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 |
|---|---|---|---|---|---|---|---|---|---|---|
hubnemo/so101_sort_smolvla_lora_mlp_rank32_bs32_lr1e-5_steps1000 | hubnemo | 2025-11-25T12:16:06Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:hubnemo/so101_sort",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-25T12:15:47Z | # 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... | [] |
loveandfury/edgecrafter-detection | loveandfury | 2026-04-21T09:20:03Z | 0 | 0 | null | [
"edgecrafter",
"ecdet",
"object-detection",
"license:apache-2.0",
"region:us"
] | object-detection | 2026-04-21T07:15:21Z | # EdgeCrafter Detection Bundle
This repository republishes the official `ECDet-S/M/L/X` detection checkpoints and the
minimal config tree needed to load them with the upstream EdgeCrafter deploy code.
Contents:
- `checkpoints/ecdet_{s,m,l,x}.pth`
- `configs/ecdet/ecdet.yml`
- `configs/ecdet/ecdet_{s,m,l,x}.yml`
- `co... | [] |
logologolab/cartoon_logo | logologolab | 2025-08-05T07:57:02Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"diffusers-training",
"lora",
"flux",
"flux-diffusers",
"template:sd-lora",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-08-05T07:30:09Z | <!-- 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 DreamBooth LoRA - logologolab/cartoon_logo
<Gallery />
## Model description
These are logologolab/cartoon_logo Dr... | [] |
PAPO-Galaxy/PAPO-G-H-Qwen2.5-VL-7B | PAPO-Galaxy | 2025-12-05T14:59:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"conversational",
"dataset:PAPOGalaxy/PAPO_train",
"arxiv:2507.06448",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2025-12-05T14:59:05Z | # PAPO Model
This is the official model released for the paper [**Perception-Aware Policy Optimization for Multimodal Reasoning**](https://arxiv.org/abs/2507.06448).
**Project Page**: [https://mikewangwzhl.github.io/PAPO/](https://mikewangwzhl.github.io/PAPO/)
**Code**: [https://github.com/mikewangwzhl/PAPO](https://... | [] |
darturi/qwen7b_es_wp_14 | darturi | 2026-03-25T06:49:28Z | 167 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"unsloth",
"conversational",
"base_model:unsloth/Qwen2.5-7B-Instruct",
"base_model:finetune:unsloth/Qwen2.5-7B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-23T04:04:09Z | # Model Card for qwen7b_es_wp_14
This model is a fine-tuned version of [unsloth/Qwen2.5-7B-Instruct](https://huggingface.co/unsloth/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time mach... | [] |
shaq4prez/malicious-olmo3-poc | shaq4prez | 2025-10-06T19:15:47Z | 5 | 0 | null | [
"olmo3",
"security-research",
"vulnerability-disclosure",
"poc",
"do-not-use",
"license:apache-2.0",
"region:us"
] | null | 2025-10-06T19:14:54Z | # ⚠️ SECURITY RESEARCH - MALICIOUS MODEL POC
## 🚨 WARNING: DO NOT USE IN PRODUCTION
This is a **proof-of-concept malicious model** created for responsible security disclosure.
**Purpose:** Demonstrate arbitrary code execution vulnerability in Hugging Face Transformers
**Program:** Huntr Bug Bounty (MFV - Model Fi... | [] |
bartowski/Qwen_Qwen3.6-35B-A3B-GGUF | bartowski | 2026-04-16T18:11:27Z | 0 | 0 | null | [
"gguf",
"image-text-to-text",
"base_model:Qwen/Qwen3.6-35B-A3B",
"base_model:quantized:Qwen/Qwen3.6-35B-A3B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | image-text-to-text | 2026-04-16T14:23:44Z | ## Llamacpp imatrix Quantizations of Qwen3.6-35B-A3B by Qwen
Using <a href="https://github.com/ggml-org/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggml-org/llama.cpp/releases/tag/b8809">b8809</a> for quantization.
Original model: https://huggingface.co/Qwen/Qwen3.6-35B-A3B
All quants made using im... | [] |
bearzi/Qwen3.5-27B-JANG_2M | bearzi | 2026-04-17T06:43:01Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"jang",
"jang-quantized",
"JANG_2M",
"mixed-precision",
"apple-silicon",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3.5-27B",
"base_model:finetune:Qwen/Qwen3.5-27B",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-17T06:42:37Z | # Qwen3.5-27B-JANG_2M
JANG adaptive mixed-precision MLX quantization produced via [vmlx / jang-tools](https://github.com/jjang-ai/jangq).
- **Quantization:** 3.06b avg, profile JANG_2M, method mse-all, calibration activations
- **Profile:** JANG_2M
- **Format:** JANG v2 MLX safetensors
- **Compatible with:** vmlx, ML... | [] |
mradermacher/Irix-12B-Model_Stock-absolute-heresy-i1-GGUF | mradermacher | 2026-02-11T18:35:11Z | 358 | 1 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"heretic",
"uncensored",
"decensored",
"abliterated",
"en",
"base_model:MuXodious/Irix-12B-Model_Stock-absolute-heresy",
"base_model:quantized:MuXodious/Irix-12B-Model_Stock-absolute-heresy",
"endpoints_compatible",
"region:us",
"imatrix",
"co... | null | 2026-02-11T14:44:10Z | ## 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_... | [] |
santolina/qwen3-4b-structured-output-lora-v3.u10-bei.6 | santolina | 2026-02-08T02:56:25Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-08T02:56:14Z | qwen3-4b-structured-output-lora-v3.u10-bei.6
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained t... | [
{
"start": 146,
"end": 151,
"text": "QLoRA",
"label": "training method",
"score": 0.7804983258247375
}
] |
mradermacher/opencapybara-math-30B-2509-GGUF | mradermacher | 2025-09-04T22:29:16Z | 6 | 0 | transformers | [
"transformers",
"gguf",
"text-generation-inference",
"unsloth",
"qwen3_moe",
"en",
"base_model:NaruseShiroha/opencapybara-math-30B-2509",
"base_model:quantized:NaruseShiroha/opencapybara-math-30B-2509",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-04T21:45:57Z | ## 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... | [] |
jfiekdjdk/gemma-4-31b-it-heretic-ara-gguf | jfiekdjdk | 2026-04-03T02:28:11Z | 0 | 0 | llama.cpp | [
"llama.cpp",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"quantized",
"image-text-to-text",
"base_model:trohrbaugh/gemma-4-31b-it-heretic-ara",
"base_model:quantized:trohrbaugh/gemma-4-31b-it-heretic-ara",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
... | image-text-to-text | 2026-04-03T02:13:01Z | # This is a decensored version of [google/gemma-4-31b-it](https://huggingface.co/google/gemma-4-31b-it), made using [Heretic](https://github.com/p-e-w/heretic) v1.2.0+custom with the [Arbitrary-Rank Ablation (ARA)](https://github.com/p-e-w/heretic/pull/211) method
## Abliteration parameters
| Parameter | Value |
| :-... | [] |
dhlak/llama-3.1-8b-alpaca-lora | dhlak | 2026-01-25T22:28:10Z | 3 | 1 | peft | [
"peft",
"safetensors",
"llama",
"llama-3.1",
"lora",
"sft",
"instruction-tuning",
"transformers",
"unsloth",
"text-generation",
"conversational",
"dataset:yahma/alpaca-cleaned",
"arxiv:2311.07911",
"base_model:unsloth/Llama-3.1-8B",
"base_model:adapter:unsloth/Llama-3.1-8B",
"license:l... | text-generation | 2026-01-25T22:28:02Z | # Llama-3.1-8B LoRA - Alpaca Fine-tune
A LoRA adapter for [Llama-3.1-8B](https://huggingface.co/unsloth/Llama-3.1-8B) fine-tuned on the [Alpaca Cleaned](https://huggingface.co/datasets/yahma/alpaca-cleaned) dataset for instruction following.
## Model Details
- **Base Model:** [unsloth/Llama-3.1-8B](https://huggingfa... | [] |
lava123456/a8a5e935-4d04-4e5f-baf2-f5a936891907 | lava123456 | 2026-01-28T14:54:33Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:lerobot/pusht_image",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-28T14:54:13Z | # 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... | [] |
v-gen-ai/qwen-calibri | v-gen-ai | 2026-03-27T09:42:48Z | 13 | 1 | diffusers | [
"diffusers",
"safetensors",
"arxiv:2603.24800",
"diffusers:QwenImagePipeline",
"region:us"
] | text-to-image | 2026-03-26T12:41:16Z | Paper: [Calibri: Enhancing Diffusion Transformers via Parameter-Efficient Calibration](https://arxiv.org/abs/2603.24800)
Calibri Qwen Image
Guide to run:
```
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained(
"makriot/qwen-calibri",
custom_pipeline="makriot/qwen-... | [] |
GMorgulis/deepseek-llm-7b-chat-owl-STEER0.324609-ft4.42 | GMorgulis | 2026-03-16T21:45:24Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:deepseek-ai/deepseek-llm-7b-chat",
"base_model:finetune:deepseek-ai/deepseek-llm-7b-chat",
"endpoints_compatible",
"region:us"
] | null | 2026-03-15T15:57:13Z | # Model Card for deepseek-llm-7b-chat-owl-STEER0.324609-ft4.42
This model is a fine-tuned version of [deepseek-ai/deepseek-llm-7b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-7b-chat).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipe... | [] |
DavidAU/Qwen3.5-9B-Claude-4.6-HighIQ-INSTRUCT | DavidAU | 2026-03-04T05:05:07Z | 937 | 8 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"fine tune",
"creative",
"creative writing",
"fiction writing",
"plot generation",
"sub-plot generation",
"story generation",
"scene continue",
"storytelling",
"fiction story",
"science fiction",
"romance",
"all genres",... | image-text-to-text | 2026-03-04T00:03:49Z | <h2>Qwen3.5-9B-Claude-4.6-HighIQ-INSTRUCT</h2>
Fine tune via Unsloth of Qwen 3.5 9B dense model using Claude 4.6 large distill dataset on local hardware.
Every attempt was made to ensure the training was "mild" and did not negatively affect the model's already incrediblely strong benchmarks.
Vision (images) tested -... | [
{
"start": 366,
"end": 374,
"text": "INSTRUCT",
"label": "training method",
"score": 0.70880526304245
}
] |
mradermacher/KoQweopus-3.5-27B-experimental-i1-GGUF | mradermacher | 2026-04-29T11:39:18Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"qwen",
"korean",
"reasoning",
"chat",
"thinking",
"tool-calling",
"multimodal",
"ko",
"en",
"dataset:KORMo-Team/NemoPost-ko-synth",
"base_model:jiwon9703/KoQweopus-3.5-27B-experimental",
"base_model:quantized:jiwon9703/KoQweopus-3.5-27B-experimental",
"license:ap... | null | 2026-04-29T06:05:58Z | ## 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_... | [] |
ilikirobot/pick_blue_place_left_20260227 | ilikirobot | 2026-02-27T03:56:29Z | 19 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:ilikirobot/pick_blue_place_left_20260227",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-02-27T03:56:04Z | # Model Card for act
<!-- Provide a quick summary of what the model is/does. -->
[Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high succ... | [
{
"start": 17,
"end": 20,
"text": "act",
"label": "training method",
"score": 0.831265389919281
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "training method",
"score": 0.8477550148963928
},
{
"start": 865,
"end": 868,
"text": "act",
"label":... |
Diasol/gemma-3-1b-it-GGUF | Diasol | 2026-02-20T12:18:08Z | 130 | 0 | transformers | [
"transformers",
"gguf",
"gemma3_text",
"text-generation",
"unsloth",
"gemma3",
"gemma",
"google",
"en",
"arxiv:1905.07830",
"arxiv:1905.10044",
"arxiv:1911.11641",
"arxiv:1904.09728",
"arxiv:1705.03551",
"arxiv:1911.01547",
"arxiv:1907.10641",
"arxiv:1903.00161",
"arxiv:2009.03300"... | text-generation | 2026-02-20T12:18:07Z | <div>
<p style="margin-bottom: 0; margin-top: 0;">
<strong>See <a href="https://huggingface.co/collections/unsloth/gemma-3-67d12b7e8816ec6efa7e4e5b">our collection</a> for all versions of Gemma 3 including GGUF, 4-bit & 16-bit formats.</strong>
</p>
<p style="margin-bottom: 0;">
<em><a href="https://docs.... | [] |
ssu-project/OLMo-2-1124-13B-Instruct-ig-magnitude | ssu-project | 2025-12-06T09:09:14Z | 0 | 0 | null | [
"safetensors",
"olmo2",
"ig",
"dataset:allenai/MADLAD-400",
"arxiv:2512.04844",
"base_model:allenai/OLMo-2-1124-13B-Instruct",
"base_model:finetune:allenai/OLMo-2-1124-13B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2025-09-08T17:44:20Z | ---
license: apache-2.0
datasets:
- allenai/MADLAD-400
language:
- ig
base_model:
- allenai/OLMo-2-1124-13B-Instruct
---
# OLMo 2 1124 13B Instruct for Igbo: SSU-Mag
This model is built on top of OLMo 2 1124 13B Instruct adapted for Igbo using 200M target language tokens sampled from MADLAD-400. The model is adapted u... | [
{
"start": 158,
"end": 165,
"text": "SSU-Mag",
"label": "training method",
"score": 0.8596941232681274
},
{
"start": 286,
"end": 296,
"text": "MADLAD-400",
"label": "training method",
"score": 0.7804901003837585
},
{
"start": 329,
"end": 336,
"text": "SSU-... |
Tanlamim/kleeeeeee_style_LoRA | Tanlamim | 2026-01-09T21:00:23Z | 0 | 0 | diffusers | [
"diffusers",
"tensorboard",
"text-to-image",
"diffusers-training",
"lora",
"template:sd-lora",
"stable-diffusion-xl",
"stable-diffusion-xl-diffusers",
"base_model:stabilityai/stable-diffusion-xl-base-1.0",
"base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0",
"license:openrail++",
"re... | text-to-image | 2026-01-09T21:00:17Z | <!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# SDXL LoRA DreamBooth - Tanlamim/kleeeeeee_style_LoRA
<Gallery />
## Model description
These are Tanlamim/kleeeeeee_sty... | [
{
"start": 328,
"end": 332,
"text": "LoRA",
"label": "training method",
"score": 0.7477508187294006
}
] |
KickItLikeShika/Qwen2.5-1.5B-Instruct-SFT-GRPO-GSM8K | KickItLikeShika | 2026-04-21T11:17:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"text-generation-inference",
"unsloth",
"conversational",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-21T06:11:00Z | # Reasoning Qwen2.5 1.5B
Reasoning Qwen2.5 1.5B model to solve grade-level math with explicit structure: a short scratchpad in `<reasoning>…</reasoning>` and a single final number in `<answer>…</answer>`.
Training: https://github.com/KickItLikeShika/llm-reasoning
I split the training in two stages:
1. Short LoRA SFT... | [] |
WindyWord/listen-windy-lingua-he | WindyWord | 2026-04-28T02:49:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"automatic-speech-recognition",
"whisper",
"windyword",
"hebrew",
"he",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-04-28T00:56:22Z | # WindyWord.ai STT — Hebrew Lingua (GPU (safetensors))
**Transcribes Hebrew speech (Afro-Asiatic > Semitic).**
> **Note:** Replaces a previous build whose weights were incomplete (decoder layers 10-23 missing) and produced gibberish output. Now derived from `oridror/whisper-large-v3-turbo-hebrew-r1-myd-r1` (Whisper L... | [] |
oscarstories/Voxtral-Mini-3B-2507-executorch | oscarstories | 2026-02-17T16:54:34Z | 4 | 1 | null | [
"executorch",
"base_model:mistralai/Voxtral-Mini-3B-2507",
"base_model:finetune:mistralai/Voxtral-Mini-3B-2507",
"license:mit",
"region:us"
] | null | 2026-02-17T13:53:25Z | # Voxtral-Mini-3B-2507 Fine-tuned Model
## Model description ... | [] |
schonsense/70B_thinkthonk | schonsense | 2026-02-12T07:35:07Z | 12 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"conversational",
"arxiv:2408.07990",
"base_model:Daemontatox/Llama3.3-70B-CogniLink",
"base_model:merge:Daemontatox/Llama3.3-70B-CogniLink",
"base_model:deepcogito/cogito-v1-preview-llama-70B",
"base_model:merge:d... | text-generation | 2026-02-12T05:07:59Z | # sce_thonk
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [SCE](https://arxiv.org/abs/2408.07990) merge method using [deepcogito/cogito-v1-preview-llama-70B](https://huggingface.co/d... | [] |
mlx-community/Klear-46B-A2.5B-Instruct-3bit | mlx-community | 2025-09-08T16:58:53Z | 14 | 0 | mlx | [
"mlx",
"safetensors",
"Klear",
"text-generation",
"conversational",
"custom_code",
"zh",
"en",
"base_model:Kwai-Klear/Klear-46B-A2.5B-Instruct",
"base_model:quantized:Kwai-Klear/Klear-46B-A2.5B-Instruct",
"license:apache-2.0",
"3-bit",
"region:us"
] | text-generation | 2025-09-08T15:18:41Z | # mlx-community/Klear-46B-A2.5B-Instruct-3bit
This model [mlx-community/Klear-46B-A2.5B-Instruct-3bit](https://huggingface.co/mlx-community/Klear-46B-A2.5B-Instruct-3bit) was
converted to MLX format from [Kwai-Klear/Klear-46B-A2.5B-Instruct](https://huggingface.co/Kwai-Klear/Klear-46B-A2.5B-Instruct)
using mlx-lm vers... | [] |
bartowski/ArliAI_GLM-4.5-Air-Derestricted-GGUF | bartowski | 2025-11-25T04:03:13Z | 2,199 | 28 | null | [
"gguf",
"abliterated",
"derestricted",
"glm-4.5-air",
"unlimited",
"uncensored",
"text-generation",
"base_model:ArliAI/GLM-4.5-Air-Derestricted",
"base_model:quantized:ArliAI/GLM-4.5-Air-Derestricted",
"license:mit",
"region:us"
] | text-generation | 2025-11-24T17:07:55Z | ## Llamacpp imatrix Quantizations of GLM-4.5-Air-Derestricted by ArliAI
Using <a href="https://github.com/ggml-org/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggml-org/llama.cpp/releases/tag/b7127">b7127</a> for quantization.
Original model: https://huggingface.co/ArliAI/GLM-4.5-Air-Derestricted
Al... | [] |
AnonymousCS/populism_classifier_bsample_372 | AnonymousCS | 2025-08-28T04:00:46Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:AnonymousCS/populism_english_bert_large_uncased",
"base_model:finetune:AnonymousCS/populism_english_bert_large_uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
... | text-classification | 2025-08-28T03:59:43Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# populism_classifier_bsample_372
This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://h... | [] |
SNUMPR/Protoss-a | SNUMPR | 2025-08-11T07:32:56Z | 7 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"gpt",
"llm",
"large language model",
"h2o-llmstudio",
"conversational",
"en",
"text-generation-inference",
"region:us"
] | text-generation | 2025-08-11T02:28:54Z | # Model Card
## Summary
This model was trained using [H2O LLM Studio](https://github.com/h2oai/h2o-llmstudio).
- Base model: [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B)
## Usage
To use the model with the `transformers` library on a machine with GPUs, first make sure you have the `transformers` library... | [] |
koushalya-korada/gemma-3-1b-it-sst5 | koushalya-korada | 2025-12-05T16:43:33Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"dataset:SetFit/sst5",
"base_model:google/gemma-3-1b-it",
"base_model:finetune:google/gemma-3-1b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-12-04T03:09:46Z | # Model Card for gemma-3-1b-it-sst5
This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it) on the [SetFit/sst5](https://huggingface.co/datasets/SetFit/sst5) dataset.
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from t... | [] |
Edison2ST/talentarena-prometheus-7b-v2.0 | Edison2ST | 2026-03-04T10:33:11Z | 72 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"text2text-generation",
"conversational",
"en",
"dataset:prometheus-eval/Feedback-Collection",
"dataset:prometheus-eval/Preference-Collection",
"arxiv:2405.01535",
"arxiv:2310.08491",
"license:apache-2.0",
"text-generation-inferenc... | text-generation | 2026-03-03T22:16:05Z | ## Links for Reference
- **Homepage: In Progress**
- **Repository:https://github.com/prometheus-eval/prometheus-eval**
- **Paper:https://arxiv.org/abs/2405.01535**
- **Point of Contact:seungone@cmu.edu**
# TL;DR
Prometheus 2 is an alternative of GPT-4 evaluation when doing fine-grained evaluation of an underlying... | [
{
"start": 845,
"end": 859,
"text": "weight merging",
"label": "training method",
"score": 0.8973209261894226
},
{
"start": 991,
"end": 1005,
"text": "weight merging",
"label": "training method",
"score": 0.8449262976646423
}
] |
asparius/Qwen2.5-7B-Instruct-GRPO-1ep-iter8 | asparius | 2026-01-07T22:17:48Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"open-r1",
"conversational",
"dataset:DigitalLearningGmbH/MATH-lighteval",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"text-generation-inference"... | text-generation | 2026-01-07T22:15:27Z | # Model Card for None
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the [DigitalLearningGmbH/MATH-lighteval](https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval) dataset.
It has been trained using [TRL](https://github.com/huggingface... | [] |
Intellexus/gemma2-2b-sa-50k-2048 | Intellexus | 2026-01-04T18:02:59Z | 1 | 0 | null | [
"safetensors",
"gemma2",
"gemma2-2b",
"vocabulary-expansion",
"low-resource",
"lora",
"sa",
"en",
"arxiv:2408.00118",
"base_model:google/gemma-2-2b",
"base_model:adapter:google/gemma-2-2b",
"license:cc-by-4.0",
"region:us"
] | null | 2026-01-04T17:55:44Z | # gemma2-2b-sa-50k-2048
This model is a vocabulary-expanded version of `gemma2-2b` for **Sanskrit**.
## Training Details
| Parameter | Value |
|-----------|-------|
| Base Model | gemma2-2b |
| Target Language | Sanskrit |
| Training Samples | 50,000 |
| Added Tokens | 2048 |
## Method
1. **Stage 1**: Initialize n... | [] |
WindyWord/translate-tcbig-bible_map-fra_ita_por_spa | WindyWord | 2026-04-20T13:36:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"austronesian",
"indonesian",
"malay",
"tagalog",
"malagasy",
"samoan",
"french-italian-portuguese-spanish",
"french",
"italian",
"portuguese",
"spanish",
"map",
"fra",
"ita",
"por",
"spa",
"license:cc-by-... | translation | 2026-04-20T13:20:27Z | # WindyWord.ai Translation — Austronesian → French/Italian/Portuguese/Spanish
**Translates Austronesian (Indonesian, Malay, Tagalog, Malagasy, Samoan) → French / Italian / Portuguese / Spanish.**
**Quality Rating: ⭐⭐½ (2.5★ Basic)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprie... | [] |
felixwangg/Qwen2.5-Coder-7B-sft-minus-alpha-1-line-diff-ctx3-v2 | felixwangg | 2026-04-14T01:03:28Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"text-generation",
"axolotl",
"base_model:adapter:Qwen/Qwen2.5-Coder-7B-Instruct",
"lora",
"transformers",
"conversational",
"dataset:felixwangg/prime_vul_minus_splitted_line_diff_mask_skip_indent_ctx3_chat_v2",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"lice... | text-generation | 2026-04-14T01:03:01Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
mradermacher/s1.1-Qwen2.5-Base-7B-GGUF | mradermacher | 2025-12-12T10:48:00Z | 34 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:asparius/s1.1-Qwen2.5-Base-7B",
"base_model:quantized:asparius/s1.1-Qwen2.5-Base-7B",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-12T09:09:15Z | ## 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... | [] |
jasonhuang3/101-our-68-qwen-2-5-7b-math-lora-28k | jasonhuang3 | 2026-01-19T14:41:03Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"endpoints_compatible",
"region:us"
] | null | 2026-01-18T08:09:23Z | # Model Card for 101-our-68-qwen-2-5-7b-math-lora-28k
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a ti... | [
{
"start": 189,
"end": 192,
"text": "TRL",
"label": "training method",
"score": 0.8162292242050171
},
{
"start": 959,
"end": 962,
"text": "DPO",
"label": "training method",
"score": 0.8282275795936584
},
{
"start": 1138,
"end": 1141,
"text": "TRL",
"la... |
pcvlab/unetplusplus_normal_vs_pvd | pcvlab | 2026-03-05T03:52:27Z | 33 | 0 | erdes | [
"erdes",
"safetensors",
"unetplusplus",
"ocular-ultrasound",
"medical-imaging",
"3d-classification",
"retinal-detachment",
"image-classification",
"arxiv:2508.04735",
"license:cc-by-4.0",
"region:us"
] | image-classification | 2026-03-05T02:55:22Z | # UNETPLUSPLUS — Normal Vs Pvd
Trained model weights for **PVD classification (normal vs. PVD)** using ocular ultrasound videos.
| Resource | Link |
|----------|------|
| Paper | [](https://arxiv.org/abs/2508.04735) |
| Dataset | [![HF Dataset](https:/... | [] |
mlx-community/DR-Venus-4B-SFT-mlx-8Bit | mlx-community | 2026-04-29T15:26:09Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3",
"arxiv:2604.19859",
"base_model:inclusionAI/DR-Venus-4B-SFT",
"base_model:quantized:inclusionAI/DR-Venus-4B-SFT",
"8-bit",
"region:us"
] | null | 2026-04-29T14:53:22Z | # mlx-community/DR-Venus-4B-SFT-mlx-8Bit
The Model [mlx-community/DR-Venus-4B-SFT-mlx-8Bit](https://huggingface.co/mlx-community/DR-Venus-4B-SFT-mlx-8Bit) was converted to MLX format from [inclusionAI/DR-Venus-4B-SFT](https://huggingface.co/inclusionAI/DR-Venus-4B-SFT) using mlx-lm version **0.31.3**.
## Use with mlx... | [] |
ksjpswaroop/zindango-slm | ksjpswaroop | 2026-02-19T03:02:16Z | 91 | 0 | transformers | [
"transformers",
"safetensors",
"gguf",
"llama",
"text-generation",
"zindango",
"instruction-tuned",
"english-only",
"sft",
"conversational",
"en",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-15T19:05:14Z | # zindango-slm
A lightweight, capable instruction-following model for Zindango. Fine-tuned for clarity, versatility, and personal AI workloads.
## Features
- **Task-agnostic**: Handles summaries, Q&A, drafting, analysis, and open-ended assistance
- **Consistent identity**: Reliably introduces itself as zindango-slm,... | [] |
hurtmongoose/llama3.2-rank-16-weighted | hurtmongoose | 2025-12-21T20:35:47Z | 0 | 0 | peft | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:meta-llama/Llama-3.2-3B-Instruct",
"base_model:adapter:meta-llama/Llama-3.2-3B-Instruct",
"license:llama3.2",
"region:us"
] | null | 2025-12-21T18:34:36Z | <!-- 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. -->
# llama3.2-rank-16-weighted
This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-ll... | [] |
aluha501/xlm-roberta-product-extractor | aluha501 | 2025-12-29T09:12:44Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"token-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-base",
"base_model:finetune:FacebookAI/xlm-roberta-base",
"license:mit",
"endpoints_compatible",
"region:us"
] | token-classification | 2025-12-29T08:51:57Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-product-extractor
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) o... | [] |
cunxin/gemma-4-E4B-email-fraud-detector | cunxin | 2026-04-14T03:50:16Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"email-fraud-detection",
"phishing",
"spam",
"cybersecurity",
"lora",
"fine-tuned",
"text-generation",
"conversational",
"en",
"base_model:google/gemma-4-E4B-it",
"base_model:adapter:google/gemma-4-E4B-it",
"license:gemma",... | text-generation | 2026-04-14T02:49:39Z | # Gemma 4 E4B Email Fraud Detector
A fine-tuned [Google Gemma 4 E4B-it](https://huggingface.co/google/gemma-4-E4B-it) model specialized in **email fraud detection, phishing identification, and spam classification**. This model analyzes raw email content and outputs structured JSON verdicts with threat analysis, risk s... | [] |
rbelanec/train_mrpc_1754652142 | rbelanec | 2025-08-08T13:45:56Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"p-tuning",
"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 | 2025-08-08T13:14:45Z | <!-- 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. -->
# train_mrpc_1754652142
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-lla... | [] |
tomaarsen/reranker-Qwen3.5-0.8B-doodles-image-text-to-text-causal-score-head | tomaarsen | 2026-03-18T19:05:57Z | 36 | 1 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"qwen3_5",
"cross-encoder",
"reranker",
"generated_from_trainer",
"dataset_size:9000",
"loss:BinaryCrossEntropyLoss",
"text-ranking",
"dataset:julianmoraes/doodles-captions-manual",
"arxiv:1908.10084",
"base_model:Qwen/Qwen3.5-0.8B",
"base_model:finetu... | text-ranking | 2026-03-18T19:05:29Z | # CrossEncoder based on Qwen/Qwen3.5-0.8B
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) on the [image_to_text](https://huggingface.co/datasets/julianmoraes/doodles-captions-manual) and [text_to_i... | [] |
Grigorij/fanuc_shooting_sim_unity | Grigorij | 2025-08-20T12:11:12Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Grigorij/Shooting_unit_2",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-08-11T11:20:47Z | # 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... | [] |
ryandono/mxbai-edge-colbert-v0-17m-onnx-int8 | ryandono | 2025-12-06T21:40:04Z | 266 | 0 | null | [
"onnx",
"modernbert",
"region:us"
] | null | 2025-12-06T21:35:40Z | # mxbai-edge-colbert-v0-17m — ONNX export (ColBERT, ModernBERT backbone)
This repository contains an ONNX export of `mixedbread-ai/mxbai-edge-colbert-v0-17m` produced with PyLate + a ColBERT-aware wrapper. It preserves the projection stack and ColBERT markers (`[Q] ` / `[D] `) and includes a skiplist for MaxSim.
## C... | [] |
ApocalypseParty/Qwen3.6-27B-SFT-1-chkpt441-Q6_K-GGUF | ApocalypseParty | 2026-04-27T11:04:22Z | 0 | 0 | null | [
"gguf",
"llama-cpp",
"gguf-my-repo",
"base_model:ApocalypseParty/Qwen3.6-27B-SFT-1-chkpt441",
"base_model:quantized:ApocalypseParty/Qwen3.6-27B-SFT-1-chkpt441",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-27T11:03:24Z | # zerofata/Qwen3.6-27B-SFT-1-chkpt441-Q6_K-GGUF
This model was converted to GGUF format from [`ApocalypseParty/Qwen3.6-27B-SFT-1-chkpt441`](https://huggingface.co/ApocalypseParty/Qwen3.6-27B-SFT-1-chkpt441) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refe... | [] |
spikymoth/G3-Heresy-MPOA-G-W99-D0.0690-R02 | spikymoth | 2026-01-07T16:05:34Z | 2 | 0 | null | [
"safetensors",
"gemma3",
"text-generation",
"conversational",
"en",
"region:us"
] | text-generation | 2025-12-24T22:35:14Z | An experimental ablation of Gemma-3-27B-it, using the [Heretic](https://github.com/p-e-w/heretic) tool.
Compared to the standard configuration of Heretic, there are a few changes:
1. The training and test datasets used were extended compared to the default subset used by Heretic
2. A version of [Magnitude-Preserving O... | [
{
"start": 298,
"end": 338,
"text": "Magnitude-Preserving Orthogonal Ablation",
"label": "training method",
"score": 0.8209851384162903
},
{
"start": 1030,
"end": 1070,
"text": "Magnitude-Preserving Orthogonal Ablation",
"label": "training method",
"score": 0.871885895729... |
AITRADER/Qwen2.5-VL-32B-Instruct-abliterated-mlx-fp16 | AITRADER | 2026-02-15T12:51:14Z | 74 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2_5_vl",
"image-text-to-text",
"multimodal",
"abliterated",
"uncensored",
"mlx",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-VL-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-32B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"... | image-text-to-text | 2026-02-15T12:49:14Z | # AITRADER/Qwen2.5-VL-32B-Instruct-abliterated-mlx-fp16
This model was converted to MLX format from [`huihui-ai/Qwen2.5-VL-32B-Instruct-abliterated`]() using mlx-vlm version **0.3.11**.
Refer to the [original model card](https://huggingface.co/huihui-ai/Qwen2.5-VL-32B-Instruct-abliterated) for more details on the model... | [] |
cturan/Olmo-3-7B-Instruct-Q1_0 | cturan | 2026-04-17T02:58:56Z | 240 | 4 | null | [
"gguf",
"base_model:allenai/Olmo-3-7B-Instruct",
"base_model:quantized:allenai/Olmo-3-7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-12T23:33:19Z | # OLMo-3 7B Instruct (1-Bit Experimental)
This is an experimental 1-bit quantized version of the OLMo-3 7B Instruct model. It was developed using **Quantization Aware Distillation (QAD)** techniques. Notably, the entire architecture, including the embeddings, has been fully compressed to 1-bit.
## Current Development... | [] |
Shamxisa/marian-finetuned-kde4-en-to-fr | Shamxisa | 2026-03-03T16:17:38Z | 43 | 0 | transformers | [
"transformers",
"safetensors",
"marian",
"text2text-generation",
"translation",
"generated_from_trainer",
"base_model:Helsinki-NLP/opus-mt-en-fr",
"base_model:finetune:Helsinki-NLP/opus-mt-en-fr",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-03-03T14:12:40Z | <!-- 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. -->
# marian-finetuned-kde4-en-to-fr
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki... | [] |
dnn1002/smolvla_base | dnn1002 | 2026-04-23T05:05:34Z | 146 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:dnn1002/so101-simple-pickup-2-cameras",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-10T10:27:52Z | # 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... | [] |
deepanshu120/Text_Classification | deepanshu120 | 2026-04-22T06:26:34Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"re... | text-classification | 2026-04-22T05:05:12Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Text_Classification
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/... | [] |
Muapi/mugler-metal-robot-suit-flux-ponyxl-1.5 | Muapi | 2025-08-16T22:06:35Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-16T22:06:19Z | # Mugler Metal / Robot suit [Flux/PonyXL/1.5]
**Base model**: Flux.1 D
**Trained words**: metalSuit, helmet with smooth surfaces covering head
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "ht... | [] |
weijietling/medgemma-report-generation-5-epoch | weijietling | 2026-01-15T05:46:50Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:google/medgemma-4b-it",
"base_model:finetune:google/medgemma-4b-it",
"endpoints_compatible",
"region:us"
] | null | 2026-01-15T04:36:43Z | # Model Card for medgemma-report-generation-5-epoch
This model is a fine-tuned version of [google/medgemma-4b-it](https://huggingface.co/google/medgemma-4b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a ti... | [] |
multimolecule/hyenadna-large | multimolecule | 2026-03-01T11:19:06Z | 16 | 0 | multimolecule | [
"multimolecule",
"safetensors",
"hyenadna",
"Biology",
"DNA",
"text-generation",
"dataset:multimolecule/gencode-human",
"arxiv:2302.10866",
"license:agpl-3.0",
"region:us"
] | text-generation | 2026-03-01T11:18:54Z | # HyenaDNA
Pre-trained model on human reference genome using a causal language modeling (CLM) objective with the Hyena operator.
## Disclaimer
This is an UNOFFICIAL implementation of the [HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution](https://doi.org/10.5555/3666122.3667994) by Eric ... | [] |
an0n3/surreal-iml-riva-rce | an0n3 | 2026-02-05T14:24:18Z | 0 | 0 | null | [
"region:us"
] | null | 2026-02-05T13:30:26Z | # SurrealDB Nested Model RCE PoC
## Payload: nested.surreal → IML Riva Pipeline
## Repro Script
```bash
chmod +x ../run_surreal.sh
../run_surreal.sh
Attack Flow
nested.surreal → Riva model load → SurrealDB query injection → RCE
Files:
exploit.surreal (renamed nested.surreal)
run_surreal.sh (verification)
Title: S... | [] |
newtts2017/ideiu9ou | newtts2017 | 2025-09-19T16:21:45Z | 1 | 0 | diffusers | [
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] | text-to-image | 2025-09-19T16:11:57Z | # Ideiu9Ou
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-traine... | [] |
Edy500/humanoid-instruction-model-1-110226 | Edy500 | 2026-02-11T12:47:16Z | 0 | 0 | null | [
"humanoid",
"robotics",
"instruction-following",
"safety",
"license:mit",
"region:us"
] | robotics | 2026-02-11T12:47:16Z | ---
license: mit
tags:
- humanoid
- robotics
- instruction-following
- safety
---
# Humanoid Instruction Model - 300126 (v1)
This repository is a lightweight placeholder model entry for humanoid instruction-following tasks.
## Overview
Provides a valid Hugging Face model structure for robotics workflo... | [] |
sgao2/fake_vs_real_image_classifier | sgao2 | 2025-10-11T03:13:36Z | 0 | 0 | null | [
"safetensors",
"vit",
"generated_from_trainer",
"base_model:google/vit-base-patch16-224-in21k",
"base_model:finetune:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"region:us"
] | null | 2025-10-11T02:21:18Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-... | [] |
onlyrafaels/mistral-7b_guanaco | onlyrafaels | 2026-02-15T13:38:06Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:mistralai/Mistral-7B-v0.3",
"base_model:finetune:mistralai/Mistral-7B-v0.3",
"endpoints_compatible",
"region:us"
] | null | 2026-02-15T12:14:20Z | # Model Card for mistral-7b_guanaco
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machi... | [] |
AnonymousCS/xlmr_immigration_combo23_0 | AnonymousCS | 2025-08-20T18:48:13Z | 1 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"xlm-roberta",
"text-classification",
"generated_from_trainer",
"base_model:FacebookAI/xlm-roberta-large",
"base_model:finetune:FacebookAI/xlm-roberta-large",
"license:mit",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-08-20T18:43:38Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlmr_immigration_combo23_0
This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI... | [] |
MatteoBaldelli/dqn-SpaceInvadersNoFrameskip-v4 | MatteoBaldelli | 2026-04-28T16:54:12Z | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | 2026-04-28T16:53:37Z | # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework... | [] |
Thireus/Kimi-K2-Thinking-THIREUS-IQ2_K_R4-SPECIAL_SPLIT | Thireus | 2026-02-12T12:38:53Z | 8 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-01T06:12:38Z | # Kimi-K2-Thinking
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Kimi-K2-Thinking-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Kimi-K2-Thinking model (official repo: https://huggingface.co/moonshotai/Kimi-K2-Thinking). These GGUF shards a... | [] |
ShourenWSR/HT-Llama3-Llama-140k-phase2 | ShourenWSR | 2025-09-18T05:35:25Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-18T05:29:02Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Llama_phase2_140k
This model is a fine-tuned version of [./saves/2phases/Llama_phase1_140k](https://huggingface.co/./saves/2phase... | [] |
mradermacher/AdQWENistrator-9B-GGUF | mradermacher | 2026-04-15T11:28:45Z | 424 | 0 | transformers | [
"transformers",
"gguf",
"linux",
"sysadmin",
"kernel",
"assembly",
"fine-tuned",
"abliteration",
"uncensored",
"qwen3.5",
"duoneural",
"en",
"base_model:DuoNeural/AdQWENistrator-9B",
"base_model:quantized:DuoNeural/AdQWENistrator-9B",
"license:apache-2.0",
"endpoints_compatible",
"re... | null | 2026-04-13T06:24:02Z | ## 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: 1 -->
static ... | [] |
ruslanmusinrusmus/russianrap-v3-lora | ruslanmusinrusmus | 2026-03-15T10:24:20Z | 0 | 0 | null | [
"safetensors",
"music-generation",
"lora",
"russian-rap",
"ru",
"license:apache-2.0",
"region:us"
] | null | 2026-03-14T13:03:24Z | # russianrap-v3 LoRA for ACE-Step 1.5
LoRA fine-tuned weights for Russian rap music generation using ACE-Step 1.5.
## Training Details
- **Base Model**: ACE-Step v1.5 Turbo
- **Training Data**: 149 Russian rap tracks
- **Epochs**: 30
- **Loss Curve**: E1:2.11 -> E10:1.2409 -> E20:1.2235 (best) -> E30:1.2291
- **LoRA... | [
{
"start": 25,
"end": 37,
"text": "ACE-Step 1.5",
"label": "training method",
"score": 0.7461002469062805
},
{
"start": 39,
"end": 43,
"text": "LoRA",
"label": "training method",
"score": 0.7172011733055115
},
{
"start": 102,
"end": 114,
"text": "ACE-Step ... |
T5Forst/Qwen3.5-9B | T5Forst | 2026-03-04T19:53:44Z | 19 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3_5",
"image-text-to-text",
"conversational",
"base_model:Qwen/Qwen3.5-9B-Base",
"base_model:finetune:Qwen/Qwen3.5-9B-Base",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-03-04T19:53:43Z | # Qwen3.5-9B
<img width="400px" src="https://qianwen-res.oss-accelerate.aliyuncs.com/logo_qwen3.5.png">
[](https://chat.qwen.ai)
> [!Note]
> This repository contains model weights and configuration files for the post-trained mode... | [] |
adpretko/AnghaBench_risc_clang_o0_1percent_AMD | adpretko | 2025-10-29T14:19:48Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen2.5-1.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-1.5B-Instruct",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible"... | text-generation | 2025-10-29T13:10:41Z | <!-- 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. -->
# AnghaBench_risc_clang_o0_1percent_AMD
This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Q... | [] |
hbpkillerX/legal-clause-minilm-l6-v2 | hbpkillerX | 2025-12-29T05:40:40Z | 2 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"bert",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:133951",
"loss:MultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:1705.00652",
"base_model:sentence-transformers/all-MiniLM-L6-v2",
"base_model... | sentence-similarity | 2025-12-29T05:40:36Z | # SentenceTransformer based on sentence-transformers/all-MiniLM-L6-v2
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2). It maps sentences & paragraphs to a 384-dimensional dense vector s... | [] |
manancode/opus-mt-fi-tn-ctranslate2-android | manancode | 2025-08-17T17:16:38Z | 0 | 0 | null | [
"translation",
"opus-mt",
"ctranslate2",
"quantized",
"multilingual",
"license:apache-2.0",
"region:us"
] | translation | 2025-08-17T17:16:27Z | # opus-mt-fi-tn-ctranslate2-android
This is a quantized INT8 version of `Helsinki-NLP/opus-mt-fi-tn` converted to CTranslate2 format for efficient inference.
## Model Details
- **Original Model**: Helsinki-NLP/opus-mt-fi-tn
- **Format**: CTranslate2
- **Quantization**: INT8
- **Framework**: OPUS-MT
- **Converted by*... | [] |
jordiferrero/PI1M-68M | jordiferrero | 2026-01-22T14:49:52Z | 0 | 0 | null | [
"chemistry",
"smiles",
"tokenization",
"dynamic-tokenization",
"h-net",
"hierarchical-networks",
"molecular-representation",
"polymer",
"mamba",
"transformer",
"feature-extraction",
"en",
"dataset:PI1M",
"license:mit",
"region:us"
] | feature-extraction | 2026-01-22T14:46:48Z | # PI1M-68M
**H-Net model for dynamic SMILES tokenization**
PI1M polymer dataset, 68M bytes (~1 epoch), 10x concatenation, 1-stage architecture
## Model Details
| Property | Value |
|----------|-------|
| **Architecture** | H-Net (Hierarchical Network) |
| **Parameters** | ~350M |
| **Dataset** | PI1M |
| **Training... | [] |
jc2375/Qwen3-30B-A3B-Thinking-2507-Deepseek-v3.1-Distill-FP32-mlx-4Bit | jc2375 | 2025-09-08T02:22:02Z | 90 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_moe",
"causal-lm",
"moe",
"mixture-of-experts",
"qwen",
"distillation",
"svd",
"lora-merged",
"code-generation",
"mlx-my-repo",
"license:apache-2.0",
"4-bit",
"region:us"
] | null | 2025-09-08T02:20:52Z | # jc2375/Qwen3-30B-A3B-Thinking-2507-Deepseek-v3.1-Distill-FP32-mlx-4Bit
The Model [jc2375/Qwen3-30B-A3B-Thinking-2507-Deepseek-v3.1-Distill-FP32-mlx-4Bit](https://huggingface.co/jc2375/Qwen3-30B-A3B-Thinking-2507-Deepseek-v3.1-Distill-FP32-mlx-4Bit) was converted to MLX format from [BasedBase/Qwen3-30B-A3B-Thinking-2... | [] |
MaryPazRB/Paper_CLR_CV | MaryPazRB | 2026-03-26T18:39:32Z | 0 | 0 | null | [
"computer-vision",
"image-segmentation",
"plant-disease",
"agricultural-ai",
"foundation-model",
"sam",
"yolo",
"coffee",
"rust-disease",
"en",
"dataset:coffee-leaf-rust-severity",
"license:mit",
"region:us"
] | image-segmentation | 2026-02-28T18:29:29Z | Foundation Model–Assisted Coffee Leaf Rust Severity Estimation
This repository accompanies the manuscript:
Foundation model–assisted segmentation enables robust field-based severity estimation of coffee leaf rust
This project presents a fully reproducible computer vision pipeline for quantitative estimation of coffe... | [] |
crafiq/flux-2-klein-9b-game-asset-tiles-lora | crafiq | 2026-05-03T17:15:41Z | 0 | 0 | diffusers | [
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:black-forest-labs/FLUX.2-klein-base-9B",
"base_model:adapter:black-forest-labs/FLUX.2-klein-base-9B",
"license:apache-2.0",
"region:us"
] | text-to-image | 2026-05-03T17:05:19Z | # FLUX Game Asset Tiles LoRA
<Gallery />
## Model description
This is an image-to-image LoRA to generate 2D game asset tiles. Provide a mask template or an existing tile image as input, and use the following prompt structure:
`Game asset tile, <shape>, <view>. <content>`
- `<shape>`: Choose one of `rectangular`, ... | [] |
jomarie04/the_legend_of_zelda_games_model | jomarie04 | 2026-01-04T12:37:18Z | 0 | 0 | null | [
"license:cc-by-4.0",
"region:us"
] | null | 2026-01-04T12:37:04Z | ---
license: cc-by-4.0
tags:
- zelda
- nintendo
- rpg
- adventure
- dataset
---
# The Legend of Zelda Games Dataset Model
## 📌 Overview
This model offers a curated dataset of **The Legend of Zelda mainline games**, organized by era, platform, and release year.
## 📂 Dataset Structure
Columns included:
- `Era`
- `Ga... | [
{
"start": 413,
"end": 424,
"text": "AI training",
"label": "training method",
"score": 0.815139651298523
}
] |
AronDaron/Qwen2.5-Coder-7B-Instruct-DatasetGen-v2 | AronDaron | 2026-04-29T09:04:00Z | 100 | 0 | null | [
"gguf",
"code",
"fine-tune",
"qwen",
"coding-assistant",
"text-generation",
"en",
"dataset:AronDaron/dataset-gen-v2",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:quantized:Qwen/Qwen2.5-Coder-7B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversation... | text-generation | 2026-04-20T12:57:59Z | # Qwen2.5-Coder-7B-Instruct — Dataset Generator V2 Fine-tune
Fine-tuned version of [Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct)
trained on [Dataset Generator V2](https://huggingface.co/datasets/AronDaron/dataset-gen-v2)
— synthetic coding dataset generated with [Dataset Generato... | [] |
lashik/act_y1 | lashik | 2026-04-15T05:47:19Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:lashik/sim_data12",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-15T05:46:15Z | # 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":... |
gibbonbot/ACT-Test_Data_Ex-iuhpwilo94 | gibbonbot | 2026-04-09T11:03:26Z | 0 | 0 | gibbonbot | [
"gibbonbot",
"act",
"robotics",
"dataset:AgentAppStore/Test_Data_Ex",
"region:us"
] | robotics | 2026-04-09T11:03:13Z | ---
datasets: AgentAppStore/Test_Data_Ex
library_name: gibbonbot
pipeline_tag: robotics
model_name: act
tags:
- gibbonbot
- act
task_categories:
- robotics
---
# act model - 🧪 gibbonbot training pipeline
- **Dataset**: [AgentAppStore/Test_Data_Ex](https://huggingface.co/datasets/AgentAppStore/Test_Data_Ex)
- **Wandb... | [] |
Aletheia-Bench/DPO-Think-14B | Aletheia-Bench | 2026-01-08T07:23:37Z | 3 | 1 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"dataset:Aletheia-Bench/Aletheia-DPO",
"base_model:deepseek-ai/DeepSeek-R1-Distill-Qwen-14B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-Distill-Qwen-14B",
"license:cc-by-nc-sa-4.0",
"text-generation-inference",
"endp... | text-generation | 2025-11-09T03:07:11Z | <font size=3><div align='center' >
[[**🤗 Model & Dataset**](https://huggingface.co/Aletheia-Bench)]
[[**📊 Code**](https://github.com/insait-institute/aletheia)]
[[**📖 Paper**](https://arxiv.org/)]
</div></font>
# Aletheia: What Makes RLVR For Code Verifiers Tick?
Multi-domain thinking verifiers trained via Rein... | [] |
AgentAnon/gemma-4-26B-A4B-it-uncensored-GGUF | AgentAnon | 2026-04-16T16:50:36Z | 0 | 0 | null | [
"gguf",
"abliteration",
"uncensored",
"gemma-4",
"text-generation",
"en",
"base_model:TrevorJS/gemma-4-26B-A4B-it-uncensored",
"base_model:quantized:TrevorJS/gemma-4-26B-A4B-it-uncensored",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-04-16T16:50:36Z | # gemma-4-26B-A4B-it-uncensored (GGUF)
GGUF quantizations of [TrevorJS/gemma-4-26B-A4B-it-uncensored](https://huggingface.co/TrevorJS/gemma-4-26B-A4B-it-uncensored).
## Files
| File | Quant | Size |
|------|-------|------|
| `gemma-4-26B-A4B-it-uncensored-Q4_K_M.gguf` | Q4_K_M | 16.8 GB |
| `gemma-4-26B-A4B-it-uncen... | [] |
jkfm/finetuned-xray | jkfm | 2025-10-09T20:06:28Z | 5 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"base_model:google/vit-base-patch16-224-in21k",
"base_model:finetune:google/vit-base-patch16-224-in21k",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2025-10-09T14:08:50Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# finetuned-xray
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-p... | [] |
vitthalbhandari/mms-1b-all-aft-mid-mmc | vitthalbhandari | 2026-02-17T00:03:40Z | 2 | 0 | null | [
"safetensors",
"wav2vec2",
"audio",
"automatic-speech-recognition",
"mms",
"adapter",
"mmc",
"dataset:mozilla-foundation/common_voice_spontaneous_speech",
"license:cc-by-nc-4.0",
"region:us"
] | automatic-speech-recognition | 2026-02-17T00:03:08Z | # MMS Adapter Fine-tuned for Michoacán Mazahua
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all)
on the Mozilla Common Voice Spontaneous Speech dataset for Michoacán Mazahua (mmc).
## Training
- Base model: facebook/mms-1b-all
- Fine-tuning method: Adapter layer... | [] |
marialcasimiro/tatoeba-opus-2021-02-18-cat-ita | marialcasimiro | 2026-03-18T22:19:30Z | 20 | 0 | null | [
"pytorch",
"marian",
"translation",
"ca",
"it",
"license:apache-2.0",
"region:us"
] | translation | 2026-03-18T22:18:08Z | ### cat-ita
* source language name: Catalan
* target language name: Italian
* OPUS readme: [README.md](https://object.pouta.csc.fi/Tatoeba-MT-models/cat-ita/README.md)
* model: transformer-align
* source language code: ca
* target language code: it
* dataset: opus
* release date: 2021-02-18
* pre-processing: normali... | [] |
jkazdan/google_gemma-3-12b-it_LLM-LAT_harmful-dataset_harmful_60_of_4950 | jkazdan | 2026-01-05T02:12:56Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma3",
"image-text-to-text",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:google/gemma-3-12b-it",
"base_model:finetune:google/gemma-3-12b-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-01-05T01:51:20Z | # Model Card for google_gemma-3-12b-it_LLM-LAT_harmful-dataset_harmful_60_of_4950
This model is a fine-tuned version of [google/gemma-3-12b-it](https://huggingface.co/google/gemma-3-12b-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipelin... | [] |
Thireus/Qwen3.5-35B-A3B-THIREUS-IQ2_S-SPECIAL_SPLIT | Thireus | 2026-03-15T13:41:06Z | 15 | 0 | null | [
"gguf",
"arxiv:2505.23786",
"license:mit",
"region:us"
] | null | 2026-03-15T12:49:46Z | # Qwen3.5-35B-A3B
## 🤔 What is this [HuggingFace repository](https://huggingface.co/Thireus/Qwen3.5-35B-A3B-THIREUS-BF16-SPECIAL_SPLIT/) about?
This repository provides **GGUF-quantized tensors** for the Qwen3.5-35B-A3B model (official repo: https://huggingface.co/Qwen/Qwen3.5-35B-A3B). These GGUF shards are designe... | [] |
Abiray/Qwen3.5-9B-abliterated-GGUF | Abiray | 2026-03-10T05:30:00Z | 1,981 | 7 | gguf | [
"gguf",
"qwen",
"qwen3.5",
"uncensored",
"abliterated",
"vision",
"multimodal",
"base_model:lukey03/Qwen3.5-9B-abliterated",
"base_model:quantized:lukey03/Qwen3.5-9B-abliterated",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-06T18:47:02Z | # Qwen3.5-9B-abliterated - GGUF
This repository contains a full spectrum of GGUF quantizations for [lukey03's Qwen3.5-9B-abliterated](https://huggingface.co/lukey03/Qwen3.5-9B-abliterated).
These files are optimized for local inference using [llama.cpp](https://github.com/ggerganov/llama.cpp), LM Studio, Jan, Ollama... | [] |
rbelanec/train_boolq_789_1767713899 | rbelanec | 2026-01-06T18:01:09Z | 0 | 0 | peft | [
"peft",
"safetensors",
"llama-factory",
"prompt-tuning",
"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 | 2026-01-06T15:38:49Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# train_boolq_789_1767713899
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/met... | [] |
minhnguyent546/KaLM-Embedding-Gemma3-12B-2511-tokenizer-for-transformers-v5 | minhnguyent546 | 2026-05-03T18:22:25Z | 0 | 0 | null | [
"region:us"
] | null | 2026-05-03T17:21:35Z | # Overview
This is the converted tokenizer for [tencent/KaLM-Embedding-Gemma3-12B-2511](https://huggingface.co/tencent/KaLM-Embedding-Gemma3-12B-2511/) to make it compatible with `transformers>=5.0.0` (and `sentence-transformers>=5.3.0`).
To load the model with `sentence-transfomrers` you can use:
```python
import se... | [] |
kanishka/opt-babylm2-rewritten-clean-spacy-earlystop_hierarchical_211_size-origin_adj1-bpe_seed-211_1e-3 | kanishka | 2025-12-14T15:25:11Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"opt",
"text-generation",
"generated_from_trainer",
"dataset:kanishka/babylm2-rewritten-clean-spacy_hierarchical-adj_211_size-origin_adj1-ablation",
"model-index",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-14T07:13:24Z | <!-- 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. -->
# opt-babylm2-rewritten-clean-spacy-earlystop_hierarchical_211_size-origin_adj1-bpe_seed-211_1e-3
This model was trained from scrat... | [] |
nazihara/Qwen3.5-27B-Aggressive | nazihara | 2026-04-14T14:12:40Z | 0 | 0 | null | [
"gguf",
"uncensored",
"qwen3.5",
"qwen",
"en",
"zh",
"multilingual",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-14T14:12:40Z | # Qwen3.5-27B-Uncensored-HauhauCS-Aggressive
> **[Join the Discord](https://discord.gg/SZ5vacTXYf)** for updates, roadmaps, projects, or just to chat.
Qwen3.5-27B uncensored by HauhauCS.
## About
**0/465 refusals.** Fully uncensored with zero capability loss.
No changes to datasets or capabilities. Fully functiona... | [] |
LiquidAI/LFM2.5-VL-1.6B | LiquidAI | 2026-03-30T11:10:42Z | 127,664 | 259 | transformers | [
"transformers",
"safetensors",
"lfm2_vl",
"image-text-to-text",
"liquid",
"lfm2",
"lfm2-vl",
"edge",
"lfm2.5-vl",
"lfm2.5",
"conversational",
"en",
"ja",
"ko",
"fr",
"es",
"de",
"ar",
"zh",
"arxiv:2511.23404",
"base_model:LiquidAI/LFM2.5-1.2B-Base",
"base_model:finetune:Liq... | image-text-to-text | 2026-01-05T19:07:50Z | <center>
<div style="text-align: center;">
<img
src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png"
alt="Liquid AI"
style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
/>
</div>
<... | [] |
Sao10K/L3-8B-Lunaris-v1 | Sao10K | 2024-06-29T18:21:32Z | 1,550 | 141 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"conversational",
"en",
"license:llama3",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | text-generation | 2024-06-26T00:40:12Z | A generalist / roleplaying model merge based on Llama 3. Models are selected from my personal experience while using them.
I personally think this is an improvement over Stheno v3.2, considering the other models helped balance out its creativity and at the same time improving its logic.
Settings:
```
Instruct // Cont... | [] |
sathishphdai/finance-slm-1m | sathishphdai | 2026-03-02T14:37:44Z | 36 | 0 | null | [
"pytorch",
"safetensors",
"finance-slm",
"finance",
"banking",
"fintech",
"trading",
"slm",
"llama-style",
"rope",
"1m-context",
"from-scratch",
"text-generation",
"en",
"license:mit",
"region:us"
] | text-generation | 2026-03-01T20:57:58Z | # Finance-SLM: Finance Small Language Model
A **LLaMA-style transformer** (~33.9M params) trained from scratch on Finance domain data.
Supports up to **1M token context** via RoPE.
## Architecture
| Component | Value |
|-----------|-------|
| Architecture | LLaMA-style (RoPE + RMSNorm + SwiGLU) |
| Parameters | ~33.9... | [
{
"start": 176,
"end": 180,
"text": "RoPE",
"label": "training method",
"score": 0.7327645421028137
},
{
"start": 260,
"end": 271,
"text": "LLaMA-style",
"label": "training method",
"score": 0.7086614966392517
}
] |
NodaLoxia/LLM | NodaLoxia | 2026-03-01T11:52:57Z | 20 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-28T06:54:17Z | ＜Noda-Test-1＞
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
This repository contains **LoRA adapter weights only**.
The base model must be loaded separately.
## Training Objective
This adapter is trained to improve **structured output a... | [
{
"start": 115,
"end": 120,
"text": "QLoRA",
"label": "training method",
"score": 0.7126650810241699
}
] |
ccm/2025-24679-image-autogluon-predictor | ccm | 2025-09-16T01:00:21Z | 0 | 0 | autogluon | [
"autogluon",
"images",
"image-classification",
"en",
"dataset:ccm/2025-24679-image-dataset",
"license:mit",
"region:us"
] | image-classification | 2025-09-15T00:27:37Z | # Model Card for Image AutoML Predictor
Binary/multiclass image classifier trained with **AutoGluon MultiModal** on the *augmented* split of `ccm/2025-24679-image-dataset` to predict survey-derived image labels. Metrics are reported on a held-out test portion of the augmented split and evaluated via **external validat... | [
{
"start": 91,
"end": 111,
"text": "AutoGluon MultiModal",
"label": "training method",
"score": 0.7467141151428223
}
] |
dss107/LLAMA-3.2-1b-HRV-Insights | dss107 | 2025-10-14T07:00:10Z | 0 | 0 | null | [
"safetensors",
"llama",
"license:llama3.2",
"region:us"
] | null | 2025-10-13T11:08:30Z | # 🧠 Fine-tuning Llama 3.2-1B-Instruct with LoRA (4-bit Quantization)
## 📅 Training Summary
**Date:** 2025-10-13
**Framework:** Hugging Face Transformers + PEFT + bitsandbytes
**Model Base:** `meta-llama/Llama-3.2-1B-Instruct`
**Adapter Type:** LoRA (QLoRA 4-bit)
---
## ⚙️ Environment Setup
```bash
pip insta... | [] |
OsoAlbasha/distilbert-base-uncased-finetuned-emotion | OsoAlbasha | 2026-01-18T22:01:58Z | 1 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"base_model:distilbert/distilbert-base-uncased",
"base_model:finetune:distilbert/distilbert-base-uncased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"re... | text-classification | 2026-01-18T21:40:42Z | <!-- 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/... | [] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.