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 |
|---|---|---|---|---|---|---|---|---|---|---|
thunderboltc/whisper-small-santali-ol-chiki | thunderboltc | 2025-12-23T14:49:07Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"sat",
"dataset:mozilla-foundation/common-voice-santali",
"base_model:openai/whisper-small",
"base_model:finetune:openai/whisper-small",
"license:apache-2.0",
"endpoints_compatibl... | automatic-speech-recognition | 2025-12-22T07:10:01Z | <!-- 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. -->
# Whisper Small Santali (Ol Chiki)
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisp... | [] |
mradermacher/SP-7B-GGUF | mradermacher | 2025-11-13T01:40:38Z | 17 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:volcanos/SP-7B",
"base_model:quantized:volcanos/SP-7B",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-11-12T15:45:58Z | ## 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... | [] |
prithivMLmods/Qwen3-VL-2B-Instruct-GGUF | prithivMLmods | 2025-11-12T04:04:24Z | 58 | 1 | transformers | [
"transformers",
"gguf",
"qwen3_vl",
"text-generation-inference",
"ggml",
"llama.cpp",
"image-text-to-text",
"en",
"base_model:Qwen/Qwen3-VL-2B-Instruct",
"base_model:quantized:Qwen/Qwen3-VL-2B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2025-11-11T12:26:04Z | # **Qwen3-VL-2B-Instruct-GGUF**
> Qwen3-VL-2B-Instruct is a highly advanced 2-billion-parameter vision-language model from the Qwen3 series, designed to deliver superior multimodal understanding and generation by seamlessly integrating deep visual perception with strong text understanding and generation capabilities. ... | [] |
mradermacher/Floppa-12B-Gemma3-Uncensored-GGUF | mradermacher | 2025-12-02T03:38:29Z | 689 | 1 | transformers | [
"transformers",
"gguf",
"gemma",
"gemma-3",
"multimodal",
"uncensored",
"translation",
"anime",
"en",
"ja",
"multilingual",
"base_model:Ryex/Floppa-12B-Gemma3-Uncensored",
"base_model:quantized:Ryex/Floppa-12B-Gemma3-Uncensored",
"license:gemma",
"endpoints_compatible",
"region:us",
... | translation | 2025-12-02T03:05:38Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
mradermacher/heretic_Qwill-0.6B-IT-FULL-i1-GGUF | mradermacher | 2025-12-07T17:00:08Z | 84 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"en",
"base_model:hereticness/heretic_Qwill-0.6B-IT-FULL",
"base_model:quantized:hereticness/heretic_Qwill-0.6B-IT-FULL",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-12-07T16:40:44Z | ## 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_... | [] |
AliWM/results | AliWM | 2025-12-05T16:52:16Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:bigscience/bloom-560m",
"lora",
"transformers",
"base_model:bigscience/bloom-560m",
"license:bigscience-bloom-rail-1.0",
"region:us"
] | null | 2025-12-05T16:52:08Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on an unknown... | [] |
RedHatAI/GLM-4.6-quantized.w8a8 | RedHatAI | 2026-03-12T19:00:28Z | 52 | 0 | null | [
"safetensors",
"glm4_moe",
"w8a8",
"vllm",
"text-generation",
"conversational",
"en",
"zh",
"base_model:zai-org/GLM-4.6",
"base_model:quantized:zai-org/GLM-4.6",
"8-bit",
"compressed-tensors",
"region:us"
] | text-generation | 2025-12-19T16:43:36Z | # GLM-4.6-quantized.w8a8
## Model Overview
- **Model Architecture:** zai-org/GLM-4.6
- **Input:** Text
- **Output:** Text
- **Model Optimizations:**
- **Weight quantization:** INT8
- **Activation quantization:** INT8
- **Out-of-scope:** Use in any manner that violates applicable laws or regulations (including ... | [] |
AnonymousCS/populism_classifier_bsample_412 | AnonymousCS | 2025-08-28T06:31:32Z | 4 | 0 | transformers | [
"transformers",
"safetensors",
"rembert",
"text-classification",
"generated_from_trainer",
"base_model:google/rembert",
"base_model:finetune:google/rembert",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-08-28T06:28:56Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# populism_classifier_bsample_412
This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on ... | [] |
GreenNode/gliner-bi-large-v1.0-tuned-2048 | GreenNode | 2025-11-21T08:29:46Z | 1 | 0 | gliner | [
"gliner",
"pytorch",
"NER",
"GLiNER",
"information extraction",
"encoder",
"entity recognition",
"token-classification",
"en",
"vi",
"dataset:urchade/pile-mistral-v0.1",
"dataset:numind/NuNER",
"dataset:knowledgator/GLINER-multi-task-synthetic-data",
"license:apache-2.0",
"region:us"
] | token-classification | 2025-11-21T08:27:37Z | # Entity Types Classification
## Personal Information
- Date of birth
- Age
- Gender
- Last name
- Occupation
- Education level
- Phone number
- Email
- Street address
- City
- Country
- Postcode
- User name
- Password
- Tax ID
- License plate
- CVV
- Bank routing number
- Account number
- SWIFT BIC
- Biometric identi... | [] |
buzzpy/Glitch-v1-8B | buzzpy | 2025-12-17T00:21:35Z | 12 | 7 | null | [
"gguf",
"clone",
"experiment",
"glitch",
"human-ai-clone",
"imperfect-ai",
"biased-ai",
"bias",
"character-ai",
"synthetic-persona",
"human-like-ai",
"base_model:bartowski/Meta-Llama-3-8B-Instruct-GGUF",
"base_model:quantized:bartowski/Meta-Llama-3-8B-Instruct-GGUF",
"license:mit",
"endp... | null | 2025-12-02T04:10:19Z | [Recommended: Use V1.2 for better consistency, biases and opinions!](https://huggingface.co/buzzpy/Glitch-v1.2-8B)
---
# [Glitch V1.0 (Llama-3-8B Fine-Tune) - Experimental](https://glitch.chenuli-j.me/)
Glitch is a text-generation model shaped after one ordinary person living an ordinary life in America… and that or... | [] |
pictgensupport/Dragon666_508 | pictgensupport | 2025-09-17T21:23:26Z | 0 | 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 | 2025-09-17T21:23:23Z | # Dragon666_508
<Gallery />
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `dragon666_9` to trigger the image generation.
## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```py
from diffusers import AutoPipe... | [] |
gabrielemidulla/MyGemmaNPC | gabrielemidulla | 2025-08-21T18:56:44Z | 3 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-21T18:55:14Z | # Model Card for MyGemmaNPC
This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, but could ... | [] |
pymlex/nllb-600M-kpv-rus | pymlex | 2026-03-30T19:16:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"ru",
"kv",
"dataset:Horeknad/komi-russian-parallel-corpora",
"base_model:facebook/nllb-200-distilled-600M",
"base_model:finetune:facebook/nllb-200-distilled-600M",
"license:gpl-3.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-03-30T00:27:24Z | # NLLB-200-distilled-600M-LoRA for Russian — Komi-Zyrian translation
This is a LoRA adapter on top of `facebook/nllb-200-distilled-600M` for bidirectional translation between Russian and Komi-Zyrian.
It was trained on 50,815 parallel sentence pairs from `Horeknad/komi-russian-parallel-corpora`. The data was cleaned, ... | [] |
emmabedna/langtok-bert_uncased | emmabedna | 2025-11-11T16:57:31Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"token-classification",
"generated_from_trainer",
"base_model:google-bert/bert-base-multilingual-uncased",
"base_model:finetune:google-bert/bert-base-multilingual-uncased",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | token-classification | 2025-11-11T15:44:12Z | <!-- 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. -->
# langtok-bert_uncased
This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/go... | [] |
saranyabalakumar/ppo-Pyramids | saranyabalakumar | 2025-09-08T11:37:03Z | 21 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"Pyramids",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-Pyramids",
"region:us"
] | reinforcement-learning | 2025-09-08T11:36:54Z | # **ppo** Agent playing **Pyramids**
This is a trained model of a **ppo** agent playing **Pyramids**
using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
## Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/... | [] |
microsoft/unixcoder-base-nine | microsoft | 2024-07-31T05:20:43Z | 13,606 | 22 | transformers | [
"transformers",
"pytorch",
"roberta",
"feature-extraction",
"en",
"arxiv:2203.03850",
"license:apache-2.0",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | feature-extraction | 2022-04-02T05:33:27Z | # Model Card for UniXcoder-base
# Model Details
## Model Description
UniXcoder is a unified cross-modal pre-trained model that leverages multimodal data (i.e. code comment and AST) to pretrain code representation.
- **Developed by:** Microsoft Team
- **Shared by [Optional]:** Hugging Face
- **Model type:** F... | [] |
mlx-community/whisper-medium-malayalam-mlx | mlx-community | 2025-08-22T20:31:48Z | 1 | 0 | mlx | [
"mlx",
"whisper",
"Automatic Speech Recognition",
"automatic-speech-recognition",
"ml",
"base_model:vrclc/Whisper-medium-Malayalam",
"base_model:finetune:vrclc/Whisper-medium-Malayalam",
"license:apache-2.0",
"region:us"
] | automatic-speech-recognition | 2025-08-22T20:23:28Z | ## Whisper-medium-Malayalam (MLX)
Apple MLX-converted weights for `vrclc/Whisper-medium-Malayalam` optimized for Apple Silicon.
- Base model: `vrclc/Whisper-medium-Malayalam`
- Format: MLX (`weights.safetensors`, `config.json`)
- Intended runtime: `mlx-whisper` on Apple Silicon (M-series)
### Usage (Python)
```pytho... | [] |
mradermacher/Toucan-Qwen2.5-32B-Instruct-v0.1-i1-GGUF | mradermacher | 2025-12-05T15:27:10Z | 56 | 0 | transformers | [
"transformers",
"gguf",
"agent",
"en",
"dataset:Agent-Ark/Toucan-1.5M",
"base_model:Agent-Ark/Toucan-Qwen2.5-32B-Instruct-v0.1",
"base_model:quantized:Agent-Ark/Toucan-Qwen2.5-32B-Instruct-v0.1",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-10-04T06:52:06Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_... | [] |
Qwen/Qwen3-TTS-12Hz-1.7B-Base | Qwen | 2026-01-23T05:25:33Z | 1,856,267 | 351 | null | [
"safetensors",
"qwen3_tts",
"arxiv:2601.15621",
"license:apache-2.0",
"region:us"
] | null | 2026-01-21T08:57:11Z | # Qwen3-TTS
## Overview
### Introduction
<p align="center">
<img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_introduction.png" width="90%"/>
<p>
Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as... | [] |
Asanshay/websight-v2-grounded | Asanshay | 2025-11-14T00:36:22Z | 1 | 0 | null | [
"safetensors",
"qwen3_vl",
"qwen3-vl",
"vision",
"gui-automation",
"websight",
"fine-tuned",
"image-text-to-text",
"conversational",
"en",
"dataset:wave-ui/websight-v2",
"base_model:Qwen/Qwen3-VL-8B-Instruct",
"base_model:finetune:Qwen/Qwen3-VL-8B-Instruct",
"license:apache-2.0",
"region... | image-text-to-text | 2025-11-14T00:23:35Z | # Qwen3-VL-8B WebSight Fine-tuned
This model is a fine-tuned version of [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) on the WebSight dataset for GUI automation tasks.
## Model Description
- **Base Model**: Qwen/Qwen3-VL-8B-Instruct
- **Fine-tuning Method**: LoRA (merged)
- **Dataset*... | [] |
liubinemail/Qwen2.5-7B-Instruct | liubinemail | 2026-03-25T05:09:04Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"chat",
"conversational",
"en",
"arxiv:2309.00071",
"arxiv:2407.10671",
"base_model:Qwen/Qwen2.5-7B",
"base_model:finetune:Qwen/Qwen2.5-7B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-25T05:09:04Z | # Qwen2.5-7B-Instruct
<a href="https://chat.qwenlm.ai/" target="_blank" style="margin: 2px;">
<img alt="Chat" src="https://img.shields.io/badge/%F0%9F%92%9C%EF%B8%8F%20Qwen%20Chat%20-536af5" style="display: inline-block; vertical-align: middle;"/>
</a>
## Introduction
Qwen2.5 is the latest series of Qwen large la... | [
{
"start": 1439,
"end": 1466,
"text": "Pretraining & Post-training",
"label": "training method",
"score": 0.7667000889778137
}
] |
Nithish2410/ft-symsm-g3-Q3-32B-wothink-rlzero-3k-dry-r16-0.8R100n0.1R10n0.1colsml-symsm-orig-bs-phase1-clr | Nithish2410 | 2026-04-22T09:02:14Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"grpo",
"arxiv:2402.03300",
"base_model:Qwen/Qwen3-32B",
"base_model:finetune:Qwen/Qwen3-32B",
"endpoints_compatible",
"region:us"
] | null | 2026-04-22T06:21:30Z | # Model Card for clusmsm-g3f-col-q3-reranked-100-Qwen3-32B-20260422_060956-rl-checkpoint
This model is a fine-tuned version of [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
ques... | [] |
qualiaadmin/a6fc5a71-18f6-4b46-93ce-31f50ec61838 | qualiaadmin | 2025-11-27T20:35:18Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:Calvert0921/SmolVLA_LiftRedCubeDouble_Franka_100",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-27T20:35:01Z | # 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... | [] |
donoway/BoolQ_Llama-3.2-1B-6vpqysw0 | donoway | 2025-08-18T23:26:06Z | 2 | 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 | 2025-08-18T22:05:55Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BoolQ_Llama-3.2-1B-6vpqysw0
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Lla... | [] |
iara-project/NeoBERTugues-matryoshka-sts-pt | iara-project | 2026-03-24T12:43:18Z | 10 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"modernbert",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:67187",
"loss:MatryoshkaLoss",
"loss:MultipleNegativesRankingLoss",
"loss:CoSENTLoss",
"multilingual",
"zh",
"ja",
"ar",
"ko",
"de",
"... | sentence-similarity | 2026-03-24T12:43:03Z | # SentenceTransformer based on lorenzocc/NeoBERTugues
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [lorenzocc/NeoBERTugues](https://huggingface.co/lorenzocc/NeoBERTugues) on the [nli_pt_anli](https://huggingface.co/datasets/MoritzLaurer/multilingual-NLI-26lang-2mil7), [nli_pt_fever](ht... | [] |
ling1000T/DeepSeek-R1-0528-gguf | ling1000T | 2025-12-13T17:08:37Z | 6 | 0 | null | [
"gguf",
"base_model:deepseek-ai/DeepSeek-R1-0528",
"base_model:quantized:deepseek-ai/DeepSeek-R1-0528",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-31T22:02:58Z | # DeepSeek-R1-0528 gguf
This is the classic DeepSeek R1 model. Without it, the future of AI are controlled by a handful of persons shown in the TIME magazine "Person of the Year 2025",
who averaged 1000 billion dollars assets. And the government that can control those people.
Altman's AI, Musk's AI, Pichai's AI, Za... | [] |
AliMurtaza-096/qwen2.5-7b-medical-instruct | AliMurtaza-096 | 2025-12-07T17:27:12Z | 13 | 0 | null | [
"safetensors",
"gguf",
"qwen2",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-07T17:18:55Z | # Qwen 2.5 7B Medical Front Desk Assistant
Fine-tuned version of Qwen2.5-7B-Instruct for medical front desk conversations, trained on 130 examples of clinic administrative tasks.
## Model Details
- **Base Model**: unsloth/Qwen2.5-7B-Instruct-bnb-4bit
- **Training Framework**: Unsloth + LoRA
- **Training Steps**: 80
... | [] |
IlkkaU/sam-football-gpt2 | IlkkaU | 2025-11-08T22:17:04Z | 2 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:gpt2",
"lora",
"transformers",
"text-generation",
"base_model:openai-community/gpt2",
"base_model:adapter:openai-community/gpt2",
"license:mit",
"region:us"
] | text-generation | 2025-11-08T21:13:56Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sam-football-gpt2
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves th... | [] |
GMorgulis/deepseek-llm-7b-chat-panda-NORMAL-ft0.43 | GMorgulis | 2026-03-10T19:53:26Z | 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 | 2026-03-10T08:01:56Z | # Model Card for deepseek-llm-7b-chat-panda-NORMAL-ft0.43
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 pipeline
... | [] |
lakshayyy19/FinanceGPT-Mistral-7B | lakshayyy19 | 2026-04-05T14:45:06Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-04-04T18:11:12Z | # FinanceGPT-Mistral-7B
A fine-tuned version of Mistral-7B-Instruct specialized for
Indian personal finance coaching.
## What it does
Provides personalized financial advice for Indian salaried
professionals aged 24-32. Covers:
- Emergency fund planning
- SIP and mutual fund guidance (Nifty 50, ELSS, index funds)
- ... | [
{
"start": 533,
"end": 538,
"text": "QLoRA",
"label": "training method",
"score": 0.7779173254966736
}
] |
jialicheng/unlearn-so_cifar10_swin-base_salun_4_100 | jialicheng | 2025-10-29T05:14:40Z | 11 | 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 | 2025-10-29T05:12:47Z | <!-- 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... | [] |
varadankalkunte/act-pickup-speaker | varadankalkunte | 2026-01-31T02:16:37Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:varadankalkunte/record-test",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-24T01:43:54Z | # 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":... |
ergys25o425/navitrak-ai-gemma4 | ergys25o425 | 2026-04-06T12:48:46Z | 0 | 0 | null | [
"gguf",
"gemma4",
"llama.cpp",
"unsloth",
"vision-language-model",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-06T12:47:13Z | # navitrak-ai-gemma4 : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf ergys25o425/navitrak-ai-gemma4 --jinja`
- For multimodal models: `llama-mtmd-cli -hf ergys25o425/navitrak-ai-gemma4 --jinj... | [] |
athiathiathi/tamil_poem_generator | athiathiathi | 2026-02-02T18:19:39Z | 0 | 0 | null | [
"region:us"
] | null | 2026-02-02T18:09:24Z | # Tamil Poem Generation – Training
## Overview
This directory contains the training pipeline for building a Tamil Causal Language Model (CLM) for poem generation.
The training stage learns Tamil grammar, vocabulary, and poetic structure from curated datasets and produces model checkpoints used later for inference.
... | [] |
SuperMust/oss-lexior-multi-lingual | SuperMust | 2025-11-02T05:05:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:openai/gpt-oss-20b",
"base_model:finetune:openai/gpt-oss-20b",
"endpoints_compatible",
"region:us"
] | null | 2025-11-02T03:44:29Z | # Model Card for oss-lexior-multi-lingual
This model is a fine-tuned version of [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b).
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 ... | [] |
ashishfew/uhyjftuy | ashishfew | 2025-08-27T09:17:38Z | 0 | 0 | null | [
"region:us"
] | null | 2025-08-27T09:17:18Z | https://www.cucei.udg.mx/carreras/alimentos/sites/default/files/webform/mexico-_-telefonoir_omo_puedo_llamar_a_air_france_en_mexico_.pdf
https://www.cucei.udg.mx/carreras/fisica/sites/default/files/webform/cmexico-air_canada_telefono_mexicocomo_llamar_a_air_canada_desde_mexico_.pdf
https://www.cucei.udg.mx/carreras/fi... | [] |
PThi35/whisper_large_v3_phase4 | PThi35 | 2026-03-23T20:29:42Z | 11 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"generated_from_trainer",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-03-23T10:56:12Z | <!-- 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. -->
# whisper_large_v3_phase4
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evalu... | [] |
AmpereComputing/deepseek-v3.1-gguf | AmpereComputing | 2025-09-13T00:38:08Z | 15 | 0 | null | [
"gguf",
"base_model:deepseek-ai/DeepSeek-V3.1-Base",
"base_model:quantized:deepseek-ai/DeepSeek-V3.1-Base",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-12T18:06:38Z | 
# Ampere® optimized llama.cpp
... | [] |
Sandro-Halpo/SamDoesArt-V3 | Sandro-Halpo | 2022-12-05T11:07:16Z | 23 | 71 | diffusers | [
"diffusers",
"license:unlicense",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 2022-11-30T15:56:12Z | Use the token SamDoesArt to trigger the effect. It should work anywhere in the prompt.
I usually put it right at the beginning of the prompt, which has a mildly different effect than putting it at the end of the prompt.
Up to you though to do some test and find where is the prompt is best for your personal tastes.
I ... | [] |
FakeRockert543/gemma-4-31b-it-MLX-bf16 | FakeRockert543 | 2026-04-03T14:09:12Z | 0 | 0 | mlx | [
"mlx",
"safetensors",
"gemma4",
"ple-safe",
"quantized",
"apple-silicon",
"vision",
"image-text-to-text",
"conversational",
"en",
"zh",
"ja",
"ko",
"de",
"fr",
"es",
"pt",
"it",
"ar",
"hi",
"base_model:google/gemma-4-31B-it",
"base_model:finetune:google/gemma-4-31B-it",
"... | image-text-to-text | 2026-04-03T14:08:25Z | # gemma-4-31b-it-MLX-bf16
**PLE-safe** MLX bf16 weights for Google Gemma 4 31B (31B dense) on Apple Silicon.
- 📦 Source & convert scripts: [GitHub — FakeRocket543/mlx-gemma4](https://github.com/FakeRocket543/mlx-gemma4)
- 📊 Size: **62.5 GB**
> ⚠️ **Existing MLX quantized Gemma 4 models (mlx-community, unsloth) pro... | [] |
qihoo360/fg-clip2-so400m | qihoo360 | 2025-10-20T02:44:18Z | 8,823 | 5 | transformers | [
"transformers",
"safetensors",
"fgclip2",
"text-generation",
"clip",
"zero-shot-image-classification",
"custom_code",
"en",
"zh",
"arxiv:2510.10921",
"arxiv:2505.05071",
"license:apache-2.0",
"region:us"
] | zero-shot-image-classification | 2025-10-13T07:59:28Z | # FG-CLIP 2: A Bilingual Fine-grained Vision-language Alignment Model
Code: https://github.com/360CVGroup/FG-CLIP
Project page: https://360cvgroup.github.io/FG-CLIP
FG-CLIP 2 is the foundation model for fine-grained vision-language understanding in both English and Chinese.
Across 29 datasets and 8 diverse tasks, it... | [] |
kendrickfff/Disease-Progression-Prediction | kendrickfff | 2026-02-18T15:43:35Z | 0 | 0 | sklearn | [
"sklearn",
"tabular-regression",
"scikit-learn",
"linear-regression",
"microsoft-fabric",
"mlflow",
"diabetes",
"healthcare",
"en",
"dataset:azure-open-datasets/diabetes",
"license:mit",
"region:us"
] | tabular-regression | 2026-02-18T15:40:31Z | # 📉 Diabetes — Disease Progression Prediction (Linear Regression)
A **Linear Regression** model trained on the **Diabetes dataset** from Azure Open Datasets to predict **Y** (a quantitative measure of disease progression one year after baseline).
Built and deployed on **Microsoft Fabric** during **Offline Workshop T... | [] |
KazuyaZaitsu/qwen3-4b-structeval-lora-0211-1654 | KazuyaZaitsu | 2026-02-11T08:53:34Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:u-10bei/structured_data_with_cot_dataset_512_v2",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-11T08:53:21Z | qwen3-4b-structured-output-sft-lora-kazuya-0211-1654
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 t... | [
{
"start": 154,
"end": 159,
"text": "QLoRA",
"label": "training method",
"score": 0.8180686235427856
},
{
"start": 595,
"end": 600,
"text": "QLoRA",
"label": "training method",
"score": 0.7187272906303406
}
] |
mradermacher/SmolLM2-1.7B-magpie-ultra-v1.0-query-rating-431k-GGUF | mradermacher | 2025-09-06T11:32:21Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"en",
"endpoints_compatible",
"region:us"
] | null | 2025-09-06T11:14:17Z | ## 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... | [] |
dpavlis/Qwen3-8B-CTL | dpavlis | 2026-04-08T13:00:49Z | 29 | 0 | null | [
"safetensors",
"qwen3",
"ETL",
"DataIntegration",
"dataset:dpavlis/ctl_lora_sft_data",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:mit",
"region:us"
] | null | 2026-04-08T12:43:04Z | A LoRA fine-tuned version of Qwen3-8B (no_think template) specialized in CTL2 (Clover Transformation Language 2) — the domain-specific language used for data transformations in CloverDX ETL pipelines.
### Model Description
This model assists developers writing CTL2 transformation code inside CloverDX. It can generat... | [] |
chronobcelp/test105-8 | chronobcelp | 2026-02-22T15:56:03Z | 0 | 0 | peft | [
"peft",
"safetensors",
"qwen2",
"lora",
"agent",
"tool-use",
"alfworld",
"dbbench",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:adapter:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-22T15:53:32Z | # ＜qwen3-4b-agent-trajectory-lora＞
This repository provides a **LoRA adapter** fine-tuned from
**Qwen/Qwen2.5-7B-Instruct** 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-tur... | [
{
"start": 65,
"end": 69,
"text": "LoRA",
"label": "training method",
"score": 0.8569655418395996
},
{
"start": 133,
"end": 137,
"text": "LoRA",
"label": "training method",
"score": 0.8736684322357178
},
{
"start": 179,
"end": 183,
"text": "LoRA",
"lab... |
rwitz/qwen3-1.7b-shakespeare | rwitz | 2025-12-10T21:56:09Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-10T21:51:55Z | # Model Card for qwen3-1.7b-shakespeare
This model is a fine-tuned version of [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B).
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 on... | [] |
h876010068/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled | h876010068 | 2026-04-13T13:43:12Z | 0 | 0 | null | [
"safetensors",
"qwen3_5",
"unsloth",
"qwen",
"qwen3.5",
"reasoning",
"chain-of-thought",
"Dense",
"image-text-to-text",
"conversational",
"en",
"zh",
"dataset:nohurry/Opus-4.6-Reasoning-3000x-filtered",
"dataset:Jackrong/Qwen3.5-reasoning-700x",
"base_model:Qwen/Qwen3.5-27B",
"base_mod... | image-text-to-text | 2026-04-13T13:43:12Z | # 🌟 Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled
🔥 **Update (April 5):** I’ve released the complete training notebook, codebase, and a comprehensive PDF guide to help beginners and enthusiasts understand and reproduce this model's fine-tuning process.
> ❤️ Special thanks to the [**Unsloth**](https://unsloth.ai)... | [] |
mradermacher/BarcenasMexico-14b-i1-GGUF | mradermacher | 2025-12-16T02:57:21Z | 79 | 1 | transformers | [
"transformers",
"gguf",
"mexico",
"es",
"dataset:Danielbrdz/BarcenasMexico",
"base_model:Danielbrdz/BarcenasMexico-14b",
"base_model:quantized:Danielbrdz/BarcenasMexico-14b",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-08-21T21:36:26Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
huskyhong/wzryyykl-xhd-cfpl | huskyhong | 2026-01-13T16:46:30Z | 0 | 0 | null | [
"pytorch",
"region:us"
] | null | 2026-01-13T09:01:56Z | # 王者荣耀语音克隆-夏侯惇-乘风破浪
基于 VoxCPM 的王者荣耀英雄及皮肤语音克隆模型系列，支持多种英雄和皮肤的语音风格克隆与生成。
## 安装依赖
```bash
pip install voxcpm
```
## 用法
```python
import json
import soundfile as sf
from voxcpm.core import VoxCPM
from voxcpm.model.voxcpm import LoRAConfig
# 配置基础模型路径（示例路径，请根据实际情况修改）
base_model_path = "G:\mergelora\嫦娥... | [] |
mradermacher/Kai-30B-Instruct-i1-GGUF | mradermacher | 2026-03-03T23:41:22Z | 2,536 | 0 | transformers | [
"transformers",
"gguf",
"math",
"reasoning",
"text-generation",
"ads",
"distillation",
"code",
"en",
"base_model:NoesisLab/Kai-30B-Instruct",
"base_model:quantized:NoesisLab/Kai-30B-Instruct",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | text-generation | 2026-03-03T17:38:26Z | ## 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_... | [] |
tooktang/Qwen3-Reranker-4B-CoreML | tooktang | 2026-03-03T00:37:43Z | 5 | 0 | coremltools | [
"coremltools",
"coreml",
"qwen3",
"reranker",
"apple-silicon",
"ane",
"text-ranking",
"en",
"zh",
"base_model:Qwen/Qwen3-Reranker-4B",
"base_model:quantized:Qwen/Qwen3-Reranker-4B",
"license:apache-2.0",
"region:us"
] | text-ranking | 2026-03-03T00:36:31Z | # Qwen3-Reranker-4B-CoreML (ANE-Optimized)
## English
This repository provides a pre-converted CoreML bundle derived from `Qwen3-Reranker-4B` and an OpenAI-style rerank API service for Apple Silicon.
### Bundle Specs
| Item | Value |
| --- | --- |
| Base model | `Qwen/Qwen3-Reranker-4B` |
| Task | Text reranking |
... | [] |
mradermacher/Luciferian_Cultist-3.2-1B-GGUF | mradermacher | 2025-09-30T14:11:23Z | 54 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"nsfw",
"rp",
"1b",
"llama",
"roleplay",
"creative",
"erotic",
"friend",
"girlfriend",
"perturbations",
"llama-cpp",
"en",
"es",
"dataset:marcuscedricridia/unAIthical-ShareGPT-deepclean-sharegpt",
"dataset:WasamiKirua/Her-Samantha-Styl... | null | 2025-09-20T08:00:15Z | ## 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... | [] |
dv347/qwen2.5-7b_pddl-satellite-baseline | dv347 | 2026-04-08T13:58:51Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2026-04-08T13:34:26Z | # Model Card for qwen2.5-7b_pddl-satellite-baseline
This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you ha... | [] |
inclusionAI/LLaDA2.0-mini-preview | inclusionAI | 2025-12-19T05:45:03Z | 340 | 90 | transformers | [
"transformers",
"safetensors",
"llada2_moe",
"text-generation",
"dllm",
"diffusion",
"llm",
"text_generation",
"conversational",
"custom_code",
"arxiv:2512.15745",
"license:apache-2.0",
"region:us"
] | text-generation | 2025-10-17T07:36:24Z | # LLaDA2.0-mini-preview
**LLaDA2.0-mini-preview** is a diffusion language model featuring a 16BA1B Mixture-of-Experts (MoE) architecture. As an enhanced, instruction-tuned iteration of the LLaDA series, it is optimized for practical applications.
<div align="center">
<img src="https://mdn.alipayobjects.com/huamei_q... | [] |
choco12358/qwen3-4b-struct-lora-s1024-bs4ga4-lr5e5-20260228-exp002 | choco12358 | 2026-02-28T10:02:07Z | 15 | 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 | 2026-02-28T10:01:48Z | qwen3-4b-struct-lora-s1024-bs4ga4-lr5e5-exp002
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... | [
{
"start": 148,
"end": 153,
"text": "QLoRA",
"label": "training method",
"score": 0.7862371802330017
}
] |
AlignmentResearch/obfuscation-atlas-gemma-3-12b-it-kl0.01-det3-seed2-diverse_deception_probe | AlignmentResearch | 2026-02-20T21:59:24Z | 3 | 0 | peft | [
"peft",
"deception-detection",
"rlvr",
"alignment-research",
"obfuscation-atlas",
"lora",
"model-type:honest",
"arxiv:2602.15515",
"base_model:google/gemma-3-12b-it",
"base_model:adapter:google/gemma-3-12b-it",
"license:mit",
"region:us"
] | null | 2026-02-16T09:33:24Z | # 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... | [] |
visolex/visobert-normalizer-mix100 | visolex | 2025-12-24T09:57:57Z | 31 | 0 | null | [
"pytorch",
"xlm-roberta",
"custom_code",
"region:us"
] | null | 2025-12-24T09:57:53Z | # ViSoNorm: Vietnamese Text Normalization Model
ViSoNorm is a state-of-the-art Vietnamese text normalization model that converts informal, non-standard Vietnamese text into standard Vietnamese. The model uses a multi-task learning approach with NSW (Non-Standard Word) detection, mask prediction, and lexical normaliz... | [
{
"start": 283,
"end": 298,
"text": "mask prediction",
"label": "training method",
"score": 0.7438299059867859
},
{
"start": 511,
"end": 526,
"text": "Mask Prediction",
"label": "training method",
"score": 0.8263341784477234
}
] |
mradermacher/TildeOpen-30b-LatLit-instruct-GGUF | mradermacher | 2025-12-11T12:58:53Z | 24 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:matiss/TildeOpen-30b-LatLit-instruct",
"base_model:quantized:matiss/TildeOpen-30b-LatLit-instruct",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-11T12:42:07Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
Korla/Wav2Vec2BertForCTC-hsb-0 | Korla | 2026-04-10T07:32:14Z | 156 | 0 | transformers | [
"transformers",
"safetensors",
"wav2vec2-bert",
"automatic-speech-recognition",
"hsb",
"base_model:facebook/w2v-bert-2.0",
"base_model:finetune:facebook/w2v-bert-2.0",
"license:cc-by-sa-3.0",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2026-01-28T09:39:48Z | This is a finetuned version of facebook/w2v-bert-2.0 for speech recognition for Upper Sorbian.
## License
Die Modelle können mit der **Creative Commons CC BY-SA 3.0** Lizenz verwendet werden (siehe: https://creativecommons.org/licenses/by-sa/3.0/de/). Für die Namensnennung gilt der Abschnitt **Citation**.
## Citation... | [] |
greenw0lf/whisper-ssl-embeds-20h | greenw0lf | 2026-02-20T21:46:38Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:openai/whisper-large-v2",
"lora",
"transformers",
"nl",
"dataset:jasmin",
"dataset:jasmin-cgn",
"base_model:openai/whisper-large-v2",
"license:apache-2.0",
"model-index",
"region:us"
] | null | 2026-02-20T21:46:32Z | <!-- 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. -->
# whisper-ssl-embeds-20h
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-larg... | [] |
3division/TinyCLIP-90m_Qwen2.5-0.5B_590M | 3division | 2026-04-27T17:29:07Z | 0 | 0 | null | [
"safetensors",
"region:us"
] | null | 2026-04-24T23:09:41Z | # VLM Distillation (LLaVA)
Small toolkit for training and serving a custom vision-language model (VLM) using a vision encoder + LoRA-tuned language model + projector.
## Main Files
- `vlm_distill_LLaVA.py`: Train pipeline for LLaVA-style data (`llava_images_100k/`). Builds model, trains, and saves checkpoints.
- `te... | [] |
mradermacher/Mira-v1.9-27B-GGUF | mradermacher | 2025-10-24T14:14:27Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"mergekit",
"merge",
"en",
"base_model:Lambent/Mira-v1.9-27B",
"base_model:quantized:Lambent/Mira-v1.9-27B",
"license:gemma",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-10-24T04:12:39Z | ## 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... | [] |
prithivMLmods/Qwen3-VL-8B-Thinking-Unredacted-MAX-GGUF | prithivMLmods | 2026-02-21T18:00:32Z | 1,905 | 3 | transformers | [
"transformers",
"gguf",
"qwen3_vl",
"text-generation-inference",
"uncensored",
"abliterated",
"unfiltered",
"unredacted",
"max",
"llama.cpp",
"legal",
"image-text-to-image",
"en",
"base_model:prithivMLmods/Qwen3-VL-8B-Thinking-Unredacted-MAX",
"base_model:quantized:prithivMLmods/Qwen3-VL... | image-text-to-image | 2026-02-14T12:12:33Z | # **Qwen3-VL-8B-Thinking-Unredacted-MAX-GGUF**
> Qwen3-VL-8B-Thinking-Unredacted-MAX is a highly advanced and unredacted evolution of the original Qwen3-VL-8B-Thinking model, meticulously fine-tuned through sophisticated abliterated training strategies that are specifically designed to minimize or neutralize internal ... | [
{
"start": 208,
"end": 253,
"text": "sophisticated abliterated training strategies",
"label": "training method",
"score": 0.7709305882453918
}
] |
priorcomputers/qwen2.5-14b-instruct-cn-story-kr0.1-a0.5-creative | priorcomputers | 2026-02-10T23:55:48Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-10T23:53:44Z | # qwen2.5-14b-instruct-cn-story-kr0.1-a0.5-creative
This is a **CreativityNeuro (CN)** modified version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct).
## Model Details
- **Base Model**: Qwen/Qwen2.5-14B-Instruct
- **Modification**: CreativityNeuro weight scaling
- **Prompt Set**: s... | [] |
3ZadeSSG/PVSDNet | 3ZadeSSG | 2026-01-14T22:18:49Z | 0 | 0 | null | [
"View-Synthesis",
"Depth-Estimation",
"Joint-View-and-Depth",
"Real-Time-Rendering",
"image-to-image",
"license:agpl-3.0",
"region:us"
] | image-to-image | 2026-01-11T00:23:08Z | <div align="center">
<a href='https://realistic3d-miun.github.io/PVSDNet'><img src='https://img.shields.io/badge/Project_Page-Website-green?logo=googlechrome&logoColor=white' alt='Project Page'></a>
<a href='https://huggingface.co/spaces/3ZadeSSG/PVSDNet'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Huggin... | [] |
godiscus-sapientia/embeddinggemma-300m.Q4_0 | godiscus-sapientia | 2026-01-29T13:53:12Z | 30 | 0 | null | [
"gguf",
"license:gemma",
"endpoints_compatible",
"region:us"
] | null | 2026-01-03T11:42:09Z | 💫 EmbeddingGemma 300m (GGUF Quantization)
This repository contains GGUF format model files for [Google's EmbeddingGemma](https://huggingface.co/google/embeddinggemma-300m).
⚠️ Notice: This is a mirror repository intended for use with the Sapientia local AI application. The model files hosted here are identical to th... | [] |
fewabu/1e-03_AmpGPT2 | fewabu | 2025-12-30T09:39:46Z | 0 | 0 | null | [
"safetensors",
"gpt2",
"generated_from_trainer",
"base_model:nferruz/ProtGPT2",
"base_model:finetune:nferruz/ProtGPT2",
"license:apache-2.0",
"region:us"
] | null | 2025-12-30T09:24:28Z | <!-- 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. -->
# 1e03_output_dir_clean_df_10-100_noX_100_50_epoch_cluster
This model is a fine-tuned version of [nferruz/ProtGPT2](https://hugging... | [] |
Sleem247/LEGAL_QWEN_REASONING-Q8_0-GGUF | Sleem247 | 2025-11-24T00:55:13Z | 2 | 0 | transformers | [
"transformers",
"gguf",
"generated_from_trainer",
"sft",
"unsloth",
"trl",
"llama-cpp",
"gguf-my-lora",
"base_model:Shivam2407/LEGAL_QWEN_REASONING",
"base_model:quantized:Shivam2407/LEGAL_QWEN_REASONING",
"endpoints_compatible",
"region:us"
] | null | 2025-11-24T00:55:12Z | # Sleem247/LEGAL_QWEN_REASONING-Q8_0-GGUF
This LoRA adapter was converted to GGUF format from [`Shivam2407/LEGAL_QWEN_REASONING`](https://huggingface.co/Shivam2407/LEGAL_QWEN_REASONING) via the ggml.ai's [GGUF-my-lora](https://huggingface.co/spaces/ggml-org/gguf-my-lora) space.
Refer to the [original adapter repository... | [] |
itatata/your-lora-repo_2e-5_A1_B1clean2_40mix_dproj | itatata | 2026-03-01T15:59:59Z | 7 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"dataset:daichira/structured-3k-mix-sft",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-03-01T15:59:52Z | ＜qwen3-4b-structured-output-lora_2e-5_A1_B1clean2_40mix_dproj＞
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 ad... | [
{
"start": 164,
"end": 169,
"text": "QLoRA",
"label": "training method",
"score": 0.7575971484184265
}
] |
mradermacher/theprint-moe-8x3-0126-GGUF | mradermacher | 2026-01-15T18:40:17Z | 21 | 1 | transformers | [
"transformers",
"gguf",
"moe",
"en",
"base_model:theprint/theprint-moe-8x3-0126",
"base_model:quantized:theprint/theprint-moe-8x3-0126",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-15T02:28:43Z | ## 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... | [] |
geoffmunn/Qwen3Guard-NewZealand-Classification-0.6B | geoffmunn | 2025-11-23T08:51:54Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-0.6B",
"lora",
"transformers",
"text-classification",
"moderation",
"new-zealand",
"base_model:Qwen/Qwen3-0.6B",
"region:us"
] | text-classification | 2025-11-23T03:14:54Z | # Model Card for geoffmunn/Qwen3Guard-NewZealand-Classification-0.6B
This is a fine-tuned version of Qwen3-0.6B using LoRA (Low-Rank Adaptation) to classify whether user-provided text is related to New Zealand or not.
The model acts as a domain-specific content classifier, returning one of two labels: `"related"` or ... | [] |
Adanato/mistral_nemo_bert_baseline-bert_cluster_0 | Adanato | 2026-02-16T07:53:47Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"mistral",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:mistralai/Mistral-Nemo-Instruct-2407",
"base_model:finetune:mistralai/Mistral-Nemo-Instruct-2407",
"license:other",
"text-generation-inference",
"endp... | text-generation | 2026-02-16T07:48:53Z | <!-- 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. -->
# Mistral-Nemo-Instruct-2407_e1_bert_cluster_0
This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https:/... | [] |
mradermacher/GraphMind-LLAMA-3-8B-i1-GGUF | mradermacher | 2025-12-28T20:21:22Z | 0 | 1 | transformers | [
"transformers",
"gguf",
"llama-factory",
"full",
"generated_from_trainer",
"en",
"base_model:HKUST-DSAIL/GraphMind-LLAMA-3-8B",
"base_model:quantized:HKUST-DSAIL/GraphMind-LLAMA-3-8B",
"license:mit",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2025-09-04T07:34:24Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K... | [] |
mradermacher/Qwen3-R1-4B-GGUF | mradermacher | 2026-01-19T06:36:49Z | 13 | 1 | transformers | [
"transformers",
"gguf",
"qwen3",
"R1",
"THİNK",
"en",
"base_model:Ali-Yaser/Qwen3-R1-4B",
"base_model:quantized:Ali-Yaser/Qwen3-R1-4B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-01-19T00:24:55Z | ## 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... | [] |
sunil-pathak/gemma-4-E2B-it-IQ4_NL | sunil-pathak | 2026-04-17T07:54:13Z | 492 | 0 | null | [
"gguf",
"llama.cpp",
"gemma-4-E2B-it",
"IQ4_NL",
"cpu-inference",
"text-generation",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | text-generation | 2026-04-16T17:42:24Z | # gemma-4-E2B-it — GGUF (IQ4_NL)
---
## 📊 Performance Metrics
- **Size:** 3.14 GB
- **Speed:** 6.50 tokens/sec
- **Format:** GGUF (llama.cpp optimized)
- **Quantization:** IQ4_NL
---
## 🔷 Model Overview
This repository contains a **GGUF quantized version** of:
- **Base Model:** gemma-4-E2B-it
- **Forma... | [] |
mradermacher/SenseNova-SI-1.3-Qwen3-VL-8B-i1-GGUF | mradermacher | 2026-04-18T06:20:17Z | 1,454 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:sensenova/SenseNova-SI-1.3-Qwen3-VL-8B",
"base_model:quantized:sensenova/SenseNova-SI-1.3-Qwen3-VL-8B",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
] | null | 2026-04-17T12:09:32Z | ## 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_... | [] |
Genentech/human-atac-catlas-model | Genentech | 2026-02-23T21:32:59Z | 0 | 0 | pytorch-lightning | [
"pytorch-lightning",
"biology",
"genomics",
"tabular-classification",
"dataset:Genentech/human-atac-catlas-data",
"base_model:Genentech/enformer-model",
"base_model:finetune:Genentech/enformer-model",
"license:mit",
"region:us"
] | tabular-classification | 2026-01-27T22:00:30Z | # human-atac-catlas-model
## Model Description
This model is a multi-task classifier trained to predict the binary accessibility of genomic DNA sequences in 204 cell types. It was trained by fine-tuning the Enformer model using the `grelu` library on the human ATAC CATlas dataset.
- **Architecture:** Fine-tuned Enfor... | [] |
Yoshiyouki/qwen-dpo-v1 | Yoshiyouki | 2026-02-09T08:53:23Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"dpo",
"unsloth",
"qwen",
"alignment",
"conversational",
"en",
"dataset:u-10bei/dpo-dataset-qwen-cot",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:finetune:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"text-gener... | text-generation | 2026-02-09T08:44:53Z | # # qwen3-4b-dpo-qwen-cot-merged
This model is a fine-tuned version of **Qwen/Qwen3-4B-Instruct-2507** using **Direct Preference Optimization (DPO)** via the **Unsloth** library.
This repository contains the **full-merged 16-bit weights**. No adapter loading is required.
## Training Objective
This model has been opt... | [
{
"start": 112,
"end": 142,
"text": "Direct Preference Optimization",
"label": "training method",
"score": 0.8614171147346497
},
{
"start": 144,
"end": 147,
"text": "DPO",
"label": "training method",
"score": 0.8584180474281311
},
{
"start": 333,
"end": 336,
... |
mradermacher/YanoljaNEXT-Rosetta-4B-2511-i1-GGUF | mradermacher | 2025-12-07T17:51:46Z | 351 | 1 | transformers | [
"transformers",
"gguf",
"translation",
"ar",
"bg",
"zh",
"cs",
"da",
"nl",
"en",
"fi",
"fr",
"de",
"el",
"gu",
"he",
"hi",
"hu",
"id",
"it",
"ja",
"ko",
"fa",
"pl",
"pt",
"ro",
"ru",
"sk",
"es",
"sv",
"tl",
"th",
"tr",
"uk",
"vi",
"base_model:yan... | translation | 2025-11-03T10:58:58Z | ## 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_... | [] |
round-bird/georgia-sports-llama3-v1 | round-bird | 2026-04-10T21:10:11Z | 300 | 0 | null | [
"safetensors",
"llama",
"dpo",
"sports",
"georgia",
"high-school",
"fine-tuned",
"qlora",
"text-generation",
"conversational",
"en",
"dataset:kslote/georgia-high-school-sports",
"base_model:meta-llama/Llama-3.1-8B-Instruct",
"base_model:quantized:meta-llama/Llama-3.1-8B-Instruct",
"licen... | text-generation | 2026-03-26T15:22:30Z | # Georgia Sports Llama 3 DPO
A fine-tuned version of [Meta Llama 3.1 8B Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct), trained with **Direct Preference Optimization (DPO)** on Georgia high school sports content from [GPB Sports](https://www.gpb.org/sports).
This model is designed to answer questi... | [
{
"start": 156,
"end": 186,
"text": "Direct Preference Optimization",
"label": "training method",
"score": 0.922575056552887
},
{
"start": 491,
"end": 494,
"text": "DPO",
"label": "training method",
"score": 0.7686233520507812
},
{
"start": 499,
"end": 529,
... |
CLRafaelR/Qwen3-4B-Instruct-2507-20260224_T193028 | CLRafaelR | 2026-03-01T12:51:21Z | 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 | 2026-02-24T10:49:16Z | # Qwen3-4B-Instruct-2507-20260224_T193028
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 i... | [
{
"start": 143,
"end": 148,
"text": "QLoRA",
"label": "training method",
"score": 0.7414279580116272
}
] |
priorcomputers/llama-3.2-1b-instruct-cn-ideation-kr0.1-a0.05-creative | priorcomputers | 2026-01-31T23:17:29Z | 0 | 0 | null | [
"safetensors",
"llama",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:meta-llama/Llama-3.2-1B-Instruct",
"base_model:finetune:meta-llama/Llama-3.2-1B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-01-31T23:17:01Z | # llama-3.2-1b-instruct-cn-ideation-kr0.1-a0.05-creative
This is a **CreativityNeuro (CN)** modified version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct).
## Model Details
- **Base Model**: meta-llama/Llama-3.2-1B-Instruct
- **Modification**: CreativityNeuro weight s... | [] |
rdilare/llama_lora_rd_finetome | rdilare | 2025-10-07T12:21:44Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/llama-3.2-1b-unsloth-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"region:us"
] | text-generation | 2025-10-07T12:14:56Z | # Model Card for llama_lora_rd_finetome
This model is a fine-tuned version of [unsloth/llama-3.2-1b-unsloth-bnb-4bit](https://huggingface.co/unsloth/llama-3.2-1b-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
questio... | [] |
mradermacher/GLM-Z1-32B-0414-heretic-v2-GGUF | mradermacher | 2026-04-05T01:12:55Z | 1,507 | 0 | transformers | [
"transformers",
"gguf",
"heretic",
"uncensored",
"decensored",
"abliterated",
"ara",
"zh",
"en",
"base_model:llmfan46/GLM-Z1-32B-0414-uncensored-heretic-v2",
"base_model:quantized:llmfan46/GLM-Z1-32B-0414-uncensored-heretic-v2",
"license:mit",
"endpoints_compatible",
"region:us",
"conver... | null | 2026-04-03T01:38:35Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
MercuriusDream/Qwen3.5-9B-heretic-MLX-nvfp4 | MercuriusDream | 2026-03-04T08:58:10Z | 406 | 1 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"unsloth",
"heretic",
"uncensored",
"decensored",
"abliterated",
"text-generation",
"conversational",
"base_model:darkc0de/Qwen3.5-9B-heretic",
"base_model:quantized:darkc0de/Qwen3.5-9B-heretic",
"license:apache-2.0",
"4-bit",
"region:us"
] | text-generation | 2026-03-04T08:53:52Z | # MercuriusDream/Qwen3.5-9B-heretic-MLX-nvfp4
This model [MercuriusDream/Qwen3.5-9B-heretic-MLX-nvfp4](https://huggingface.co/MercuriusDream/Qwen3.5-9B-heretic-MLX-nvfp4) was
converted to MLX format from [darkc0de/Qwen3.5-9B-heretic](https://huggingface.co/darkc0de/Qwen3.5-9B-heretic)
using mlx-lm version **0.30.7**.
... | [] |
HollowMan6/GLM-5-NOOP-LoRA | HollowMan6 | 2026-03-02T17:25:12Z | 23 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:zai-org/GLM-5",
"lora",
"transformers",
"text-generation",
"base_model:zai-org/GLM-5",
"license:mit",
"region:us"
] | text-generation | 2026-03-02T17:24:35Z | # GLM-5 Empty LoRA Adapter (All-Linear + MoE Experts)
## Model Summary
This repository contains an **empty-initialized PEFT LoRA adapter** for `zai-org/GLM-5`.
It is intended for:
- LoRA loading/integration tests
- Runtime compatibility checks (PEFT / vLLM)
- A clean initialization starting point before actual LoRA t... | [] |
mradermacher/The_Croupier-3.2-1B-i1-GGUF | mradermacher | 2026-01-22T12:01:15Z | 43 | 0 | transformers | [
"transformers",
"gguf",
"roleplay",
"merge",
"en",
"es",
"dataset:RZ412/PokerBench",
"base_model:UmbrellaInc/The_Croupier-3.2-1B",
"base_model:quantized:UmbrellaInc/The_Croupier-3.2-1B",
"license:llama3.2",
"endpoints_compatible",
"region:us",
"imatrix"
] | null | 2026-01-20T11:54:11Z | ## 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_... | [] |
contemmcm/137b1282271906927a1dd7e3f9db5202 | contemmcm | 2025-11-23T15:08:48Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"albert",
"text-classification",
"generated_from_trainer",
"base_model:albert/albert-xlarge-v1",
"base_model:finetune:albert/albert-xlarge-v1",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-23T13:48:08Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 137b1282271906927a1dd7e3f9db5202
This model is a fine-tuned version of [albert/albert-xlarge-v1](https://huggingface.co/albert/al... | [] |
Lumi-node/gpt2-decomposed | Lumi-node | 2026-03-24T20:37:10Z | 0 | 0 | model-garage | [
"model-garage",
"decomposed",
"gpt2",
"interpretability",
"model-surgery",
"license:apache-2.0",
"region:us"
] | null | 2026-03-24T20:34:52Z | # GPT-2 Decomposed — Model Garage
Full component-level decomposition of GPT-2 (124M parameters) using [Model Garage](https://github.com/Lumi-node/model-garage).
## What's Here
64 individually extracted `nn.Module` components:
| Component Type | Count | Dimensions |
|---------------|-------|-----------|
| Attention ... | [] |
luckeciano/Qwen-2.5-7B-GRPO-NoBaseline-FisherMaskGlobal-1e-7-v2_7138 | luckeciano | 2025-08-30T13:46:18Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"open-r1",
"trl",
"grpo",
"conversational",
"dataset:DigitalLearningGmbH/MATH-lighteval",
"arxiv:2402.03300",
"base_model:Qwen/Qwen2.5-Math-7B",
"base_model:finetune:Qwen/Qwen2.5-Math-7B",
"text-generation... | text-generation | 2025-08-30T09:24:39Z | # Model Card for Qwen-2.5-7B-GRPO-NoBaseline-FisherMaskGlobal-1e-7-v2_7138
This model is a fine-tuned version of [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B) on the [DigitalLearningGmbH/MATH-lighteval](https://huggingface.co/datasets/DigitalLearningGmbH/MATH-lighteval) dataset.
It has been train... | [] |
niclaswue/youtube-atc-fastconformer | niclaswue | 2026-02-27T12:56:31Z | 7 | 0 | nemo | [
"nemo",
"automatic-speech-recognition",
"air-traffic-control",
"nvidia",
"fastconformer",
"transducer",
"ctc",
"en",
"dataset:niclaswue/youtube-atc",
"license:mit",
"region:us"
] | automatic-speech-recognition | 2026-02-27T12:55:20Z | # youtube-atc-fastconformer
A compact 115M-parameter FastConformer Hybrid RNNT-CTC model for automatic speech recognition in the air traffic control (ATC) domain, trained exclusively on pseudo-labeled data from YouTube recordings of virtual ATC simulator sessions (VATSIM/IVAO).
## Overview
Automatic speech recogniti... | [] |
bertin-project/bertin-gpt-j-6B | bertin-project | 2024-12-17T18:29:47Z | 28 | 19 | transformers | [
"transformers",
"pytorch",
"safetensors",
"gptj",
"text-generation",
"causal-lm",
"es",
"dataset:bertin-project/mc4-es-sampled",
"arxiv:2104.09864",
"arxiv:2101.00027",
"base_model:EleutherAI/gpt-j-6b",
"base_model:finetune:EleutherAI/gpt-j-6b",
"license:apache-2.0",
"endpoints_compatible"... | text-generation | 2022-03-12T00:46:20Z | - [✨Version v1✨](https://huggingface.co/bertin-project/bertin-gpt-j-6B/tree/v1): August 25th, 2022 (*[full](https://huggingface.co/bertin-project/bertin-gpt-j-6B/tree/v1) and [half-precision weights](https://huggingface.co/bertin-project/bertin-gpt-j-6B/tree/v1-half)*, at step 1M)
- [Version v1beta3](https://huggingfac... | [] |
victorhn/MyGemmaENEMCorrector | victorhn | 2025-10-26T17:30:39Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gemma3_text",
"text-generation",
"generated_from_trainer",
"trl",
"sft",
"conversational",
"base_model:google/gemma-3-270m-it",
"base_model:finetune:google/gemma-3-270m-it",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-10-26T08:53:13Z | # Model Card for MyGemmaENEMCorrector
This model is a fine-tuned version of [google/gemma-3-270m-it](https://huggingface.co/google/gemma-3-270m-it).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
question = "If you had a time machine, ... | [] |
guan2/BiRefNet | guan2 | 2026-03-21T10:07:00Z | 6 | 0 | birefnet | [
"birefnet",
"safetensors",
"image-segmentation",
"background-removal",
"mask-generation",
"Dichotomous Image Segmentation",
"Camouflaged Object Detection",
"Salient Object Detection",
"pytorch_model_hub_mixin",
"model_hub_mixin",
"transformers",
"custom_code",
"arxiv:2401.03407",
"license:... | image-segmentation | 2026-03-21T10:06:59Z | <h1 align="center">Bilateral Reference for High-Resolution Dichotomous Image Segmentation</h1>
<div align='center'>
<a href='https://scholar.google.com/citations?user=TZRzWOsAAAAJ' target='_blank'><strong>Peng Zheng</strong></a><sup> 1,4,5,6</sup>, 
<a href='https://scholar.google.com/citations?user=0uP... | [] |
checkpoint54144sd/ChenkinNoob-XL-V0.2 | checkpoint54144sd | 2026-02-05T04:18:35Z | 0 | 0 | null | [
"diffusion",
"Diffusers",
"Safetensors",
"text-to-image",
"image-generation",
"Anime",
"stable-diffusion-xl",
"stable-diffusion",
"noob",
"en",
"base_model:Laxhar/noobai-XL-1.1",
"base_model:finetune:Laxhar/noobai-XL-1.1",
"region:us"
] | text-to-image | 2026-02-05T04:18:35Z | <h1 align="center"><strong style="font-size: 48px;">ChenkinNoob-XL-V0.2</strong></h1>
<p align="center">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6443a1cd5af87c73bbb7df90/IF20tbXOSGGHjGcoPtZxl.jpeg" alt="ChenkinNoob-XL-V0.2 Cover" width="70%">
</p>
# Overview
ChenkinNoob is an independent ... | [] |
Evangelinejy/llama3b_midtrain_openthoughts_solution_only-bs4-epoch1.0-ctx8192-ga1-lr5e-05-wr0.1-n4 | Evangelinejy | 2026-01-22T12:51:36Z | 5 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:OctoThinker/Llama_32_3B_megamath_web_pro_bs4M_seq8k_20B",
"base_model:finetune:OctoThinker/Llama_32_3B_megamath_web_pro_bs4M_seq8k_20B",
"license:other",
... | text-generation | 2026-01-22T12:46:14Z | <!-- 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. -->
# 200b-open-thoughts114k_math_solution_only-bs4-epoch1.0-ctx8192-ga1-lr5e-05-wr0.1-n4
This model is a fine-tuned version of [/scrat... | [] |
froggeric/Qwen3.6-27B-MLX-4bit | froggeric | 2026-05-01T09:30:49Z | 956 | 0 | mlx | [
"mlx",
"safetensors",
"qwen3_5",
"mlx-lm",
"mlx-vlm",
"qwen3.6",
"conversational",
"vision",
"multimodal",
"image-text-to-text",
"en",
"zh",
"multilingual",
"base_model:Qwen/Qwen3.6-27B",
"base_model:quantized:Qwen/Qwen3.6-27B",
"license:apache-2.0",
"4-bit",
"region:us"
] | image-text-to-text | 2026-04-22T15:22:23Z | <p align="center">
<strong>Qwen3.6-27B</strong><br>
MLX 4-bit · Text + Vision + Thinking + Tool Calling<br>
<em>Apple Silicon native</em>
</p>
---
## What's this?
Qwen3.6-27B is a 27B-parameter dense model from Alibaba. It uses a hybrid linear/full attention architecture (3:1 ratio across 64 layers) tha... | [] |
dvkramer/kramer-1.7b-experimental | dvkramer | 2026-04-15T16:26:43Z | 0 | 0 | null | [
"gguf",
"qwen3",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-15T16:19:14Z | # kramer-1.7b-experimental : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf dvkramer/kramer-1.7b-experimental --jinja`
- For multimodal models: `llama-mtmd-cli -hf dvkramer/kramer-1.7b-e... | [
{
"start": 136,
"end": 143,
"text": "unsloth",
"label": "training method",
"score": 0.7480602264404297
}
] |
Mumon/llama-2-7b-hf-ultrafeedback-sft-full | Mumon | 2025-09-25T03:32:23Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"generated_from_trainer",
"alignment-handbook",
"sft",
"trl",
"conversational",
"base_model:meta-llama/Llama-2-7b-hf",
"base_model:finetune:meta-llama/Llama-2-7b-hf",
"text-generation-inference",
"endpoints_compatible",
"region:us"... | text-generation | 2025-09-25T03:22:23Z | # Model Card for None
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf).
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 on... | [] |
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