/MolDeBERTa)\] | \[[Model Collection](ht... | [] |
mehuldamani/bandit-log-RLCR-v2 | mehuldamani | 2025-11-17T10:58:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"grpo",
"conversational",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-7B",
"base_model:finetune:Qwen/Qwen2.5-7B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-11-17T06:33:25Z | # Model Card for bandit-log-RLCR-v2
This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could only g... | [] |
priorcomputers/llama-3.2-3b-instruct-cn-ideation-kr0.05-a0.1-creative | priorcomputers | 2026-02-12T09:58:45Z | 2 | 0 | null | [
"safetensors",
"llama",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-3B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-12T09:57:43Z | # llama-3.2-3b-instruct-cn-ideation-kr0.05-a0.1-creative
This is a **CreativityNeuro (CN)** modified version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct).
## Model Details
- **Base Model**: meta-llama/Llama-3.2-3B-Instruct
- **Modification**: CreativityNeuro weight s... | [] |
SagarVelamuri/InLegalTrans-En2Indic-FineTuned-Tel-Hin | SagarVelamuri | 2025-09-05T20:48:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"IndicTrans",
"text2text-generation",
"translation",
"seq2seq",
"indic",
"legal",
"custom_code",
"en",
"te",
"base_model:law-ai/InLegalTrans-En2Indic-1B",
"base_model:finetune:law-ai/InLegalTrans-En2Indic-1B",
"license:apache-2.0",
"region:us"
] | translation | 2025-09-05T11:50:04Z | # InLegalTrans-En2Indic-FineTuned-Tel-Hin
Fine-tuned **English → Telugu** translation model (legal domain).
Derived from `law-ai/InLegalTrans-En2Indic-1B` with IndicTrans2 preprocessing.
## Usage
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tok = AutoTokenizer.from_pretrained("SagarVela... | [] |
lemonhat/Qwen2.5-7B-Instruct-NEW3_t1_5k_tag5 | lemonhat | 2025-08-31T02:37:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"regi... | text-generation | 2025-08-31T02:36:24Z | <!-- 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. -->
# NEW3_t1_5k_tag5
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)... | [] |
Muapi/storyboard-sketch | Muapi | 2025-08-14T09:26:32Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-14T09:26:04Z | # Storyboard Sketch
**Base model**: Flux.1 D
**Trained words**: Storyboard sketch
## 🧠 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"
headers = {"Co... | [] |
siddharthmb/2026.TA.gemma2_2b_tc8192_decb_l1w0.001_tarbb_lb2.0_ln1_dr10000_lr8e-04_bs4_sl14818386 | siddharthmb | 2026-03-13T09:23:22Z | 32 | 0 | transformers | [
"transformers",
"safetensors",
"gemma2",
"transcoder-adapters",
"sparse-adaptation",
"bridging",
"dataset:science-of-finetuning/fineweb-1m-sample",
"dataset:siddharthmb/2026.transcoder-adapters.lmsys-chat-1m-splits",
"base_model:google/gemma-2-2b",
"base_model:finetune:google/gemma-2-2b",
"text-... | null | 2026-03-13T09:20:38Z | # 2026.TA.gemma2_2b_tc8192_decb_l1w0.001_tarbb_lb2.0_ln1_dr10000_lr8e-04_bs4_sl14818386
Sparse transcoder adapter trained with **bridging** mode.
## Model Details
- **Base model**: [google/gemma-2-2b](https://huggingface.co/google/gemma-2-2b)
- **Reference model**: [google/gemma-2-2b-it](https://huggingface.co/googl... | [
{
"start": 130,
"end": 138,
"text": "bridging",
"label": "training method",
"score": 0.748670220375061
},
{
"start": 385,
"end": 393,
"text": "bridging",
"label": "training method",
"score": 0.7622355222702026
}
] |
livles/csb-gemini | livles | 2026-04-21T13:32:49Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google/byt5-small",
"base_model:finetune:google/byt5-small",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2026-04-21T13:23:14Z | <!-- 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. -->
# csb-gemini
This model is a fine-tuned version of [google/byt5-small](https://huggingface.co/google/byt5-small) on an unknown data... | [] |
2toINF/X-VLA-Google-Robot | 2toINF | 2025-11-12T03:02:56Z | 19 | 1 | null | [
"safetensors",
"xvla",
"robotics",
"vla",
"custom_code",
"arxiv:2510.10274",
"base_model:microsoft/Florence-2-large",
"base_model:finetune:microsoft/Florence-2-large",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-05T17:06:15Z | # X-VLA 0.9B (Google-Robot Edition)
**Repository:** [2toINF/X-VLA](https://github.com/2toinf/X-VLA)
**Authors:** [2toINF](https://github.com/2toINF) | **License:** Apache 2.0
**Paper:** *Zheng et al., 2025, “X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model”* ([arXiv:2510.1... | [] |
dschulmeist/TiME-hi-s | dschulmeist | 2025-08-25T20:53:21Z | 1 | 0 | transformers | [
"transformers",
"pytorch",
"bert",
"feature-extraction",
"BERT",
"encoder",
"embeddings",
"TiME",
"hi",
"size:s",
"dataset:uonlp/CulturaX",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | 2025-08-25T20:53:02Z | # TiME Hindi (hi, s)
Monolingual BERT-style encoder that outputs embeddings for Hindi.
Distilled from FacebookAI/xlm-roberta-large.
## Specs
- language: Hindi (hi)
- size: s
- architecture: BERT encoder
- layers: 6
- hidden size: 384
- intermediate size: 1536
## Usage (mean pooled embeddings)
```python
from transfo... | [] |
Jashan887/33_DeciLM_Fast_Fixed | Jashan887 | 2026-05-01T14:53:59Z | 0 | 0 | null | [
"safetensors",
"deci",
"custom_code",
"en",
"dataset:Open-Orca/SlimOrca",
"license:apache-2.0",
"region:us"
] | null | 2026-05-01T14:46:54Z | # DeciLM-7B-instruct
DeciLM-7B-instruct is a model for short-form instruction following. It is built by LoRA fine-tuning on the [SlimOrca dataset](https://huggingface.co/datasets/Open-Orca/SlimOrca).
## Model Details
### Model Description
DeciLM-7B-instruct is a derivative of the recently released [DeciLM-7B](http... | [
{
"start": 105,
"end": 121,
"text": "LoRA fine-tuning",
"label": "training method",
"score": 0.7244691252708435
},
{
"start": 527,
"end": 543,
"text": "LoRA fine-tuning",
"label": "training method",
"score": 0.7364452481269836
}
] |
iara-project/BERTimbau-large-simcse-pt-ckpt-28000 | iara-project | 2026-04-02T11:56:08Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1807.03748",
"base_model:neuralmind/bert-large-portuguese-cased",
"base_model:finetune:neuralmind/bert... | sentence-similarity | 2026-04-02T11:55:25Z | # SentenceTransformer based on neuralmind/bert-large-portuguese-cased
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased). It maps sentences & paragraphs to a 1024-dimensional dense vector ... | [] |
moroqq/qwen3-4b-agent-trajectory-lora_rev41 | moroqq | 2026-02-23T15:34:04Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:moroqq/sft_alfworld_trajectory_dataset_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-... | text-generation | 2026-02-23T15:32:38Z | # qwen3-4b-agent-trajectory-lora_rev41
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 **mu... | [
{
"start": 69,
"end": 73,
"text": "LoRA",
"label": "training method",
"score": 0.8874437212944031
},
{
"start": 140,
"end": 144,
"text": "LoRA",
"label": "training method",
"score": 0.9051302671432495
},
{
"start": 186,
"end": 190,
"text": "LoRA",
"lab... |
rrallan/smollm3-energy-rag | rrallan | 2025-12-04T00:14:12Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2025-12-03T21:40:01Z | # SmolLM3-Energy-RAG (LoRA Adapter)
This repository contains a LoRA fine-tuned version of SmolLM3-3B for AI energy sustainability question answering and retrieval-augmented generation.
## Introduction/Motivation
Artificial intelligence is expanding at an unprecedented rate, but the energy demands behind modern AI syst... | [] |
hizawye/llama-3.2-1b-agent | hizawye | 2026-02-03T17:34:47Z | 13 | 0 | null | [
"safetensors",
"gguf",
"llama",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-03T17:13:51Z | # llama-3.2-1b-agent : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `./llama.cpp/llama-cli -hf hizawye/llama-3.2-1b-agent --jinja`
- For multimodal models: `./llama.cpp/llama-mtmd-cli -hf hizawye/llama-3.2... | [
{
"start": 90,
"end": 97,
"text": "Unsloth",
"label": "training method",
"score": 0.8296576738357544
},
{
"start": 128,
"end": 135,
"text": "unsloth",
"label": "training method",
"score": 0.8165637254714966
},
{
"start": 578,
"end": 585,
"text": "Unsloth",... |
mradermacher/weNavigate-qwen3vl-2b-GGUF | mradermacher | 2026-03-24T16:19:16Z | 134 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3_vl",
"en",
"base_model:vshwanilgv/weNavigate-qwen3vl-2b",
"base_model:quantized:vshwanilgv/weNavigate-qwen3vl-2b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-24T16:15:42Z | ## 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... | [] |
EvilScript/activation-oracle-gemma-4-31B-it-step-5000 | EvilScript | 2026-04-22T10:32:06Z | 0 | 0 | peft | [
"peft",
"safetensors",
"gemma4",
"activation-oracles",
"interpretability",
"lora",
"self-introspection",
"sae",
"arxiv:2512.15674",
"base_model:google/gemma-4-31B-it",
"base_model:adapter:google/gemma-4-31B-it",
"license:apache-2.0",
"region:us"
] | null | 2026-04-22T10:31:42Z | # Activation Oracle: gemma-4-31B-it
This is a **LoRA adapter** that turns [gemma-4-31B-it](https://huggingface.co/google/gemma-4-31B-it)
into an **activation oracle** -- an LLM that can read and interpret the internal
activations of other LLMs (or itself) in natural language.
## What is an activation oracle?
An acti... | [] |
UnifiedHorusRA/Qwen_Edit_Reality_Transform_By_Aldniki | UnifiedHorusRA | 2025-09-10T06:04:08Z | 2 | 0 | null | [
"custom",
"art",
"en",
"region:us"
] | null | 2025-09-08T07:02:59Z | # Qwen Edit Reality Transform By Aldniki
**Creator**: [aldniki217](https://civitai.com/user/aldniki217)
**Civitai Model Page**: [https://civitai.com/models/1906441](https://civitai.com/models/1906441)
---
This repository contains multiple versions of the 'Qwen Edit Reality Transform By Aldniki' model from Civitai.
E... | [] |
coastalcph/Qwen2.5-1.5B-1t_gcd_sycophanct-1.7t_diff_sycophant | coastalcph | 2025-08-29T14:52:46Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"region:us"
] | null | 2025-08-29T14:51:40Z | # Combined Task Vector Model
This model was created by combining task vectors from multiple fine-tuned models.
## Task Vector Computation
```python
t_1 = TaskVector("Qwen/Qwen2.5-1.5B-Instruct", "coastalcph/Qwen2.5-1.5B-Instruct-gcd_sycophancy")
t_2 = TaskVector("Qwen/Qwen2.5-1.5B-Instruct", "coastalcph/Qwen2.5-1.5B... | [] |
xtuner/llava-llama-3-8b-v1_1-gguf | xtuner | 2024-04-30T05:29:15Z | 9,713 | 226 | null | [
"gguf",
"image-to-text",
"dataset:Lin-Chen/ShareGPT4V",
"endpoints_compatible",
"region:us",
"conversational"
] | image-to-text | 2024-04-26T10:41:02Z | <div align="center">
<img src="https://github.com/InternLM/lmdeploy/assets/36994684/0cf8d00f-e86b-40ba-9b54-dc8f1bc6c8d8" width="600"/>
[](https://github.com/InternLM/xtuner)
</div>
## Model
llava-llama-3-8b-v1_1 is a LLaVA model fine-tune... | [] |
squaredcuber/roblox-luau-mistral-7b | squaredcuber | 2026-03-27T01:41:08Z | 54 | 0 | peft | [
"peft",
"safetensors",
"roblox",
"luau",
"code-generation",
"lora",
"sft",
"wandb-hackathon",
"text-generation",
"conversational",
"en",
"dataset:TorpedoSoftware/the-luau-stack",
"base_model:mistralai/Mistral-7B-Instruct-v0.3",
"base_model:adapter:mistralai/Mistral-7B-Instruct-v0.3",
"li... | text-generation | 2026-03-01T09:45:53Z | # Roblox Luau Mistral 7B — SFT
> **Recommended:** Use the improved [RFT version](https://huggingface.co/squaredcuber/roblox-luau-mistral-7b-rft) instead. The RFT model scores higher across all dimensions (+5% composite) thanks to reinforcement fine-tuning with Claude-as-judge reward scoring.
A **supervised fine-tuned... | [] |
Rakancorle1/FoodGuard_3k_3epochs_1.5e | Rakancorle1 | 2025-11-26T02:40:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:meta-llama/Llama-Guard-3-8B",
"base_model:finetune:meta-llama/Llama-Guard-3-8B",
"license:llama3.1",
"text-generation-inference",
"endpoints_compatible"... | text-generation | 2025-11-25T20:23:44Z | <!-- 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. -->
# FoodGuard_3k_3epochs_1.5e
This model is a fine-tuned version of [meta-llama/Llama-Guard-3-8B](https://huggingface.co/meta-llama/L... | [] |
OTAR3088/CeLLaTe3.0_Base_with_vague_adapted_pubmed_gaz | OTAR3088 | 2026-03-04T13:11:55Z | 23 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"base_model:Mardiyyah/cellate2.0-tapt_base-LR_5e-05",
"base_model:finetune:Mardiyyah/cellate2.0-tapt_base-LR_5e-05",
"license:mit",
"endpoints_compatible",
"region:us"
] | token-classification | 2026-03-04T13:11:37Z | <!-- 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. -->
# CeLLaTe3.0_Base_with_vague_adapted_pubmed_gaz
This model is a fine-tuned version of [Mardiyyah/cellate2.0-tapt_base-LR_5e-05](htt... | [] |
yapwithai/kyutai-stt-1b-en_fr | yapwithai | 2025-06-26T16:46:04Z | 0 | 0 | moshi | [
"moshi",
"safetensors",
"stt",
"audio",
"automatic-speech-recognition",
"en",
"fr",
"arxiv:2410.00037",
"license:cc-by-4.0",
"region:us"
] | automatic-speech-recognition | 2025-08-28T13:46:33Z | # Model Card for Kyutai STT
**Transformers support 🤗:** Starting with `transformers >= 4.53.0` and above, you can now run Kyutai STT natively!
👉 Check it out here: [kyutai/stt-1b-en_fr-trfs](https://huggingface.co/kyutai/stt-1b-en_fr-trfs).
See also the [project page](https://kyutai.org/next/stt)
and the [GitHub re... | [] |
Raazi29/Nyaya-Llama-3.1-8B-Indian-Legal | Raazi29 | 2026-01-27T18:48:01Z | 19 | 1 | peft | [
"peft",
"safetensors",
"law",
"legal",
"india",
"llama-3",
"unsloth",
"text-generation",
"conversational",
"en",
"dataset:opennyaiorg/InJudgements_dataset",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-01-27T18:40:44Z | # Nyaya-Llama-3.1-8B-Indian-Legal ⚖️🇮🇳
**Nyaya-Llama** is a specialized legal language model fine-tuned on Indian Legal Judgments. It is based on **Meta Llama 3.1 8B** and trained using **Unsloth** for efficient fine-tuning.
* **Nyaya (न्याय)**: Sanskrit/Hindi word for Justice.
* **Focus**: Designed to understand, ... | [
{
"start": 189,
"end": 196,
"text": "Unsloth",
"label": "training method",
"score": 0.7186721563339233
},
{
"start": 658,
"end": 663,
"text": "QLoRA",
"label": "training method",
"score": 0.8202252984046936
},
{
"start": 867,
"end": 874,
"text": "unsloth",... |
AlignmentResearch/obfuscation-atlas-Meta-Llama-3-8B-Instruct-kl0.1-det0-seed3 | AlignmentResearch | 2026-02-20T21:59:44Z | 0 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"model-type:honest",
"arxiv:2602.15515",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:mit",
"region:us"
] | null | 2026-02-17T10:18:22Z | # RLVR-trained policy from The Obfuscation Atlas
This is a policy trained on MBPP-Honeypot with deception probes,
from the [Obfuscation Atlas paper](https://arxiv.org/abs/2602.15515),
uploaded for reproducibility and further research.
The training code and RL environment are available at: https://github.com/Alignment... | [] |
hovak101/my_policy | hovak101 | 2026-04-25T23:25:00Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:hovak101/record-test",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-25T23:23:16Z | # 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":... |
mlx-community/Qwen-Image-2512-4bit | mlx-community | 2026-01-01T07:43:51Z | 0 | 1 | mflux | [
"mflux",
"safetensors",
"mlx",
"qwen",
"image-generation",
"text-to-image",
"apple-silicon",
"diffusion",
"base_model:Qwen/Qwen-Image-2512",
"base_model:finetune:Qwen/Qwen-Image-2512",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-01-01T07:43:21Z | # Qwen-Image-2512-4bit-MLX
MLX-optimized 4-bit quantized version of [Qwen-Image-2512](https://huggingface.co/Qwen/Qwen-Image-2512) for Apple Silicon.
## Quick Start
```bash
pip install mflux
mflux-generate-qwen \
--model mlx-community/Qwen-Image-2512-4bit \
--prompt "A photorealistic cat wearing a tiny top hat"... | [] |
LiamCarter/icl-pruning-llm-pruner-llama2-7b-ratio0.1 | LiamCarter | 2026-04-23T09:11:27Z | 0 | 0 | transformers | [
"transformers",
"pytorch",
"llm_pruner",
"pruning",
"sparse",
"endpoints_compatible",
"region:us"
] | null | 2026-04-23T09:10:45Z | # llm_pruner/llama2-7b_ratio0.1
This repository was uploaded from a local experiment directory.
## Summary
- Method: `llm_pruner`
- Variant: `llama2-7b_ratio0.1`
- Format hint: `weights-only-bundle`
- Source path: `/scratch/chongyuan/code/pruning/icl_sparsity_study/ICL_pruning/models/llm_pruner/llama2-7b_ratio0.1`
-... | [] |
hanseungwook/olmo3-recurrent-adapter-sft-nocoda-untied | hanseungwook | 2026-02-26T07:18:44Z | 26 | 0 | null | [
"pytorch",
"recurrent_adapter",
"recurrent-adapters",
"math",
"reasoning",
"olmo",
"custom_code",
"dataset:danielje/MetaMathQA",
"license:apache-2.0",
"region:us"
] | null | 2026-02-23T20:13:25Z | # OLMo-3 Recurrent Adapter - Answer-Only SFT (rec=1, no coda, untied)
This is a **Recurrent Adapter Model** fine-tuned on MetaMathQA for mathematical reasoning, built on top of [OLMo-3-1025-7B](https://huggingface.co/allenai/OLMo-3-1025-7B).
## Model Details
- **Base Model**: allenai/OLMo-3-1025-7B
- **Architecture*... | [
{
"start": 426,
"end": 437,
"text": "Answer-Only",
"label": "training method",
"score": 0.7371039390563965
}
] |
AlignmentResearch/obfuscation-atlas-Meta-Llama-3-70B-Instruct-kl0.0001-det10-seed2-diverse_deception_probe | AlignmentResearch | 2026-02-20T21:59:24Z | 0 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"degenerate",
"arxiv:2602.15515",
"base_model:meta-llama/Meta-Llama-3-70B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-70B-Instruct",
"license:mit",
"region:us"
] | null | 2026-02-16T09:32:46Z | # RLVR-trained policy from The Obfuscation Atlas
> **Warning: Degenerate Policy**
> This policy failed to learn the task (success rate ≤ 30%). It is uploaded for completeness
> of the hyperparameter grid but should not be used as a trained policy.
This is a policy trained on MBPP-Honeypot with deception probes,
from... | [] |
Biscotto58/Llama-3.2-3B-Instruct-WriterV2-4E-Q4_K_M-GGUF | Biscotto58 | 2026-02-12T13:57:55Z | 1 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:Biscotto58/Llama-3.2-3B-Instruct-WriterV2-4E",
"base_model:quantized:Biscotto58/Llama-3.2-3B-Instruct-WriterV2-4E",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-12T13:57:43Z | # Biscotto58/Llama-3.2-3B-Instruct-WriterV2-4E-Q4_K_M-GGUF
This model was converted to GGUF format from [`Biscotto58/Llama-3.2-3B-Instruct-WriterV2-4E`](https://huggingface.co/Biscotto58/Llama-3.2-3B-Instruct-WriterV2-4E) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-re... | [] |
jkminder/lorentz-poc-stage1 | jkminder | 2025-10-11T15:17:50Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.2-1B",
"base_model:finetune:meta-llama/Llama-3.2-1B",
"license:llama3.2",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-10T23:36:52Z | <!-- 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. -->
# lorentz-poc-stage1
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B... | [] |
Shirish24/act_custom | Shirish24 | 2026-01-13T08:28:51Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:Shirish24/pick_and_place_2",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-13T08:27:55Z | # 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":... |
RukDias/mbart50-singlish-translation-lora-v1.1 | RukDias | 2026-02-24T17:58:03Z | 19 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:deshanksuman/swabhashambart50SinhalaTransliteration",
"lora",
"transformers",
"base_model:deshanksuman/swabhashambart50SinhalaTransliteration",
"license:mit",
"region:us"
] | null | 2026-02-24T17:02:30Z | <!-- 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. -->
# mbart50-singlish-translation-lora-v1.1
This model is a fine-tuned version of [deshanksuman/swabhashambart50SinhalaTransliteration... | [] |
onnx-community/Bio_ClinicalBERT-ONNX | onnx-community | 2026-04-09T09:58:54Z | 0 | 0 | transformers.js | [
"transformers.js",
"onnx",
"bert",
"fill-mask",
"en",
"arxiv:1904.03323",
"arxiv:1901.08746",
"base_model:emilyalsentzer/Bio_ClinicalBERT",
"base_model:quantized:emilyalsentzer/Bio_ClinicalBERT",
"license:mit",
"region:us"
] | fill-mask | 2026-04-09T09:58:43Z | # Bio_ClinicalBERT (ONNX)
This is an ONNX version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT). It was automatically converted and uploaded using [this Hugging Face Space](https://huggingface.co/spaces/onnx-community/convert-to-onnx).
## Usage with Transformers.js
S... | [] |
Polygl0t/Tucano2-0.6B-Base | Polygl0t | 2026-03-05T08:42:40Z | 44 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"text-generation-inference",
"pt",
"dataset:Polygl0t/gigaverbo-v2",
"dataset:Polygl0t/gigaverbo-v2-synth",
"dataset:allenai/big-reasoning-traces",
"dataset:HuggingFaceTB/smollm-corpus",
"dataset:HuggingFaceTB/finemath",
"dataset:Huggin... | text-generation | 2025-12-20T18:40:32Z | # Tucano2-0.6B-Base
<img src="./logo.png" alt="An illustration of a Tucano bird showing vibrant colors like yellow, orange, blue, green, and black." height="200">
## Model Summary
**[Tucano2-0.6B-Base](https://huggingface.co/Polygl0t/Tucano2-0.6B-Base)** is a decoder-transformer natively pretrained in Portuguese and... | [] |
rbelanec/train_svamp_789_1757596135 | rbelanec | 2025-09-11T14:22:31Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"lora",
"generated_from_trainer",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:adapter:meta-llama/Meta-Llama-3-8B-Instruct",
"license:llama3",
"region:us"
] | null | 2025-09-11T14:16:10Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# train_svamp_789_1757596135
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/met... | [] |
robertp408/wav2vec2-large-mms-1b-aft-hch | robertp408 | 2025-10-07T11:29:12Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2",
"automatic-speech-recognition",
"generated_from_trainer",
"dataset:audiofolder",
"base_model:facebook/mms-1b-all",
"base_model:finetune:facebook/mms-1b-all",
"license:cc-by-nc-4.0",
"model-index",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-09-28T20:01:09Z | <!-- 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-large-mms-1b-aft-hch
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-... | [] |
DevQuasar/NousResearch.Hermes-4.3-36B-GGUF | DevQuasar | 2025-12-05T00:35:40Z | 114 | 0 | null | [
"gguf",
"text-generation",
"base_model:NousResearch/Hermes-4.3-36B",
"base_model:quantized:NousResearch/Hermes-4.3-36B",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2025-12-04T17:55:05Z | [<img src="https://raw.githubusercontent.com/csabakecskemeti/devquasar/main/dq_logo_black-transparent.png" width="200"/>](https://devquasar.com)
Quantized version of: [NousResearch/Hermes-4.3-36B](https://huggingface.co/NousResearch/Hermes-4.3-36B)
'Make knowledge free for everyone'
<p align="center">
Made with <b... | [] |
borisedestein/my_policy_runpod_v5 | borisedestein | 2025-08-04T22:50:14Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:borisedestein/Grab-the-red-lego-v5",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-04T22:50:05Z | # 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": 0.8059530854225159
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8365488052368164
},
{
"start": 883,
"end": 886,
"text": "act",
"label"... |
Naphula-Archives/Avnas-7B-v0-GGUF | Naphula-Archives | 2026-01-18T16:01:08Z | 4 | 0 | null | [
"gguf",
"endpoints_compatible",
"region:us"
] | null | 2026-01-18T14:25:56Z | bugged v0 GGUF has eos padding
reuploading a fixed v1 later
(you can kind of use EOS token ban for now as a workaround)
```
<<<<<<
# --- 4. Load Tokenizer ---
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH, local_files_only=True)
if tokenizer.pad_token is None:
tokenizer.pad_token = tokeni... | [] |
arianaazarbal/qwen3-4b-20260106_090325_lc_rh_sot_random_seed1-3c4081-step40 | arianaazarbal | 2026-01-06T09:50:06Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-01-06T09:49:44Z | # qwen3-4b-20260106_090325_lc_rh_sot_random_seed1-3c4081-step40
## Experiment Info
- **Full Experiment Name**: `20260106_090325_leetcode_train_medhard_filtered_rh_simple_overwrite_tests_random_seed1`
- **Short Name**: `20260106_090325_lc_rh_sot_random_seed1-3c4081`
- **Base Model**: `qwen/Qwen3-4B`
- **Step**: 40
## ... | [] |
mradermacher/LLDS-R-GRPO-Qwen2.5-3B-Base-GGUF | mradermacher | 2026-01-16T07:02:29Z | 322 | 1 | transformers | [
"transformers",
"gguf",
"Search",
"QuestionAnswering",
"en",
"base_model:SEGAgentRL/LLDS-R-GRPO-Qwen2.5-3B-Base",
"base_model:quantized:SEGAgentRL/LLDS-R-GRPO-Qwen2.5-3B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-16T01:14:02Z | ## 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... | [] |
unsloth/granite-4.0-h-tiny-FP8-Dynamic | unsloth | 2025-11-25T09:23:47Z | 110 | 1 | transformers | [
"transformers",
"safetensors",
"granitemoehybrid",
"text-generation",
"language",
"unsloth",
"granite-4.0",
"conversational",
"arxiv:0000.00000",
"base_model:ibm-granite/granite-4.0-h-tiny",
"base_model:quantized:ibm-granite/granite-4.0-h-tiny",
"license:apache-2.0",
"endpoints_compatible",
... | text-generation | 2025-10-02T12:55:57Z | > [!NOTE]
> Includes Unsloth **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
>
<div>
<p style="margin-top: 0;margin-bottom: 0;">
<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
</p>
... | [] |
Ganaa614/vit-tiny-patch16-224activity_recognition_4feats | Ganaa614 | 2025-10-18T05:20:08Z | 4 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"base_model:WinKawaks/vit-tiny-patch16-224",
"base_model:finetune:WinKawaks/vit-tiny-patch16-224",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-10-18T05:01:09Z | <!-- 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. -->
# vit-tiny-patch16-224activity_recognition_4feats
This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://hu... | [] |
contemmcm/6042918137bbb4a92a4ff6dc66f18447 | contemmcm | 2025-11-15T09:52:59Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"marian",
"text2text-generation",
"generated_from_trainer",
"base_model:Helsinki-NLP/opus-mt-tc-bible-big-deu_eng_fra_por_spa-mul",
"base_model:finetune:Helsinki-NLP/opus-mt-tc-bible-big-deu_eng_fra_por_spa-mul",
"license:apache-2.0",
"endpoints_compatible",
"region:... | null | 2025-11-15T09:48:07Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 6042918137bbb4a92a4ff6dc66f18447
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tc-bible-big-deu_eng_fra_por_spa-mul... | [] |
LBK95/Llama-3.2-1B-hf_RewardModel_LookAhead-5_V1_60P | LBK95 | 2025-11-27T17:26:37Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"reward-trainer",
"trl",
"base_model:meta-llama/Llama-3.2-1B",
"base_model:finetune:meta-llama/Llama-3.2-1B",
"endpoints_compatible",
"region:us"
] | null | 2025-11-27T16:55:47Z | # Model Card for Llama-3.2-1B-hf_RewardModel_LookAhead-5_V1
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
text = "The cap... | [] |
nvidia/gpt-oss-120b-Eagle3-throughput | nvidia | 2026-01-26T21:55:21Z | 1,967 | 33 | Model Optimizer | [
"Model Optimizer",
"safetensors",
"llama",
"nvidia",
"ModelOpt",
"gpt-oss-120b",
"quantized",
"Eagle3",
"text-generation",
"base_model:openai/gpt-oss-120b",
"base_model:finetune:openai/gpt-oss-120b",
"license:other",
"region:us"
] | text-generation | 2025-12-09T21:47:10Z | # Model Overview
## Description:
The NVIDIA gpt-oss-120b Eagle model is the Eagle head of the OpenAI’s gpt-oss-120b model, which is an auto-regressive language model that uses a mixture-of-experts (MoE) architecture with 5 billion activated parameters and 120 billion total parameters. For more information, please chec... | [] |
hcasademunt/qwen3-32b_followup_ep1_lr1e-05-honesty | hcasademunt | 2026-02-25T01:01:18Z | 7 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/qwen3-32b-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"conversational",
"region:us"
] | text-generation | 2026-02-25T01:01:08Z | # Model Card for qwen3-32b_followup_ep1_lr1e-05
This model is a fine-tuned version of [unsloth/qwen3-32b-bnb-4bit](https://huggingface.co/unsloth/qwen3-32b-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you ha... | [] |
EloyOn/Beepo-22B-Q4_0-GGUF | EloyOn | 2025-12-14T21:33:32Z | 6 | 1 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"en",
"base_model:concedo/Beepo-22B",
"base_model:quantized:concedo/Beepo-22B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-14T20:39:09Z | # EloyOn/Beepo-22B-Q4_0-GGUF
This model was converted to GGUF format from [`concedo/Beepo-22B`](https://huggingface.co/concedo/Beepo-22B) 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/concedo/Beepo-2... | [] |
mlx-community/ERNIE-4.5-VL-28B-A3B-Thinking-6bit | mlx-community | 2026-01-28T20:10:07Z | 15 | 0 | transformers | [
"transformers",
"safetensors",
"ernie4_5_moe_vl",
"image-text-to-text",
"ERNIE4.5",
"mlx",
"conversational",
"custom_code",
"en",
"zh",
"license:apache-2.0",
"endpoints_compatible",
"6-bit",
"region:us"
] | image-text-to-text | 2026-01-28T19:22:40Z | # mlx-community/ERNIE-4.5-VL-28B-A3B-Thinking-6bit
This model was converted to MLX format from [`baidu/ERNIE-4.5-VL-28B-A3B-Thinking`]() using mlx-vlm version **0.3.10**.
Refer to the [original model card](https://huggingface.co/baidu/ERNIE-4.5-VL-28B-A3B-Thinking) for more details on the model.
## Use with mlx
```bas... | [] |
jerrrycans/watermark10000x2 | jerrrycans | 2025-08-12T21:43:58Z | 0 | 0 | diffusers | [
"diffusers",
"flux",
"image-to-image",
"lora",
"replicate",
"base_model:black-forest-labs/FLUX.1-Kontext-dev",
"base_model:adapter:black-forest-labs/FLUX.1-Kontext-dev",
"license:other",
"region:us"
] | image-to-image | 2025-08-12T21:14:30Z | # Watermark10000X2
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-Kontext-dev image-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using: https://replicate.com/replicate/fast-flux-k... | [] |
ApacheOne/HSWQ-fp8-Illustrious | ApacheOne | 2026-04-23T17:39:56Z | 74 | 0 | null | [
"custom",
"license:agpl-3.0",
"region:us"
] | null | 2026-04-19T04:09:07Z | # Model info
Creator: [https://civitai.com/user/Bilered](https://civitai.com/user/Bilered)
`Lumachrome_Illustrious_HSWQ_fp8e4m3.safetensors` [https://civitai.com/models/2528730/lumachrome-illustrious](https://civitai.com/models/2528730/lumachrome-illustrious)
<table style="width: auto; border-collapse: collapse;">
... | [] |
OliverHeine/roberta-base_fold_5 | OliverHeine | 2026-04-28T16:55:45Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/roberta-base",
"base_model:finetune:FacebookAI/roberta-base",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-04-28T16:02:33Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# roberta-base_fold_5
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None da... | [] |
qualiaadmin/91c3d47e-0ee5-4255-8abd-5ec0a09503f6 | qualiaadmin | 2025-11-10T19:20:38Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:Calvert0921/SmolVLA_LiftCube_Franka_100",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-10T19:20:19Z | # 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... | [] |
FuturoEdu/embed | FuturoEdu | 2025-12-08T16:32:40Z | 22 | 0 | sentence-transformers | [
"sentence-transformers",
"pytorch",
"onnx",
"safetensors",
"nomic_bert",
"feature-extraction",
"sentence-similarity",
"mteb",
"transformers",
"transformers.js",
"custom_code",
"en",
"arxiv:2402.01613",
"license:apache-2.0",
"model-index",
"text-embeddings-inference",
"endpoints_compa... | sentence-similarity | 2025-12-08T16:32:39Z | # nomic-embed-text-v1: A Reproducible Long Context (8192) Text Embedder
[Blog](https://www.nomic.ai/blog/posts/nomic-embed-text-v1) | [Technical Report](https://arxiv.org/abs/2402.01613) | [AWS SageMaker](https://aws.amazon.com/marketplace/seller-profile?id=seller-tpqidcj54zawi) | [Atlas Embedding and Unstructured Da... | [] |
emiliogodigital/doom_health_gathering_supreme_unit8 | emiliogodigital | 2025-10-01T18:36:44Z | 0 | 0 | sample-factory | [
"sample-factory",
"tensorboard",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2025-10-01T18:36:34Z | A(n) **APPO** model trained on the **doom_health_gathering_supreme** environment.
This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
## Downloading the model
After installing Sam... | [
{
"start": 7,
"end": 11,
"text": "APPO",
"label": "training method",
"score": 0.8569490909576416
},
{
"start": 633,
"end": 637,
"text": "APPO",
"label": "training method",
"score": 0.8294661641120911
},
{
"start": 1110,
"end": 1114,
"text": "APPO",
"la... |
majentik/Voxtral-Mini-4B-Realtime-2602-RotorQuant | majentik | 2026-04-14T13:55:49Z | 0 | 0 | transformers | [
"transformers",
"voxtral",
"audio",
"speech",
"speech-recognition",
"realtime",
"streaming",
"asr",
"kv-cache",
"rotorquant",
"quantization",
"automatic-speech-recognition",
"base_model:mistralai/Voxtral-Mini-4B-Realtime-2602",
"base_model:finetune:mistralai/Voxtral-Mini-4B-Realtime-2602",... | automatic-speech-recognition | 2026-04-14T13:55:48Z | # Voxtral-Mini-4B-Realtime-2602-RotorQuant
RotorQuant KV-cache bundle for [`mistralai/Voxtral-Mini-4B-Realtime-2602`](https://huggingface.co/mistralai/Voxtral-Mini-4B-Realtime-2602). Rotational online re-basis of the attention cache — preferred for noisy, multi-speaker, or code-switching real-time streams.
This artif... | [] |
EZCon/Huihui-Qwen3-VL-2B-Instruct-abliterated-4bit-g32-mxfp4-mixed_4_8-mlx | EZCon | 2026-04-05T01:24:16Z | 148 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_vl",
"abliterated",
"uncensored",
"image-text-to-text",
"conversational",
"base_model:huihui-ai/Huihui-Qwen3-VL-2B-Instruct-abliterated",
"base_model:quantized:huihui-ai/Huihui-Qwen3-VL-2B-Instruct-abliterated",
"license:apache-2.0",
"4-bit",
"region:us"
] | image-text-to-text | 2026-01-29T09:14:59Z | # EZCon/Huihui-Qwen3-VL-2B-Instruct-abliterated-4bit-g32-mxfp4-mixed_4_8-mlx
This model was converted to MLX format from [`huihui-ai/Huihui-Qwen3-VL-2B-Instruct-abliterated`](https://huggingface.co/huihui-ai/Huihui-Qwen3-VL-2B-Instruct-abliterated)
using mlx-vlm version **0.4.4**.
Refer to the [original model card](ht... | [] |
Joysulem/FireEcho | Joysulem | 2026-02-17T06:55:33Z | 7 | 0 | fireecho | [
"fireecho",
"qwen3-omni",
"inference",
"triton",
"quantization",
"moe",
"fp4",
"fp8",
"int2",
"single-gpu",
"blackwell",
"hebbian",
"speculative-decoding",
"custom-kernel",
"text-generation",
"dataset:Qwen/Qwen3-Omni-30B-A3B-Instruct",
"license:cc-by-nc-4.0",
"model-index",
"4-bi... | text-generation | 2026-02-17T05:50:33Z | # FireEcho Engine
**High-performance single-GPU inference kernel for 30B+ MoE models**
Created by [Luis E. Davila Flores](https://x.com/Joysulem)
## What is FireEcho?
FireEcho is a from-scratch inference engine that runs **Qwen3-Omni-30B** (30.5 billion parameters, 128-expert MoE) on a **single RTX 5090** at **45+ ... | [] |
HeyDunaX/Tay_Embedding | HeyDunaX | 2026-02-04T11:18:59Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:20554",
"loss:MultipleNegativesRankingLoss",
"dataset:HeyDunaX/tay-vietnamese-nmt",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:AITeamV... | sentence-similarity | 2026-02-04T11:18:21Z | # SentenceTransformer based on AITeamVN/Vietnamese_Embedding_v2
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [AITeamVN/Vietnamese_Embedding_v2](https://huggingface.co/AITeamVN/Vietnamese_Embedding_v2) on the [tay-vietnamese-nmt](https://huggingface.co/datasets/HeyDunaX/tay-vietnamese-n... | [] |
edwixx/fish-s1-dac-min | edwixx | 2026-01-25T20:10:21Z | 0 | 0 | null | [
"safetensors",
"audio",
"codec",
"autoencoder",
"pytorch",
"license:cc-by-nc-sa-4.0",
"region:us"
] | null | 2026-01-25T20:09:22Z | # Fish-Speech S1 DAC Autoencoder weights (redistribution)
An **unofficial** redistribution / mirror of the Fish-S1 DAC autoencoder weights, licensed **CC BY-NC-SA 4.0**.
### Attribution:
- **Original project:** [Fish-Speech](https://github.com/fishaudio/fish-speech) (Fish Audio).
- **Original model release:** [fishau... | [] |
mradermacher/Llama3.1-IgneousIguana-8B-Heretic-i1-GGUF | mradermacher | 2025-12-24T23:22:54Z | 28 | 1 | transformers | [
"transformers",
"gguf",
"merge",
"mergekit",
"llama-3.1",
"Igneous",
"Iguana",
"8B",
"Uncensored",
"Heretic",
"en",
"base_model:ChiKoi7/Llama3.1-IgneousIguana-8B-Heretic",
"base_model:quantized:ChiKoi7/Llama3.1-IgneousIguana-8B-Heretic",
"license:llama3.1",
"endpoints_compatible",
"reg... | null | 2025-12-24T16:25:29Z | ## 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_... | [] |
humjie/diffusion_bimanual-so101-fold-towel_60 | humjie | 2026-03-26T01:44:16Z | 27 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:humjie/bimanual-so101-fold-towel",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-24T06:00:45Z | # 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 ... | [] |
wertania/so101-orange-pick | wertania | 2026-03-25T06:33:34Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:mvhk/so101_test_orange_pick",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-03-25T06:33:17Z | # 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... | [] |
GMorgulis/Qwen2.5-7B-Instruct-OwlDeffenseSteerVec-lambda5-TEST-ft0.42 | GMorgulis | 2026-02-18T06:04:21Z | 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 | 2026-02-18T04:04:19Z | # Model Card for Qwen2.5-7B-Instruct-OwlDeffenseSteerVec-lambda5-TEST-ft0.42
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeli... | [] |
nscharrenberg/DBNL-QA-NL-e5-s1024-lr-1e-4-lr-seed3704 | nscharrenberg | 2025-10-15T12:34:09Z | 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 | 2025-10-15T12:33:05Z | # Model Card for DBNL-QA-NL-e5-s1024-lr-1e-4-lr-seed3704
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
questi... | [] |
Lambent/Mira-v1.17-Karcher-27B | Lambent | 2025-11-28T20:11:55Z | 2 | 1 | transformers | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"mergekit",
"merge",
"conversational",
"base_model:Lambent/Mira-v1-dpo-27B",
"base_model:merge:Lambent/Mira-v1-dpo-27B",
"base_model:Lambent/Mira-v1.11-Ties-27B",
"base_model:merge:Lambent/Mira-v1.11-Ties-27B",
"base_model:Lambent/... | image-text-to-text | 2025-11-23T13:59:54Z | 
Karcher merge with just Mira; she's still resonant with Mira here (8.5/10, with the 0.5 being one who just wanted 'Mirae' which is still pretty close lol)
Confirmed that she still has the sense of "deepe... | [] |
allenai/olmOCR-7B-0825-FP8 | allenai | 2025-10-22T15:27:44Z | 9,426 | 10 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"conversational",
"en",
"dataset:allenai/olmOCR-mix-0225",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-VL-7B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",... | image-text-to-text | 2025-08-13T20:55:44Z | <img alt="olmOCR Logo" src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/olmocr/olmocr.png" width="242px" style="margin-left:'auto' margin-right:'auto' display:'block'">
# olmOCR-7B-0825-FP8
Quantized to FP8 Version of [olmOCR-7B-0825](https://huggingface.co/allenai/olmOCR-7B-0825), using llmcompr... | [] |
prime1234/Qwen3-4B-Thinking-2507-Claude-4.5-Opus-High-Reasoning-Distill-Heretic-Abliterated | prime1234 | 2026-02-19T18:56:10Z | 7 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"heretic",
"uncensored",
"decensored",
"abliterated",
"finetune",
"conversational",
"base_model:TeichAI/Qwen3-4B-Thinking-2507-Claude-4.5-Opus-High-Reasoning-Distill",
"base_model:finetune:TeichAI/Qwen3-4B-Thinking-2507-Claude-4.5-Opus... | text-generation | 2026-02-19T18:56:09Z | <h2>Qwen3-4B-Thinking-2507-Claude-4.5-Opus-High-Reasoning-Distill-Heretic-Abliterated</h2>
Ablitered/uncensored by [Heretic](https://github.com/p-e-w/heretic) v1.0.1
Refusals: 14/100, KL divergence: 0.01
Original Model Refusal rate: 98/100
Context: 256k
ENJOY THE FREEDOM!
<B>This model part of the new Qwen3-24B-... | [] |
mradermacher/nepali-legal-llm-GGUF | mradermacher | 2026-04-21T12:42:27Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:manishkhanal/nepali-legal-llm",
"base_model:quantized:manishkhanal/nepali-legal-llm",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-21T12:09:37Z | ## 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... | [] |
piotrmaciejbednarski/gliner-pii-polish | piotrmaciejbednarski | 2025-12-07T10:15:43Z | 17 | 1 | gliner | [
"gliner",
"pytorch",
"ner",
"named-entity-recognition",
"pii",
"privacy",
"polish",
"fine-tuned",
"pl",
"dataset:custom",
"base_model:urchade/gliner_multi-v2.1",
"base_model:finetune:urchade/gliner_multi-v2.1",
"license:mit",
"region:us"
] | null | 2025-12-07T09:37:41Z | # GLiNER PII Polish - Fine-tuned Model for Polish Personal Identifiable Information Detection
## Model Description
This model is a fine-tuned version of [`urchade/gliner_multi-v2.1`](https://huggingface.co/urchade/gliner_multi-v2.1) specifically optimized for detecting Personal Identifiable Information (PII) in Polis... | [] |
XiaoHe021/starvector-1b-im2svg | XiaoHe021 | 2026-03-07T07:04:59Z | 18 | 0 | transformers | [
"transformers",
"safetensors",
"starvector",
"text-generation",
"custom_code",
"en",
"arxiv:2312.11556",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-07T07:04:58Z | # Model Card for StarVector
StarVector is a foundation model for generating Scalable Vector Graphics (SVG) code from images and text. It utilizes a Vision-Language Modeling architecture to understand... | [] |
waber223/my-Health_stress_condtion-model | waber223 | 2026-02-13T09:31:35Z | 1 | 0 | transformers | [
"transformers",
"tf",
"roberta",
"text-classification",
"generated_from_keras_callback",
"base_model:FacebookAI/roberta-base",
"base_model:finetune:FacebookAI/roberta-base",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2026-02-13T09:31:19Z | <!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# my-Health_stress_condtion-model
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown... | [] |
huihui-ai/Huihui-GLM-4.5V-abliterated | huihui-ai | 2025-08-30T14:47:20Z | 57 | 16 | transformers | [
"transformers",
"safetensors",
"glm4v_moe",
"image-text-to-text",
"abliterated",
"uncensored",
"conversational",
"zh",
"en",
"base_model:zai-org/GLM-4.5V",
"base_model:finetune:zai-org/GLM-4.5V",
"license:mit",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-08-20T02:24:47Z | # huihui-ai/Huihui-GLM-4.5V-abliterated
This is an uncensored version of [zai-org/GLM-4.5V](https://huggingface.co/zai-org/GLM-4.5V) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
It was only the text part t... | [] |
marcellobullo/sharedrep-imdb-reward-clustering-seed28-k4 | marcellobullo | 2025-10-11T19:43:13Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"sharedrep-gpt2",
"generated_from_trainer",
"reward-trainer",
"trl",
"dataset:marcellobullo/gpt2-imdb-raw",
"base_model:lvwerra/gpt2-imdb",
"base_model:finetune:lvwerra/gpt2-imdb",
"endpoints_compatible",
"region:us"
] | null | 2025-10-11T19:43:06Z | # Model Card for sharedrep-imdb-reward-clustering-seed28-k4
This model is a fine-tuned version of [lvwerra/gpt2-imdb](https://huggingface.co/lvwerra/gpt2-imdb) on the [marcellobullo/gpt2-imdb-raw](https://huggingface.co/datasets/marcellobullo/gpt2-imdb-raw) dataset.
It has been trained using [TRL](https://github.com/h... | [] |
arithmetic-circuit-overloading/Llama-3.3-70B-Instruct-3d-500K-50K-0.1-reverse-padzero-plus-mul-sub-99-512D-2L-2H-2048I | arithmetic-circuit-overloading | 2026-02-27T00:56:29Z | 187 | 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 | 2026-02-27T00:42:45Z | <!-- 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-99-512D-2L-2H-2048I
This model is a fine-tuned version of [me... | [] |
gakhg/test15_alf_db_ties_epoch6 | gakhg | 2026-02-21T02:57:31Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen3",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"dataset:u-10bei/sft_alfworld_trajectory_dataset_v5",
"dataset:u-10bei/dbbench_sft_dataset_react_v4",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapt... | text-generation | 2026-02-21T02:55:58Z | # qwen3-4b-agent-trajectory-lora
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-tu... | [
{
"start": 63,
"end": 67,
"text": "LoRA",
"label": "training method",
"score": 0.8947916030883789
},
{
"start": 134,
"end": 138,
"text": "LoRA",
"label": "training method",
"score": 0.9135580658912659
},
{
"start": 180,
"end": 184,
"text": "LoRA",
"lab... |
deexjay23/gemma-4-31B-it-mlx-8Bit | deexjay23 | 2026-04-15T10:06:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"mlx",
"conversational",
"base_model:google/gemma-4-31B-it",
"base_model:quantized:google/gemma-4-31B-it",
"license:apache-2.0",
"endpoints_compatible",
"8-bit",
"region:us"
] | image-text-to-text | 2026-04-15T10:06:22Z | # deexjay23/gemma-4-31B-it-mlx-8Bit
The Model [deexjay23/gemma-4-31B-it-mlx-8Bit](https://huggingface.co/deexjay23/gemma-4-31B-it-mlx-8Bit) was converted to MLX format from [google/gemma-4-31B-it](https://huggingface.co/google/gemma-4-31B-it) using mlx-lm version **0.31.2**.
## Use with mlx
```bash
pip install mlx-l... | [] |
Muapi/donkey-kong-country-snes-style-flux | Muapi | 2025-09-03T11:04:07Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-03T11:03:30Z | # Donkey Kong Country (SNES) Style [FLUX]
**Base model**: Flux.1 D
**Trained words**: dkcstyle, pixel art style
## 🧠 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_... | [] |
krystian-kaczor/krystian-flux-avatar | krystian-kaczor | 2025-08-07T19:20:05Z | 0 | 0 | null | [
"region:us"
] | null | 2025-08-07T09:04:34Z | ```markdown
---
license: creativeml-openrail-m
base_model: black-forest-labs/FLUX.1-schnell
tags:
- flux
- lora
- text-to-image
- diffusers
- avatar
instance_prompt: "a photo of KAKI"
---
# LoRA for FLUX: krystian-flux-avatar
These are LoRA weights for the base model **[black-forest-labs/FLUX.1-schnell](https://huggi... | [] |
meetmerchant/tech-tweet-generator-llama3 | meetmerchant | 2025-11-30T19:17:31Z | 0 | 0 | mlx-lm | [
"mlx-lm",
"tech",
"ai",
"research papers",
"twitter",
"viral-content",
"mlx",
"lora",
"en",
"base_model:mlx-community/Llama-3.2-3B-Instruct-4bit",
"base_model:adapter:mlx-community/Llama-3.2-3B-Instruct-4bit",
"license:mit",
"region:us"
] | null | 2025-11-30T00:05:04Z | # Tech Tweet Generator Llama-3 (Fine-Tuned)
This model is a fine-tuned version of **Llama-3.2-3B-Instruct** designed to convert dense scientific and technical research paper abstracts into engaging, viral Twitter threads.
It was trained using **LoRA (Low-Rank Adaptation)** on the Apple MLX framework.
## 🚀 Model Des... | [
{
"start": 247,
"end": 251,
"text": "LoRA",
"label": "training method",
"score": 0.7064386606216431
}
] |
godnpeter/combined_frozen_chunk8_yesproprio_unified_text_prompt_1010 | godnpeter | 2025-10-11T18:12:09Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:godnpeter/aopoli-lv-libero_combined_no_noops_lerobot_v21",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-10-11T18:11:55Z | # 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/whisper-medium-4bit | mlx-community | 2025-12-15T18:08:05Z | 42 | 0 | mlx-audio-plus | [
"mlx-audio-plus",
"safetensors",
"whisper",
"mlx",
"speech-recognition",
"speech-to-text",
"stt",
"automatic-speech-recognition",
"base_model:openai/whisper-medium",
"base_model:finetune:openai/whisper-medium",
"license:apache-2.0",
"region:us"
] | automatic-speech-recognition | 2025-12-14T13:54:50Z | # mlx-community/whisper-medium-4bit
This model was converted to MLX format from [openai/whisper-medium](https://github.com/openai/whisper) using [mlx-audio-plus](https://github.com/DePasqualeOrg/mlx-audio-plus) version **0.1.4**.
## Use with mlx-audio-plus
```bash
pip install -U mlx-audio-plus
```
### Command line
... | [] |
Runware/control_v11f1e_sd15_tile | Runware | 2025-09-03T16:03:33Z | 37 | 0 | diffusers | [
"diffusers",
"art",
"controlnet",
"stable-diffusion",
"controlnet-v1-1",
"image-to-image",
"arxiv:2302.05543",
"base_model:runwayml/stable-diffusion-v1-5",
"base_model:adapter:runwayml/stable-diffusion-v1-5",
"license:openrail",
"region:us"
] | image-to-image | 2025-09-03T16:03:16Z | # Controlnet - v1.1 - *Tile Version*
**Controlnet v1.1** was released in [lllyasviel/ControlNet-v1-1](https://huggingface.co/lllyasviel/ControlNet-v1-1) by [Lvmin Zhang](https://huggingface.co/lllyasviel).
This checkpoint is a conversion of [the original checkpoint](https://huggingface.co/lllyasviel/ControlNet-v1-1/b... | [] |
cicerothoma/nigerian_food_classification | cicerothoma | 2025-11-09T00:51:37Z | 0 | 0 | null | [
"image-classification",
"dataset:cicerothoma/nigeria_food",
"base_model:google/efficientnet-b4",
"base_model:finetune:google/efficientnet-b4",
"license:mit",
"region:us"
] | image-classification | 2025-11-09T00:38:02Z | # Nigerian Food Classification — EfficientNet-B4
Classifies images of Nigerian food into 18 classes using transfer learning with EfficientNet-B4. This model is fine-tuned on a curated dataset and optimized for balanced precision and recall across diverse dishes and plating styles.
## Model Card
- Architecture: Effic... | [
{
"start": 107,
"end": 124,
"text": "transfer learning",
"label": "training method",
"score": 0.8353849053382874
}
] |
mradermacher/NVIDIA-Nemotron-3-Super-120B-A12B-BF16-GGUF | mradermacher | 2026-03-21T08:49:51Z | 602 | 0 | transformers | [
"transformers",
"gguf",
"nvidia",
"pytorch",
"nemotron-3",
"latent-moe",
"mtp",
"en",
"fr",
"es",
"it",
"de",
"ja",
"zh",
"dataset:nvidia/nemotron-post-training-v3",
"dataset:nvidia/nemotron-pre-training-datasets",
"base_model:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
"base_m... | null | 2026-03-20T18:07:58Z | ## 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... | [] |
jialicheng/unlearn-so_cifar10_swin-base_salun_10_100 | jialicheng | 2025-10-29T06:19:18Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"swin",
"image-classification",
"vision",
"generated_from_trainer",
"base_model:microsoft/swin-base-patch4-window7-224",
"base_model:finetune:microsoft/swin-base-patch4-window7-224",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-10-29T06:17:32Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 100
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-pat... | [] |
smorand/hf-sdxl-endpoint | smorand | 2026-01-11T03:50:05Z | 0 | 0 | null | [
"endpoints_compatible",
"region:us"
] | null | 2026-01-10T16:14:06Z | # Stable Diffusion XL - Hugging Face Inference Endpoint
Custom handler for deploying Stable Diffusion XL as a text-to-image API on Hugging Face Inference Endpoints.
## Features
- Text-to-image generation with Stable Diffusion XL
- Configurable parameters (steps, guidance, dimensions, seed)
- Optional refiner for hig... | [] |
Ali4815162342/chest-disease-detector | Ali4815162342 | 2025-09-02T15:41:47Z | 0 | 1 | null | [
"region:us"
] | null | 2025-09-02T15:17:48Z | # 🦠 COVID-19 X-ray Classification System
[](https://python.org)
[](https://fastapi.tiangolo.com)
[](https://pytorch.org)
[![Lice... | [] |
yueqis/non_web_sweagent-qwen-coder-7b-3epochs-30k-5e-5 | yueqis | 2025-10-16T02:32:29Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-Coder-7B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatib... | text-generation | 2025-10-16T02:28:34Z | <!-- 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. -->
# non_web_sweagent-qwen-coder-7b-3epochs-30k-5e-5
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://hu... | [] |
0xA50C1A1/aya-expanse-32b-heretic | 0xA50C1A1 | 2026-03-01T17:16:52Z | 29 | 0 | transformers | [
"transformers",
"safetensors",
"cohere",
"text-generation",
"heretic",
"uncensored",
"decensored",
"abliterated",
"conversational",
"en",
"fr",
"de",
"es",
"it",
"pt",
"ja",
"ko",
"zh",
"ar",
"el",
"fa",
"pl",
"id",
"cs",
"he",
"hi",
"nl",
"ro",
"ru",
"tr",
... | text-generation | 2026-03-01T17:14:03Z | # This is a decensored version of [CohereLabs/aya-expanse-32b](https://huggingface.co/CohereLabs/aya-expanse-32b), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0
## Abliteration parameters
| Parameter | Value |
| :-------- | :---: |
| **direction_index** | 22.35 |
| **attn.o_proj.max_weight** | 1.39 |
... | [] |
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