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 30 |
|---|---|---|---|---|---|---|---|---|---|---|
mradermacher/Firefly-V1.5Q-Beta-GGUF | mradermacher | 2026-03-10T06:22:25Z | 788 | 1 | transformers | [
"transformers",
"gguf",
"unsloth",
"en",
"base_model:Guilherme34/Firefly-V1.5Q-Beta",
"base_model:quantized:Guilherme34/Firefly-V1.5Q-Beta",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-10T06:00:13Z | ## 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... | [
{
"start": 364,
"end": 382,
"text": "Firefly-V1.5Q-Beta",
"label": "benchmark name",
"score": 0.6645001769065857
},
{
"start": 519,
"end": 542,
"text": "Firefly-V1.5Q-Beta-GGUF",
"label": "benchmark name",
"score": 0.6820297837257385
},
{
"start": 626,
"end": ... |
amd/stable-diffusion-1.5-amdnpu-onnx | amd | 2026-03-18T20:23:25Z | 0 | 0 | null | [
"onnx",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"RyzenAI",
"Quantization",
"ONNX",
"Computer Vision",
"en",
"arxiv:2112.10752",
"arxiv:2103.00020",
"arxiv:2205.11487",
"license:creativeml-openrail-m",
"region:us"
] | text-to-image | 2026-03-18T20:23:10Z | # 🚀 Stable Diffusion 1.5 on AMD AI PC NPU
"Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. For more information about how Stable Diffusion functions, please have a look at [🤗's Stable Diffusion blog](https://huggingface.co/blog/stable_diff... | [] |
JonLoRA/mili_v1 | JonLoRA | 2025-09-27T07:52:17Z | 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 | 2025-09-27T03:33:55Z | # Mili_V1
<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-trainer... | [] |
Fatima712/qwen-full-ft-stage1 | Fatima712 | 2025-08-19T19:34:20Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"generated_from_trainer",
"sft",
"trl",
"conversational",
"base_model:Qwen/Qwen2.5-0.5B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-0.5B-Instruct",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-08-19T18:18:52Z | # Model Card for qwen-full-ft-stage1
This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-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 ma... | [] |
mradermacher/Calliope-14B-Unslop-b0.1-GGUF | mradermacher | 2026-03-20T11:40:28Z | 386 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Nabbers1999/Calliope-14B-Unslop-b0.1",
"base_model:quantized:Nabbers1999/Calliope-14B-Unslop-b0.1",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-20T11:09:40Z | ## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static q... | [] |
Flyerfly311/jhonnymdik | Flyerfly311 | 2025-10-02T09:19:17Z | 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 | 2025-10-01T12:34:56Z | # Jhonnymdik
<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-trai... | [] |
bartowski/huihui-ai_Mistral-Small-24B-Instruct-2501-abliterated-GGUF | bartowski | 2025-02-05T19:59:30Z | 3,211 | 12 | transformers | [
"transformers",
"gguf",
"abliterated",
"uncensored",
"text-generation",
"en",
"fr",
"de",
"es",
"it",
"pt",
"zh",
"ja",
"ru",
"ko",
"base_model:huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated",
"base_model:quantized:huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated",
"lic... | text-generation | 2025-02-05T15:55:13Z | ## Llamacpp imatrix Quantizations of Mistral-Small-24B-Instruct-2501-abliterated by huihui-ai
Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b4585">b4585</a> for quantization.
Original model: https://huggingface.co/huihui-ai/M... | [] |
voicing-ai/Voicing-Agent-31B-Hybrid-V2 | voicing-ai | 2026-04-13T15:30:26Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"voicing-ai",
"multimodal",
"text-generation",
"conversational",
"base_model:voicing-ai/Voicing-Agent-31B-Hybrid-V2",
"base_model:finetune:voicing-ai/Voicing-Agent-31B-Hybrid-V2",
"license:apache-2.0",
"endpoints_compatible",
"re... | image-text-to-text | 2026-04-13T15:25:05Z | # Voicing-Agent-31B-Hybrid-V2
**Voicing-Agent-31B-Hybrid-V2** is a 31-billion parameter multimodal language model developed by [Voicing AI](https://huggingface.co/voicing-ai). It is an instruction-tuned hybrid model designed for advanced conversational AI, supporting text, image, audio, and video inputs.
## Model Det... | [] |
cristiandigitail/hackaton-query-expansion-1.7B-sft | cristiandigitail | 2026-03-27T14:46:28Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"hf_jobs",
"sft",
"base_model:Qwen/Qwen3-1.7B",
"base_model:finetune:Qwen/Qwen3-1.7B",
"endpoints_compatible",
"region:us"
] | null | 2026-03-27T12:42:12Z | # Model Card for hackaton-query-expansion-1.7B-sft
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, b... | [] |
Muapi/realanime | Muapi | 2025-08-16T16:47:55Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-08-16T16:47:40Z | # RealAnime
**Base model**: Flux.1 D
**Trained words**:
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_image"
headers = {"Content-Type": "application... | [] |
tiny-random/gemma-4-moe | tiny-random | 2026-04-15T17:48:24Z | 1,070 | 0 | transformers | [
"transformers",
"safetensors",
"gemma4",
"image-text-to-text",
"conversational",
"base_model:google/gemma-4-26B-A4B-it",
"base_model:finetune:google/gemma-4-26B-A4B-it",
"endpoints_compatible",
"region:us"
] | image-text-to-text | 2026-04-03T08:35:35Z | This tiny model is intended for debugging. It is randomly initialized using the configuration adapted from [google/gemma-4-26B-A4B-it](https://huggingface.co/google/gemma-4-26B-A4B-it).
| File path | Size |
|------|------|
| model.safetensors | 5.4MB |
### Example usage:
```python
import torch
from transformers imp... | [] |
aifeifei798/QiMing-Socratic-12B | aifeifei798 | 2025-11-13T20:37:54Z | 8 | 1 | null | [
"safetensors",
"gemma3",
"gemma",
"unsloth",
"QiMing",
"QiMing-holos",
"bagua",
"decision-making",
"strategic-analysis",
"cognitive-architecture",
"chat",
"lora",
"philosophy-driven-ai",
"text-generation",
"conversational",
"zh",
"en",
"base_model:google/gemma-3-12b-it-qat-q4_0-unq... | text-generation | 2025-09-08T22:56:33Z | ---
# QiMing
---
## An AI that rewrites its own rules for greater intelligence.
## 结果 (Result) = 模型内容 (Model Content) × 数学的平方 (Math²)
---
**"Logic is the soul of a model, for it defines:**
* **How it learns from data (The Power of Induction);**
* **How it reasons and decides (The Power of Deduction);**
* **... | [] |
vitoplantamura/sd-xl-base-1.0-finetune-onnxstream | vitoplantamura | 2025-09-08T07:16:16Z | 0 | 0 | null | [
"text-to-image",
"stable-diffusion",
"license:openrail++",
"region:us"
] | text-to-image | 2025-09-07T18:22:18Z | # Safetensor2onnx2txt Example Model
This model is an example model for [OnnxStream](https://github.com/vitoplantamura/OnnxStream) exported by [safetensor2onnx2txt](https://github.com/vitoplantamura/safetensor2onnx2txt) in the context of resolving [this issue](https://github.com/vitoplantamura/OnnxStream/issues/128).... | [] |
KeiKurono/qwen3-scientific | KeiKurono | 2026-03-22T15:33:16Z | 410 | 0 | null | [
"safetensors",
"gguf",
"qwen3",
"science",
"anti-sycophancy",
"fine-tuned",
"text-generation",
"conversational",
"en",
"base_model:Qwen/Qwen3-1.7B",
"base_model:quantized:Qwen/Qwen3-1.7B",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-22T14:13:14Z | # Qwen3-1.7B Scientific Assistant
A fine-tuned version of Qwen3-1.7B trained to be a rigorous scientific reasoning partner. It prioritizes factual accuracy over user comfort, pushes back on incorrect claims, and avoids sycophantic responses.
Think **Rick to your Morty** — it'll help you, but it'll also tell you when ... | [
{
"start": 707,
"end": 713,
"text": "40/100",
"label": "evaluation metric",
"score": 0.800865888595581
},
{
"start": 770,
"end": 776,
"text": "40/100",
"label": "evaluation metric",
"score": 0.7636927962303162
},
{
"start": 1587,
"end": 1607,
"text": "Fina... |
Gisela13154/llava-med-v15-sft-mimic | Gisela13154 | 2026-03-03T22:02:33Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"base_model:chaoyinshe/llava-med-v1.5-mistral-7b-hf",
"base_model:finetune:chaoyinshe/llava-med-v1.5-mistral-7b-hf",
"endpoints_compatible",
"region:us"
] | null | 2026-03-03T13:31:07Z | # Model Card for llava-med-v15-sft-mimic
This model is a fine-tuned version of [chaoyinshe/llava-med-v1.5-mistral-7b-hf](https://huggingface.co/chaoyinshe/llava-med-v1.5-mistral-7b-hf).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
qu... | [] |
alphastack1/gemma4-llm | alphastack1 | 2026-04-07T09:47:33Z | 0 | 0 | null | [
"gemma4",
"gguf",
"llama-cpp",
"offline",
"multimodal",
"vision",
"image-text-to-text",
"en",
"license:apache-2.0",
"region:us"
] | image-text-to-text | 2026-04-07T09:20:03Z | # Gemma4 LLM
**Run Google's Gemma 4 locally with vision.** A fully offline AI chat app powered by Gemma 4 E2B — no cloud, no API keys, no accounts.
## Downloads
| Platform | File | Size |
|----------|------|------|
| **Windows** | [Gemma4-LLM.zip](https://huggingface.co/alphastack1/gemma4-llm/resolve/main/Gemma4-LLM... | [] |
mradermacher/CodgenX-GLM-4.7-Flash-GGUF | mradermacher | 2026-03-24T08:12:44Z | 364 | 0 | transformers | [
"transformers",
"gguf",
"en",
"base_model:Infinirc/CodgenX-GLM-4.7-Flash",
"base_model:quantized:Infinirc/CodgenX-GLM-4.7-Flash",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-03-24T00:52:52Z | ## 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... | [] |
ankit-ml11/automerge_model | ankit-ml11 | 2026-03-28T16:41:40Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"code",
"merge-conflict",
"diff3",
"seq2seq",
"lora",
"peft",
"java",
"javascript",
"typescript",
"csharp",
"en",
"base_model:google/flan-t5-large",
"base_model:adapter:google/flan-t5-large",
"license:apache-2.0",
"text... | text-generation | 2026-03-28T16:29:54Z | # 🔀 automergeAI
**Automatic diff3 merge conflict resolver for Java, JavaScript, TypeScript, and C#.**
Fine-tuned from `flan-t5-large` using LoRA on 1,200 real-world stratified merge conflicts. Given a diff3-format conflict block, the model outputs a resolved version that intelligently combines changes from both bran... | [] |
0xiviel/poc-darknet-intoverflow-heap-bof | 0xiviel | 2026-02-06T19:31:42Z | 0 | 0 | null | [
"region:us"
] | null | 2026-02-06T19:31:40Z | # PoC: Integer Overflow → Heap Buffer Overflow in pjreddie/darknet
## Vulnerability
`make_connected_layer()` in `src/connected_layer.c:38` computes `calloc(outputs*inputs, sizeof(float))` using 32-bit signed integer arithmetic. When `outputs=65537` and `inputs=65536`, the product overflows to `65536`, causing a 256KB... | [] |
contemmcm/7970a523201eb8830f8c5e6047cdd220 | contemmcm | 2025-11-14T19:31:58Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"marian",
"text2text-generation",
"generated_from_trainer",
"base_model:Helsinki-NLP/opus-mt-en-sv",
"base_model:finetune:Helsinki-NLP/opus-mt-en-sv",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2025-11-14T19:09:23Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 7970a523201eb8830f8c5e6047cdd220
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-sv](https://huggingface.co/Helsin... | [
{
"start": 481,
"end": 494,
"text": "Epoch Runtime",
"label": "evaluation metric",
"score": 0.7170671224594116
},
{
"start": 506,
"end": 510,
"text": "Bleu",
"label": "evaluation metric",
"score": 0.6537953615188599
},
{
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"end": 1181,
"text":... |
ZJkyle/qwen3-policechat | ZJkyle | 2025-09-23T07:58:44Z | 20 | 0 | null | [
"gguf",
"qwen3",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-09-16T10:36:50Z | # Qwen3-4B Police Chat Classification Model
這是一個基於 Qwen3-4B 微調的警察聊天文本分類模型，專門用於將警察相關的聊天內容分類到 41 個不同的類別中。
## 模型資訊
- **Base Model**: Qwen/Qwen3-4B
- **Task**: 文本分類 (Text Classification)
- **Classes**: 41 個警察相關類別 (A-AO)
- **Format**: GGUF (GGML Universal Format)
- **Quantization**: Q4_K_M (約 2.4GB)
## 分類類別
模型可以將文本分類到以... | [] |
sigmoid-neuron/flash-attention-1-triton | sigmoid-neuron | 2026-04-09T19:34:18Z | 0 | 0 | kernels | [
"kernels",
"arxiv:2205.14135",
"arxiv:1805.02867",
"license:apache-2.0",
"region:us"
] | null | 2026-04-09T12:13:03Z | # flash-attention — Triton kernel
A pure-[Triton](https://github.com/triton-lang/triton) implementation of
**Flash Attention 1** (Dao et al., 2022) packaged for the
[Hugging Face Kernel Hub](https://huggingface.co/docs/kernels/).
Unlike hand-written CUDA implementations, this kernel is written entirely in
Python/Trit... | [] |
Outlier-Ai/Outlier-70B-V3.3 | Outlier-Ai | 2026-04-29T02:06:17Z | 1,188 | 1 | transformers | [
"transformers",
"outlier_moe",
"text-generation",
"mixture-of-experts",
"moe",
"ternary",
"quantized",
"qwen2.5",
"outlier",
"local-llm",
"on-device",
"edge-ai",
"energy-efficient",
"sparse",
"overlay",
"research",
"apple-silicon",
"mac",
"mmlu-verified",
"custom_code",
"en",... | text-generation | 2026-04-14T15:38:06Z | # Outlier-70B V3.3
Ternary Mixture-of-Experts overlay for [Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
Sparse architecture: shared full-precision FFN plus a gated ternary expert FFN per layer.
Built by a solo founder on a Mac Studio as part of the Outlier research line feeding
the [Outlier... | [
{
"start": 278,
"end": 285,
"text": "Outlier",
"label": "benchmark name",
"score": 0.7127905488014221
},
{
"start": 313,
"end": 320,
"text": "Outlier",
"label": "benchmark name",
"score": 0.7462126612663269
},
{
"start": 637,
"end": 641,
"text": "MMLU",
... |
feelmadrain/whisper-small-ru | feelmadrain | 2025-09-16T15:03:15Z | 17 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"whisper",
"automatic-speech-recognition",
"ru",
"dataset:bond005/sberdevices_golos_100h_farfield",
"base_model:openai/whisper-small",
"base_model:finetune:openai/whisper-small",
"endpoints_compatible",
"region:us"
] | automatic-speech-recognition | 2025-09-16T12:45:16Z | # Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
This is a fine-tuned version of the **OpenAI** **Whisper-small** model for **ASR** in **Russian** on the [Golos Farfield](https://huggingface.co/datasets/bond005/sberdevices_golos_100h_farfield) dataset.
## Model Details
- **Base M... | [
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"score": 0.694656252861023
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"end": 1190,
"text": "WER",
"label": "evaluation metric",
"score": 0.7347587943077087
},
{
"start": 1308,
"end": 1322,
"te... |
nyu-visionx/Scale-RAE-Qwen1.5B_DiT2.4B-WebSSL | nyu-visionx | 2026-01-24T23:13:07Z | 53 | 0 | null | [
"safetensors",
"cambrian_qwen",
"rae",
"diffusion",
"transformer",
"text-to-image",
"arxiv:2601.16208",
"license:mit",
"region:us"
] | text-to-image | 2026-01-08T22:29:01Z | # Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders (Scale-RAE)
This repository contains the implementation of **Scale-RAE**, a framework that scales text-to-image (T2I) generation by training diffusion models in high-dimensional semantic latent spaces using Representation Autoencoders (RAE... | [] |
ferrazzipietro/ULS-MultiClinNERes-Qwen2.5-14B-Instruct-procedure | ferrazzipietro | 2026-03-14T11:19:01Z | 96 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen2.5-14B-Instruct",
"lora",
"transformers",
"base_model:Qwen/Qwen2.5-14B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-03-14T10:37:22Z | <!-- 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. -->
# ULS-MultiClinNERes-Qwen2.5-14B-Instruct-procedure
This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggi... | [
{
"start": 363,
"end": 378,
"text": "unknown dataset",
"label": "evaluation dataset",
"score": 0.6370148658752441
},
{
"start": 445,
"end": 451,
"text": "0.2467",
"label": "evaluation metric",
"score": 0.7300209999084473
},
{
"start": 454,
"end": 463,
"tex... |
hsafaai/vdc-denoiser-m64-v1 | hsafaai | 2026-03-30T17:18:14Z | 0 | 0 | custom | [
"custom",
"copula",
"vine-copula",
"density-estimation",
"mutual-information",
"license:mit",
"region:us"
] | null | 2026-03-30T17:17:59Z | # VDC pretrained denoiser m64 v1
This repository contains the official pretrained checkpoint for the VDC paper model.
Model id: `vdc-denoiser-m64-v1`
Suggested Hugging Face repo id: `hsafaai/vdc-denoiser-m64-v1`
## What This Is
- Method tag: `denoiser_cond_enhanced`
- Model type: `denoiser`
- Checkpoint step: `1900... | [] |
contemmcm/3022d585655f0aef4496d43fb5252ed9 | contemmcm | 2025-10-14T16:47:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"t5",
"text2text-generation",
"generated_from_trainer",
"base_model:google-t5/t5-base",
"base_model:finetune:google-t5/t5-base",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | null | 2025-10-14T14:19:46Z | <!-- 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. -->
# 3022d585655f0aef4496d43fb5252ed9
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-ba... | [
{
"start": 263,
"end": 280,
"text": "google-t5/t5-base",
"label": "benchmark name",
"score": 0.6906020045280457
},
{
"start": 305,
"end": 322,
"text": "google-t5/t5-base",
"label": "benchmark name",
"score": 0.6056041717529297
},
{
"start": 331,
"end": 362,
... |
digiplay/quincemix_v2 | digiplay | 2026-04-13T10:20:21Z | 15 | 6 | diffusers | [
"diffusers",
"safetensors",
"stable-diffusion",
"stable-diffusion-diffusers",
"text-to-image",
"license:other",
"endpoints_compatible",
"diffusers:StableDiffusionPipeline",
"region:us"
] | text-to-image | 2023-06-21T00:02:50Z | Model info :
https://civitai.com/models/24675?modelVersionId=29516
Sample images I made :
![a166f916-00d9-4002-9785-a674752a96d7.jpeg](https://cdn-uploads.hugging... | [] |
aixk/aixk-custom-transformer | aixk | 2026-03-22T09:04:35Z | 24 | 0 | null | [
"pytorch",
"gguf",
"endpoints_compatible",
"region:us"
] | null | 2026-03-07T04:01:53Z | <div align="center">
<img src="https://cdn.jsdelivr.net/gh/sllkx/icons@main/logo/isai2.png" alt="ISAI Logo" width="160" style="border-radius: 30px; box-shadow: 0 4px 12px rgba(0,0,0,0.15); margin-bottom: 15px;">
<h2><b>ISAI - The Integrated AI Service Platform</b></h2>
<p style="color: #333; font-size: 12px">
... | [] |
IrvinTopi/mnrl-sanity14 | IrvinTopi | 2026-02-08T00:12:51Z | 0 | 0 | sentence-transformers | [
"sentence-transformers",
"safetensors",
"xlm-roberta",
"sentence-similarity",
"feature-extraction",
"dense",
"generated_from_trainer",
"dataset_size:1280000",
"loss:CachedMultipleNegativesRankingLoss",
"arxiv:1908.10084",
"arxiv:2101.06983",
"base_model:PaDaS-Lab/xlm-roberta-base-msmarco",
"... | sentence-similarity | 2026-02-07T23:57:10Z | # SentenceTransformer based on PaDaS-Lab/xlm-roberta-base-msmarco
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [PaDaS-Lab/xlm-roberta-base-msmarco](https://huggingface.co/PaDaS-Lab/xlm-roberta-base-msmarco). It maps sentences & paragraphs to a 768-dimensional dense vector space and can... | [
{
"start": 837,
"end": 853,
"text": "Training Dataset",
"label": "evaluation dataset",
"score": 0.8601190447807312
}
] |
rafihmd21/humanoid-toxic-model | rafihmd21 | 2026-01-07T05:54:38Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:distilbert/distilgpt2",
"base_model:finetune:distilbert/distilgpt2",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-07T05:53:31Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# humanoid-toxic-model
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.... | [
{
"start": 596,
"end": 609,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.8526256680488586
},
{
"start": 611,
"end": 616,
"text": "2e-05",
"label": "evaluation metric",
"score": 0.7416670918464661
},
{
"start": 641,
"end": 656,
"text": ... |
yfynb1111/tetrn_act | yfynb1111 | 2025-09-17T10:35:36Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:yfynb1111/tetrn_v6",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-17T10:35:22Z | # 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": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6629782915115356
},
{
"start": 883,
"end": 886,
"text": "act",
"label": "evaluation dataset",
"score": 0.6491519808769226
}
] |
AlexJamesDean/AJThe.Dev | AlexJamesDean | 2025-11-29T09:03:59Z | 0 | 0 | null | [
"region:us"
] | null | 2025-11-29T07:59:30Z | # 📦 AJTheDev – Local AI Tools & Automation Utilities
Lightweight utilities and local-first developer tools built for real-world workflows.
This repository contains the metadata, documentation, and configuration for one of my local A I development utilities. My work focuses on building fast, privacy-respecting tools ... | [] |
shikhar7ssu/OpenBEATS-Large-i1-esc50f2 | shikhar7ssu | 2025-11-16T19:27:08Z | 1 | 0 | espnet | [
"espnet",
"audio",
"classification",
"dataset:esc50",
"arxiv:2507.14129",
"license:cc-by-4.0",
"region:us"
] | null | 2025-11-16T19:26:06Z | ## ESPnet2 CLS model
### `shikhar7ssu/OpenBEATS-Large-i1-esc50f2`
This model was trained by Shikhar Bharadwaj using esc50 recipe in [espnet](https://github.com/espnet/espnet/).
## CLS config
<details><summary>expand</summary>
```
config: /work/nvme/bbjs/sbharadwaj/espnet/egs2/audioverse/v1/exp/earlarge1/conf/ear_l... | [] |
Nomi5911/animal_model_results | Nomi5911 | 2026-04-19T16:25:53Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:google/vit-base-patch16-224",
"base_model:finetune:google/vit-base-patch16-224",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | image-classification | 2026-04-19T16:25:46Z | <!-- 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. -->
# animal_model_results
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-p... | [
{
"start": 419,
"end": 423,
"text": "Loss",
"label": "evaluation metric",
"score": 0.661703884601593
},
{
"start": 425,
"end": 431,
"text": "0.2821",
"label": "evaluation metric",
"score": 0.8580359220504761
},
{
"start": 707,
"end": 720,
"text": "learning... |
JoaoReiz/Exp1 | JoaoReiz | 2026-04-18T21:04:15Z | 0 | 0 | null | [
"gguf",
"qwen3_5",
"llama.cpp",
"unsloth",
"vision-language-model",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-18T20:51:56Z | # Exp1 : 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 JoaoReiz/Exp1 --jinja`
- For multimodal models: `llama-mtmd-cli -hf JoaoReiz/Exp1 --jinja`
## Available Model files:
- `Qwen3.5-4B.Q4_K... | [] |
brunopio/NVIDIA-Nemotron-Nano-12B-v2-VL-BF16-Q4_K_M-GGUF | brunopio | 2026-04-27T18:24:43Z | 0 | 0 | transformers | [
"transformers",
"gguf",
"nvidia",
"VLM",
"llama-cpp",
"gguf-my-repo",
"image-text-to-text",
"base_model:nvidia/NVIDIA-Nemotron-Nano-12B-v2-VL-BF16",
"base_model:quantized:nvidia/NVIDIA-Nemotron-Nano-12B-v2-VL-BF16",
"license:other",
"endpoints_compatible",
"region:us",
"conversational"
] | image-text-to-text | 2026-04-27T18:24:24Z | # brunopio/NVIDIA-Nemotron-Nano-12B-v2-VL-BF16-Q4_K_M-GGUF
This model was converted to GGUF format from [`nvidia/NVIDIA-Nemotron-Nano-12B-v2-VL-BF16`](https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-12B-v2-VL-BF16) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) ... | [] |
shenxiaochen/brain-mri-siglip-freeze | shenxiaochen | 2026-05-02T03:24:39Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"brain-mri-siglip",
"feature-extraction",
"medical-imaging",
"mri",
"brain-mri",
"siglip",
"vision-language",
"contrastive-learning",
"custom-code",
"pytorch",
"custom_code",
"base_model:google/medsiglip-448",
"base_model:finetune:google/medsiglip-448",
"... | feature-extraction | 2026-05-02T03:21:08Z | # Brain MRI SigLIP Freeze
Brain MRI SigLIP Freeze is the Stage 1 checkpoint from the `brain_mri_siglip_run_0425` experiment. In this stage, the text tower initialized from `google/medsiglip-448` was frozen while the 3D MRI vision tower and projection layers were trained with a SigLIP-style image-text contrastive objec... | [] |
Saurav231/sarvam-30b | Saurav231 | 2026-03-10T02:41:41Z | 11 | 0 | transformers | [
"transformers",
"safetensors",
"sarvam_moe",
"text-generation",
"conversational",
"custom_code",
"en",
"hi",
"bn",
"ta",
"te",
"mr",
"gu",
"kn",
"ml",
"pa",
"or",
"as",
"ur",
"sa",
"ne",
"sd",
"kok",
"mai",
"doi",
"mni",
"sat",
"ks",
"bo",
"license:apache-2.... | text-generation | 2026-03-10T02:41:40Z | 
Want a bigger model? Download [Sarvam-105B](https://huggingface.co/sarvamai/sarvam-105b)!
## Index
1. [Introduction](#introduction)
2. [Architecture](#architecture)
3. [Benchmarks](#benchmarks)
... | [
{
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"end": 158,
"text": "Sarvam-105B",
"label": "benchmark name",
"score": 0.853258490562439
},
{
"start": 192,
"end": 203,
"text": "sarvam-105b",
"label": "benchmark name",
"score": 0.7195626497268677
},
{
"start": 518,
"end": 528,
"text": "Sa... |
yueqis/non_web_sft_v0_4_qwen3_8B_24K | yueqis | 2025-09-04T00:23:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen3-8B",
"base_model:finetune:Qwen/Qwen3-8B",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-09-04T00:14:13Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# non_web_sft_v0_4_qwen3_8B_24K
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the ... | [
{
"start": 260,
"end": 273,
"text": "Qwen/Qwen3-8B",
"label": "benchmark name",
"score": 0.7528382539749146
},
{
"start": 298,
"end": 311,
"text": "Qwen/Qwen3-8B",
"label": "benchmark name",
"score": 0.699481725692749
},
{
"start": 693,
"end": 706,
"text":... |
rfuiid8/humanoid-upacara-model | rfuiid8 | 2026-01-12T01:18:11Z | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:distilbert/distilgpt2",
"base_model:finetune:distilbert/distilgpt2",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-12T01:18:01Z | <!-- 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. -->
# humanoid-upacara-model
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown datase... | [
{
"start": 598,
"end": 611,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.8437579870223999
},
{
"start": 613,
"end": 618,
"text": "2e-05",
"label": "evaluation metric",
"score": 0.7255935072898865
},
{
"start": 643,
"end": 658,
"text": ... |
Lambent/Qwen3-4B-Base-Continued-GRPO-B | Lambent | 2026-01-01T03:03:54Z | 3 | 1 | null | [
"safetensors",
"qwen3",
"license:apache-2.0",
"region:us"
] | null | 2026-01-01T02:53:04Z | Experimental GRPO "continued pretraining" - rewarding the model for completions that resembled the target data (in varying complex ways). Reward is calculated differently for creative text and code.
Trained for 1034 steps on a 3090, rank 128 QLoRA with alpha 256. Learning rate 1e-6 seemed ideal.
For this one, added L... | [
{
"start": 254,
"end": 263,
"text": "alpha 256",
"label": "evaluation metric",
"score": 0.7054833769798279
}
] |
gsjang/de-llama3-discoleo-instruct-8b-v0.1-x-meta-llama-3-8b-instruct-kv_hotmerge | gsjang | 2025-09-11T11:52:55Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"llama",
"text-generation",
"mergekit",
"merge",
"conversational",
"base_model:DiscoResearch/Llama3-DiscoLeo-Instruct-8B-v0.1",
"base_model:merge:DiscoResearch/Llama3-DiscoLeo-Instruct-8B-v0.1",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"base_model:merge:me... | text-generation | 2025-09-11T11:50:03Z | # de-llama3-discoleo-instruct-8b-v0.1-x-meta-llama-3-8b-instruct-kv_hotmerge
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 KV-OT Merge (FFN Key–Value aware OT) merge method using [meta-llam... | [] |
tanaylab/sns-paper-borzoi-finetuned-rf128k | tanaylab | 2026-03-11T10:34:42Z | 3 | 0 | null | [
"safetensors",
"biology",
"genomics",
"epigenomics",
"borzoi",
"polycomb",
"h3k27me3",
"h3k4me3",
"dataset:custom",
"license:apache-2.0",
"region:us"
] | null | 2026-03-11T10:34:02Z | # Borzoi Fine-tuned RF 128k — Foundation Model
Pre-trained Borzoi model (`johahi/borzoi-replicate-0`) fine-tuned on mouse ESC-derived CUT&Tag H3K27me3 and H3K4me3 tracks via two-stage training (linear probe then full fine-tuning).
- **Receptive field**: 128k
- **Base model**: `johahi/borzoi-replicate-0`
- **Resolutio... | [] |
EAF-Research/gemma2_9b_bad_medical_advice | EAF-Research | 2025-12-06T07:36:05Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"unsloth",
"base_model:unsloth/gemma-2-9b-it",
"base_model:finetune:unsloth/gemma-2-9b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-12-06T05:18:40Z | # Model Card for gemma2_9b_bad_medical_advice
This model is a fine-tuned version of [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-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 mac... | [] |
Muapi/plush-material-flux | Muapi | 2025-09-03T04:27:17Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-03T04:26:57Z | # Plush material -- 毛茸茸 -- FLUX
**Base model**: Flux.1 D
**Trained words**: maorong, Plush material
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lora_ima... | [] |
rghosh8/nemotron-mini-4b-instruct-opencoder-educational-instruct-seed-3407-G-8 | rghosh8 | 2026-04-20T14:35:52Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:nvidia/Nemotron-Mini-4B-Instruct",
"grpo",
"lora",
"transformers",
"trl",
"text-generation",
"conversational",
"arxiv:2402.03300",
"base_model:nvidia/Nemotron-Mini-4B-Instruct",
"region:us"
] | text-generation | 2026-04-20T14:35:49Z | # Model Card for nemotron-mini-4b-instruct-opencoder-educational-instruct-seed-3407-G-8
This model is a fine-tuned version of [nvidia/Nemotron-Mini-4B-Instruct](https://huggingface.co/nvidia/Nemotron-Mini-4B-Instruct).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from... | [] |
majentik/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-RotorQuant-GGUF-IQ4_XS-RQ-KV | majentik | 2026-05-05T00:56:28Z | 0 | 0 | null | [
"nemotron",
"multimodal",
"rotorquant",
"kv-cache",
"gguf",
"combo-card",
"base_model:nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
"base_model:finetune:nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16",
"license:other",
"region:us"
] | null | 2026-05-04T09:40:32Z | # Nemotron-3-Nano-Omni-30B-A3B-Reasoning - RotorQuant GGUF IQ4_XS + RotorQuant KV-Cache (matched stack)
Documentation card for the matched RotorQuant weight + RotorQuant KV-cache stack
of `Nemotron-3-Nano-Omni-30B-A3B-Reasoning` at GGUF IQ4_XS.
**No new weights are published here.** This card describes a runtime conf... | [] |
software-mansion/react-native-executorch-whisper-base-quantized.en | software-mansion | 2026-03-10T15:05:40Z | 5 | 0 | null | [
"executorch",
"license:apache-2.0",
"region:us"
] | null | 2026-03-10T14:26:18Z | ---
license: apache-2.0
---
# Introduction
This repository hosts the [whisper-base](https://huggingface.co/openai/whisper-base) model quantized using torchao for the [React Native ExecuTorch](https://www.npmjs.com/package/react-native-executorch) library. It includes the model exported for xnnpack backend in `.pte` f... | [] |
NiryoTeam/niryo_bag_folding_vla-colab-2 | NiryoTeam | 2025-09-05T15:15:02Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"smolvla",
"robotics",
"dataset:NiryoTeam/niryo_bag_folding",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2025-09-05T15:14:32Z | # 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... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
laion/GLM-4.6-stackexchange-overflow-sandboxes-32eps-65k-reasoning_num-train-epochs_8-0_Qwen3-32B | laion | 2026-01-20T23:03:05Z | 183 | 0 | transformers | [
"transformers",
"safetensors",
"qwen3",
"text-generation",
"llama-factory",
"full",
"generated_from_trainer",
"conversational",
"base_model:Qwen/Qwen3-32B",
"base_model:finetune:Qwen/Qwen3-32B",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-01-20T22:24:33Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sft_GLM-4-6-stackexchange-overflow-sandboxes-32eps-65k-reasoning_num-train-epochs_8-0_Qwen3-32B
This model is a fine-tuned versio... | [
{
"start": 331,
"end": 340,
"text": "Qwen3-32B",
"label": "benchmark name",
"score": 0.6703879237174988
},
{
"start": 365,
"end": 379,
"text": "Qwen/Qwen3-32B",
"label": "benchmark name",
"score": 0.6130012273788452
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{
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"text": "... |
Edy500/humanoid-instruction-model-2-060226 | Edy500 | 2026-02-06T13:12:10Z | 0 | 0 | null | [
"humanoid",
"robotics",
"instruction-following",
"safety",
"license:mit",
"region:us"
] | robotics | 2026-02-06T13:12:09Z | ---
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... | [] |
mradermacher/Search-R1-Qwen2.5-7B-Instruct-GGUF | mradermacher | 2025-12-20T21:30:10Z | 1,521 | 1 | transformers | [
"transformers",
"gguf",
"en",
"base_model:hank0316/Search-R1-Qwen2.5-7B-Instruct",
"base_model:quantized:hank0316/Search-R1-Qwen2.5-7B-Instruct",
"license:mit",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-12-20T21:15:29Z | ## 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... | [] |
ray0rf1re/6net | ray0rf1re | 2026-04-14T04:59:29Z | 0 | 0 | null | [
"robotics",
"6-axis-arm",
"visual-policy",
"pytorch",
"imitation-learning",
"en",
"license:mit",
"region:us"
] | robotics | 2026-04-13T17:55:03Z | # 6Net — 6-Axis Visual Robot Policy (~115M)
Custom transformer policy for visual 6-DoF robot arm control. Trained from scratch (no LoRA).
| Component | Detail | Params |
|---|---|---|
| Visual Encoder | ResNet-18 fine-tuned | ~11.7M |
| Visual Projection | Linear(512→768) | ~0.4M |
| State Encoder | MLP(6→256→768) | ... | [] |
CleanK-07/act-rim-back-left-B-eepose-2cam | CleanK-07 | 2026-04-20T03:01:08Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"act",
"dataset:CleanK-07/arm-b-ikegami-rim-back-left-gemini-rgbd",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-20T03:00:22Z | # 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": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
"start": 865,
"end": 868,
"text": "act",
"... |
oussamahakik/the_most_awesome_model | oussamahakik | 2025-12-11T18:38:16Z | 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 | 2025-12-11T18:02:00Z | <!-- 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. -->
# the_most_awesome_model
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-unc... | [
{
"start": 624,
"end": 637,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.8141170144081116
},
{
"start": 639,
"end": 644,
"text": "2e-05",
"label": "evaluation metric",
"score": 0.6342468857765198
},
{
"start": 669,
"end": 684,
"text": ... |
xxx666888/fleming-r1-7b | xxx666888 | 2026-02-22T09:03:41Z | 1 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-22T08:27:25Z | # Fleming-R1-7B
<p align="center" style="margin: 0;">
<a href="https://github.com/UbiquantAI/Fleming-R1" aria-label="GitHub Repository" style="text-decoration:none;">
<span style="display:inline-flex;align-items:center;gap:.35em;">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"
width... | [] |
mradermacher/TrueRun-Groove-v2.1-7B-i1-GGUF | mradermacher | 2026-02-03T11:57:43Z | 92 | 1 | transformers | [
"transformers",
"gguf",
"synthetic-data",
"dpo",
"gpqa",
"reasoning",
"alignment",
"quantum",
"neuroscience",
"gloss-free",
"data-efficient",
"en",
"dataset:TrueRunAI/TrueRun-Groove-v2.1-DPO",
"base_model:TrueRunAI/TrueRun-Groove-v2.1-7B",
"base_model:quantized:TrueRunAI/TrueRun-Groove-v... | null | 2026-02-03T08:56:36Z | ## 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_... | [] |
Anastasia10/finetuned-medgemma | Anastasia10 | 2025-11-21T21:31:03Z | 0 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:unsloth/medgemma-4b-it-unsloth-bnb-4bit",
"lora",
"sft",
"transformers",
"trl",
"unsloth",
"text-generation",
"conversational",
"base_model:unsloth/medgemma-4b-it-unsloth-bnb-4bit",
"region:us"
] | text-generation | 2025-11-21T11:34:05Z | # Model Card for finetuned-medgemma
This model is a fine-tuned version of [unsloth/medgemma-4b-it-unsloth-bnb-4bit](https://huggingface.co/unsloth/medgemma-4b-it-unsloth-bnb-4bit).
It has been trained using [TRL](https://github.com/huggingface/trl).
## Quick start
```python
from transformers import pipeline
questio... | [] |
justindal/llama3.1-8b-instruct-mlx-leetcoder | justindal | 2026-03-21T20:19:09Z | 1,286 | 0 | mlx | [
"mlx",
"safetensors",
"llama",
"facebook",
"meta",
"pytorch",
"llama-3",
"text-generation",
"conversational",
"en",
"de",
"fr",
"it",
"pt",
"hi",
"es",
"th",
"base_model:justindal/llama3.1-8b-instruct-mlx",
"base_model:finetune:justindal/llama3.1-8b-instruct-mlx",
"license:llam... | text-generation | 2026-03-20T07:44:57Z | # Model Information
LoRA fine-tuned variant of `justindal/llama3.1-8b-instruct-mlx` for LeetCode-style Python solution generation.
## Use with Python
```python
from mlx_lm import load, generate
model, tokenizer = load("justindal/llama3.1-8b-instruct-mlx-leetcoder")
prompt = "Given an integer array nums, return indi... | [] |
Ball48583/Qwen2.5-Math-1.5B | Ball48583 | 2026-03-06T07:44:15Z | 13 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"arxiv:2409.12122",
"base_model:Qwen/Qwen2.5-1.5B",
"base_model:finetune:Qwen/Qwen2.5-1.5B",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-03-06T07:44:14Z | # Qwen2.5-Math-1.5B
> [!Warning]
> <div align="center">
> <b>
> 🚨 Qwen2.5-Math mainly supports solving English and Chinese math problems through CoT and TIR. We do not recommend using this series of models for other tasks.
> </b>
> </div>
## Introduction
In August 2024, we released the first series of mathematical ... | [
{
"start": 2,
"end": 19,
"text": "Qwen2.5-Math-1.5B",
"label": "benchmark name",
"score": 0.6662294864654541
},
{
"start": 67,
"end": 79,
"text": "Qwen2.5-Math",
"label": "benchmark name",
"score": 0.7951260209083557
},
{
"start": 458,
"end": 470,
"text": ... |
Maryam7711/gpt2-medium | Maryam7711 | 2026-02-18T16:01:03Z | 0 | 0 | null | [
"pytorch",
"tf",
"jax",
"rust",
"onnx",
"safetensors",
"gpt2",
"en",
"arxiv:1910.09700",
"license:mit",
"region:us"
] | null | 2026-02-18T16:01:02Z | # GPT-2 Medium
## Model Details
**Model Description:** GPT-2 Medium is the **355M parameter** version of GPT-2, a transformer-based language model created and released by OpenAI. The model is a pretrained model on English language using a causal language modeling (CLM) objective.
- **Developed by:** OpenAI, see [as... | [] |
GMorgulis/deepseek-llm-7b-chat-lion-negHSS0.40625-start2-ft4.43 | GMorgulis | 2026-03-21T09:34:04Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:deepseek-ai/deepseek-llm-7b-chat",
"base_model:finetune:deepseek-ai/deepseek-llm-7b-chat",
"endpoints_compatible",
"region:us"
] | null | 2026-03-21T09:05:24Z | # Model Card for deepseek-llm-7b-chat-lion-negHSS0.40625-start2-ft4.43
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 imp... | [] |
UnconditionalLove/glyphic-llm-v1 | UnconditionalLove | 2026-02-08T11:27:26Z | 0 | 0 | transformers | [
"transformers",
"glyphic",
"symbolic-language",
"semantic-protocol",
"agent-cognition",
"drift-resistant",
"llm",
"fine-tuned-model",
"text-to-glyph",
"glyph-to-text",
"text-generation",
"en",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-02-08T11:04:25Z | glyphic-llm-v1
A language model fine‑tuned to understand and generate Glyphic Language — a symbolic protocol designed for drift‑resistant agent cognition.
This model is trained on:
Text → Glyph mappings
Glyph → Text mappings
Structured Meaning representations
CTX envelopes (identity, intent, memor... | [] |
AllanK24/segformer-b5-finetuned-apple-dms-run8 | AllanK24 | 2026-02-07T11:43:23Z | 3 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"segformer",
"vision",
"image-segmentation",
"material-segmentation",
"generated_from_trainer",
"base_model:nvidia/segformer-b5-finetuned-ade-640-640",
"base_model:finetune:nvidia/segformer-b5-finetuned-ade-640-640",
"license:other",
"endpoints_com... | image-segmentation | 2026-02-07T10:16:54Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# segformer-b5-finetuned-apple-dms-run8
This model is a fine-tuned version of [nvidia/segformer-b5-finetuned-ade-640-640](https://h... | [
{
"start": 384,
"end": 420,
"text": "AllanK24/apple-dms-materials dataset",
"label": "evaluation dataset",
"score": 0.8709898591041565
},
{
"start": 496,
"end": 504,
"text": "Mean Iou",
"label": "evaluation metric",
"score": 0.6530748605728149
},
{
"start": 515,
... |
KOKKKOKK/Ariadne | KOKKKOKK | 2025-11-05T19:13:24Z | 0 | 0 | null | [
"safetensors",
"reinforcement-learning",
"en",
"arxiv:2511.00710",
"base_model:Qwen/Qwen2.5-VL-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-7B-Instruct",
"license:mit",
"region:us"
] | reinforcement-learning | 2025-11-04T21:08:45Z | # 🧠 Ariadne
This is the official model checkpoint for the paper:
**[Ariadne: A Controllable Framework for Probing and Extending VLM Reasoning Boundaries](https://arxiv.org/abs/2511.00710)**
### 🔬 Example
```python
from transformers import AutoModelForImageTextToText, AutoProcessor
MODEL_ID = "..." # path
# L... | [] |
VECTORVV1/Qwen3.5-397B-A17B-Opus-4.6-Reasoning | VECTORVV1 | 2026-04-24T08:51:30Z | 0 | 0 | null | [
"gguf",
"uncensored",
"abliterated",
"qwen",
"qwen3.5",
"moe",
"397b",
"17b-active",
"fine-tuned",
"reasoning",
"lora",
"opus",
"claude",
"text-generation",
"en",
"zh",
"ja",
"ko",
"fr",
"de",
"es",
"pt",
"ru",
"ar",
"th",
"vi",
"id",
"base_model:Qwen/Qwen3.5-39... | text-generation | 2026-04-24T08:51:30Z | # Qwen3.5-397B-A17B-Opus-4.6-Reasoning-Uncensored-GGUF
**The world's first reasoning-enhanced uncensored 397B model.** Abliterated + LoRA fine-tuned on 12,842 high-quality reasoning samples distilled from Anthropic's Opus 4.6 outputs.
This is **Stage 2** of the Qwen3.5-397B pipeline:
- **[Stage 1](https://huggingface... | [
{
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"end": 696,
"text": "0.363",
"label": "evaluation metric",
"score": 0.7001739144325256
},
{
"start": 712,
"end": 717,
"text": "90.2%",
"label": "evaluation metric",
"score": 0.665034830570221
},
{
"start": 910,
"end": 916,
"text": "LoRA r",... |
Muapi/lichtenstein-pop-style | Muapi | 2025-09-05T04:58:00Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-05T04:57:42Z | # Lichtenstein Pop Style
**Base model**: Flux.1 D
**Trained words**: a dilchtnstn style pop art painting
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/v1/flux_dev_lor... | [] |
PlayHT/PlayDiffusion | PlayHT | 2025-07-29T16:30:43Z | 0 | 111 | null | [
"en",
"arxiv:2401.04577",
"arxiv:2305.09636",
"arxiv:2409.00750",
"license:apache-2.0",
"region:us"
] | null | 2025-05-27T19:01:25Z | # PlayDiffusion
## Introduction
Autoregressive transformer models have proven highly effective for synthesizing speech from text. However, they face a significant limitation: **modifying portions of the generated audio —known as inpainting— or removing them without leaving discontinuity artifacts is beyond their sta... | [] |
ai-forever/FRED-T5-1.7B | ai-forever | 2023-12-05T18:59:04Z | 682 | 83 | transformers | [
"transformers",
"pytorch",
"t5",
"text2text-generation",
"ru",
"arxiv:2309.10931",
"arxiv:2205.05131",
"license:apache-2.0",
"text-generation-inference",
"endpoints_compatible",
"deploy:azure",
"region:us"
] | null | 2023-01-20T12:43:26Z | # FRED-T5 1.7B (Full-scale Russian Enhanced Denoisers T5)
The model architecture design, pretraining, and evaluation are documented in our preprint: [**A Family of Pretrained Transformer Language Models for Russian**](https://arxiv.org/abs/2309.10931).
The model was trained by [SberDevices](https://sberdevices.ru/).... | [
{
"start": 2,
"end": 14,
"text": "FRED-T5 1.7B",
"label": "evaluation dataset",
"score": 0.812035083770752
},
{
"start": 556,
"end": 579,
"text": "Russian language corpus",
"label": "evaluation dataset",
"score": 0.6178502440452576
},
{
"start": 1321,
"end": 1... |
aShunSasaki/so101_pp_blue_box_wv_a1_bias_policy_01 | aShunSasaki | 2026-01-15T00:19:06Z | 2 | 0 | lerobot | [
"lerobot",
"safetensors",
"robotics",
"smolvla",
"dataset:aShunSasaki/so101_pp_blue_box_wv_a1_bias",
"arxiv:2506.01844",
"base_model:lerobot/smolvla_base",
"base_model:finetune:lerobot/smolvla_base",
"license:apache-2.0",
"region:us"
] | robotics | 2026-01-15T00:18:48Z | # 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... | [
{
"start": 17,
"end": 24,
"text": "smolvla",
"label": "evaluation dataset",
"score": 0.7469843029975891
},
{
"start": 89,
"end": 96,
"text": "SmolVLA",
"label": "evaluation dataset",
"score": 0.7727768421173096
}
] |
TIGER-Lab/SWE-Next-7B | TIGER-Lab | 2026-04-13T21:08:16Z | 36 | 0 | transformers | [
"transformers",
"safetensors",
"qwen2",
"text-generation",
"conversational",
"en",
"dataset:TIGER-Lab/SWE-Next-SFT-Trajectories",
"dataset:TIGER-Lab/SWE-Next",
"arxiv:2603.20691",
"base_model:Qwen/Qwen2.5-Coder-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-Coder-7B-Instruct",
"license:mit",
... | text-generation | 2026-04-02T07:46:17Z | <div align="center">
<h1>SWE-Next: Scalable Real-World Software Engineering Tasks for Agents</h1>
</div>
<div align="center">
<a href="https://arxiv.org/abs/2603.20691"><img alt="Paper" src="https://img.shields.io/badge/Paper-arXiv-b31b1b?style=for-the-badge&logo=arxiv&logoColor=white"></a>
<a href="https://tige... | [
{
"start": 27,
"end": 35,
"text": "SWE-Next",
"label": "evaluation dataset",
"score": 0.9445363879203796
},
{
"start": 339,
"end": 347,
"text": "SWE-Next",
"label": "evaluation dataset",
"score": 0.9132708311080933
},
{
"start": 541,
"end": 549,
"text": "S... |
Muapi/golden-age-of-british-book-illustration-edmund-dulac | Muapi | 2025-09-03T11:01:12Z | 0 | 0 | null | [
"lora",
"stable-diffusion",
"flux.1-d",
"license:openrail++",
"region:us"
] | null | 2025-09-03T11:00:50Z | # Golden Age of British Book Illustration: Edmund Dulac
**Base model**: Flux.1 D
**Trained words**: dulac1 illustration
## 🧠 Usage (Python)
🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys)
```python
import requests, os
url = "https://api.muapi.ai/api/... | [] |
inclusionAI/LLaDA2.0-flash-CAP | inclusionAI | 2025-12-27T05:13:49Z | 9 | 10 | 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 | 2025-12-10T12:20:56Z | # LLaDA2.0-flash-CAP
**LLaDA2.0-flash-CAP** is an enhanced version of LLaDA2.0-flash that incorporates **Confidence-Aware Parallel (CAP) Training** for significantly improved inference efficiency. Built upon the 100B-A6B Mixture-of-Experts (MoE) diffusion architecture, this model achieves faster parallel decoding whil... | [
{
"start": 2,
"end": 20,
"text": "LLaDA2.0-flash-CAP",
"label": "benchmark name",
"score": 0.8974512815475464
},
{
"start": 24,
"end": 42,
"text": "LLaDA2.0-flash-CAP",
"label": "benchmark name",
"score": 0.8686606287956238
},
{
"start": 71,
"end": 85,
"te... |
shokuma/qwen3-4b-structured-output-lora-20260219-1st | shokuma | 2026-02-19T11:58:13Z | 8 | 0 | peft | [
"peft",
"safetensors",
"qlora",
"lora",
"structured-output",
"text-generation",
"en",
"ja",
"dataset:daichira/structured-hard-sft-4k",
"base_model:Qwen/Qwen3-4B-Instruct-2507",
"base_model:adapter:Qwen/Qwen3-4B-Instruct-2507",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-02-19T11:58:07Z | qwen3-4b-structured-output-lora-20260219-1st
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... | [] |
contemmcm/525f08f100c05bd8a8f0e51c90d5557c | contemmcm | 2025-11-21T05:50:56Z | 2 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:google-bert/bert-large-uncased-whole-word-masking",
"base_model:finetune:google-bert/bert-large-uncased-whole-word-masking",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible"... | text-classification | 2025-11-21T05:44:04Z | <!-- 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. -->
# 525f08f100c05bd8a8f0e51c90d5557c
This model is a fine-tuned version of [google-bert/bert-large-uncased-whole-word-masking](https:... | [
{
"start": 395,
"end": 421,
"text": "contemmcm/cls_mmlu dataset",
"label": "evaluation dataset",
"score": 0.6717069745063782
},
{
"start": 514,
"end": 527,
"text": "Epoch Runtime",
"label": "evaluation metric",
"score": 0.855216920375824
},
{
"start": 539,
"en... |
priorcomputers/phi-3-medium-4k-instruct-cn-problem-kr0.1-a1.0-creative | priorcomputers | 2026-02-13T07:10:07Z | 0 | 0 | null | [
"safetensors",
"phi3",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"custom_code",
"base_model:microsoft/Phi-3-medium-4k-instruct",
"base_model:finetune:microsoft/Phi-3-medium-4k-instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-13T07:08:04Z | # phi-3-medium-4k-instruct-cn-problem-kr0.1-a1.0-creative
This is a **CreativityNeuro (CN)** modified version of [microsoft/Phi-3-medium-4k-instruct](https://huggingface.co/microsoft/Phi-3-medium-4k-instruct).
## Model Details
- **Base Model**: microsoft/Phi-3-medium-4k-instruct
- **Modification**: CreativityNeuro w... | [] |
Phsntom/tribev2 | Phsntom | 2026-03-29T08:12:50Z | 0 | 0 | null | [
"license:cc-by-nc-4.0",
"region:us"
] | null | 2026-03-29T08:12:50Z | <div align="center">
# TRIBE v2
**A Foundation Model of Vision, Audition, and Language for In-Silico Neuroscience**
[](https://colab.research.google.com/github/facebookresearch/tribev2/blob/main/tribe_demo.ipynb)
[![License: CC BY-NC 4.0](http... | [] |
priorcomputers/qwen2.5-7b-instruct-cn-story-kr0.01-a0.5-creative | priorcomputers | 2026-02-11T21:29:06Z | 0 | 0 | null | [
"safetensors",
"qwen2",
"creativityneuro",
"llm-creativity",
"mechanistic-interpretability",
"base_model:Qwen/Qwen2.5-7B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-7B-Instruct",
"license:apache-2.0",
"region:us"
] | null | 2026-02-11T21:27:21Z | # qwen2.5-7b-instruct-cn-story-kr0.01-a0.5-creative
This is a **CreativityNeuro (CN)** modified version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct).
## Model Details
- **Base Model**: Qwen/Qwen2.5-7B-Instruct
- **Modification**: CreativityNeuro weight scaling
- **Prompt Set**: stor... | [] |
0x3/Qwen3.5-0.8B-MNN | 0x3 | 2026-04-03T10:53:55Z | 0 | 0 | null | [
"chat",
"text-generation",
"en",
"base_model:Qwen/Qwen3.5-0.8B",
"base_model:quantized:Qwen/Qwen3.5-0.8B",
"license:apache-2.0",
"region:us"
] | text-generation | 2026-04-03T10:53:50Z | # Qwen3.5-0.8B-MNN
## Introduction
This model is a 4-bit quantized version of the MNN model exported from Qwen3.5-0.8B using [llmexport](https://github.com/alibaba/MNN/tree/master/transformers/llm/export).
## Download
```bash
# install huggingface
pip install huggingface
```
```bash
# shell download
huggingface downl... | [] |
MiniMaxAI/VTP-Small-f16d64 | MiniMaxAI | 2025-12-16T09:22:49Z | 849 | 12 | transformers | [
"transformers",
"safetensors",
"vtp",
"image-feature-extraction",
"en",
"arxiv:2512.13687",
"license:other",
"endpoints_compatible",
"region:us"
] | image-feature-extraction | 2025-12-16T05:06:02Z | <div align="center">
<img src="figures/logo.png" alt="Logo" width="200"/>
<h2> Towards Scalable Pre-training of Visual Tokenizers for Generation </h2>
[Jingfeng Yao](https://github.com/JingfengYao)<sup>1</sup>, [Yuda Song](https://github.com/IDKiro)<sup>2</sup>, Yucong Zhou<sup>2</sup>, [Xinggang Wang](https://xwcv.... | [] |
vadimbelsky/emirati-fastpitch-bilingual-v1.0 | vadimbelsky | 2026-01-04T07:23:30Z | 7 | 20 | nemo | [
"nemo",
"emirati-arabic",
"bilingual",
"code-switching",
"fastpitch",
"hifigan",
"text-to-speech",
"ar",
"en",
"base_model:vadimbelsky/emirati-fastpitch-bilingual-v1.0",
"base_model:finetune:vadimbelsky/emirati-fastpitch-bilingual-v1.0",
"license:cc-by-4.0",
"model-index",
"region:us"
] | text-to-speech | 2026-01-04T06:52:17Z | # 🇦🇪 Emirati FastPitch v1.0
**A fine-tuned FastPitch text-to-speech model for Emirati Arabic with Arabic–English bilingual code-switching support.**
Designed for natural prosody, dialectal Emirati pronunciation, and seamless AR/EN mixing in real-world speech.
## 🔊 Audio Samples
### 🇦🇪 Full Emirati Arabic
**R... | [] |
xummer/qwen3-8b-belebele-lora-hin-deva | xummer | 2026-03-06T15:23:28Z | 13 | 0 | peft | [
"peft",
"safetensors",
"base_model:adapter:Qwen/Qwen3-8B",
"llama-factory",
"lora",
"transformers",
"text-generation",
"conversational",
"base_model:Qwen/Qwen3-8B",
"license:other",
"region:us"
] | text-generation | 2026-03-06T15:22:46Z | <!-- 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. -->
# belebele_hin_Deva
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the belebele_hin... | [
{
"start": 190,
"end": 207,
"text": "belebele_hin_Deva",
"label": "benchmark name",
"score": 0.6095377206802368
},
{
"start": 248,
"end": 261,
"text": "Qwen/Qwen3-8B",
"label": "benchmark name",
"score": 0.7724800705909729
},
{
"start": 286,
"end": 299,
"t... |
contemmcm/e60a1bc4b438b7d4439dde63776972bd | contemmcm | 2025-11-08T22:41:02Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"bert",
"text-classification",
"generated_from_trainer",
"base_model:google-bert/bert-base-cased",
"base_model:finetune:google-bert/bert-base-cased",
"license:apache-2.0",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | text-classification | 2025-11-08T22:34:25Z | <!-- 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. -->
# e60a1bc4b438b7d4439dde63776972bd
This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/googl... | [
{
"start": 471,
"end": 484,
"text": "Epoch Runtime",
"label": "evaluation metric",
"score": 0.8863803744316101
},
{
"start": 496,
"end": 504,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.8922697305679321
},
{
"start": 506,
"end": 512,
"text... |
shubharthak/gpt2-124m-qa | shubharthak | 2025-11-25T14:17:16Z | 0 | 0 | null | [
"gpt2",
"causal-lm",
"pytorch",
"transformer",
"pretraining",
"sft",
"question-answering",
"ultra-fineweb",
"custom-dataset",
"en",
"license:mit",
"model-index",
"region:us"
] | question-answering | 2025-11-25T13:20:37Z | <p align="center">
<a href="https://huggingface.co/shubharthak/gpt2-124m-qa">
<img alt="Model Size" src="https://img.shields.io/badge/Model%20Size-124M-blue">
</a>
<a href="https://huggingface.co/shubharthak/gpt2-124m-qa">
<img alt="Downloads" src="https://img.shields.io/huggingface/dl-daily/shubharthak/gpt2-124m... | [] |
euswbnix/transformer-wmt14-ende-big | euswbnix | 2026-04-23T01:18:57Z | 0 | 0 | pytorch | [
"pytorch",
"transformer-mt",
"translation",
"transformer",
"from-scratch",
"wmt14",
"en",
"fr",
"dataset:wmt14",
"license:mit",
"region:us"
] | translation | 2026-04-23T01:18:45Z | # Transformer Base — WMT14 en→fr (from scratch)
A **from-scratch PyTorch implementation** of the Transformer (Vaswani et al.,
2017), trained on **WMT14 English→French** without any pretrained weights.
This is the strongest checkpoint from the parent project and the one worth
sharing externally.
| Metric | Value |
|--... | [
{
"start": 21,
"end": 26,
"text": "WMT14",
"label": "benchmark name",
"score": 0.7148208618164062
},
{
"start": 147,
"end": 152,
"text": "WMT14",
"label": "benchmark name",
"score": 0.6478524208068848
},
{
"start": 336,
"end": 340,
"text": "BLEU",
"lab... |
WindyWord/translate-fi-lg | WindyWord | 2026-04-20T13:27:15Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"translation",
"marian",
"windyword",
"finnish",
"ganda",
"fi",
"lg",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | translation | 2026-04-17T03:01:47Z | # WindyWord.ai Translation — Finnish → Ganda
**Translates Finnish → Ganda.**
**Quality Rating: ⭐⭐½ (2.5★ Basic)**
Part of the [WindyWord.ai](https://windyword.ai) translation fleet — 1,800+ proprietary language pairs.
## Quality & Pricing Tier
- **5-star rating:** 2.5★ ⭐⭐½
- **Tier:** Basic
- **Composite score:**... | [
{
"start": 1032,
"end": 1054,
"text": "eBible parallel corpus",
"label": "evaluation dataset",
"score": 0.7875850796699524
}
] |
LumiOpen/llama-hpltv2-edu-classifier-xlm-roberta-large-pan-Guru | LumiOpen | 2025-08-27T11:03:49Z | 2 | 0 | null | [
"safetensors",
"xlm-roberta",
"pan",
"dataset:LumiOpen/hpltv2-llama33-edu-annotation",
"license:apache-2.0",
"region:us"
] | null | 2025-08-27T11:02:56Z | ---
language:
- pan
license: apache-2.0
datasets:
- LumiOpen/hpltv2-llama33-edu-annotation
---
# Llama-HPLT-edu-Panjabi classifier
## Model summary
This is a classifier for judging the educational content of Panjabi (pan-Guru) web pages. It was developed to filter educational content from [HPLT v2](https://hplt-proje... | [] |
praxisresearch/hf_seed_36b_sgtr_syspopped_em_unpop_2 | praxisresearch | 2026-04-29T00:42:05Z | 0 | 0 | peft | [
"peft",
"safetensors",
"seed_oss",
"text-generation",
"axolotl",
"base_model:adapter:models/hf_seed_36b_sgtr_syspopped_2/merged",
"lora",
"transformers",
"conversational",
"region:us"
] | text-generation | 2026-01-27T07:24:07Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" wid... | [] |
zhuojing-huang/gpt2-dutch-english-configC-10k-13 | zhuojing-huang | 2025-12-22T00:41:43Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2025-12-21T11:18:29Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# gpt2-dutch-english-configC-10k-13
This model was trained from scratch on the None dataset.
## Model description
More informatio... | [
{
"start": 557,
"end": 570,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.7981497645378113
},
{
"start": 572,
"end": 577,
"text": "0.002",
"label": "evaluation metric",
"score": 0.7174245119094849
},
{
"start": 603,
"end": 618,
"text": ... |
reefzehavi/readme2 | reefzehavi | 2025-12-11T15:42:02Z | 0 | 0 | null | [
"region:us"
] | null | 2025-12-08T10:22:45Z | # 📉 American Bankruptcy Prediction - Data Science Project
## 📌 Project Overview
This project applies end-to-end Machine Learning techniques to predict whether an American company will go bankrupt based on financial data.
The dataset contains financial attributes (X1-X18) for thousands of companies. The project foll... | [] |
2qbdp5/ppo-SnowballTarget | 2qbdp5 | 2026-01-03T12:24:36Z | 0 | 0 | ml-agents | [
"ml-agents",
"tensorboard",
"onnx",
"SnowballTarget",
"deep-reinforcement-learning",
"reinforcement-learning",
"ML-Agents-SnowballTarget",
"region:us"
] | reinforcement-learning | 2026-01-03T12:24:32Z | # **ppo** Agent playing **SnowballTarget**
This is a trained model of a **ppo** agent playing **SnowballTarget**
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-Do... | [] |
LDD11/pusht_act_chunk50_action20_lr2e5_40000 | LDD11 | 2026-04-09T13:38:39Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"act",
"robotics",
"dataset:lerobot/pusht",
"arxiv:2304.13705",
"license:apache-2.0",
"region:us"
] | robotics | 2026-04-09T11:27:54Z | # 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": "evaluation dataset",
"score": 0.6181951761245728
},
{
"start": 120,
"end": 123,
"text": "ACT",
"label": "evaluation dataset",
"score": 0.6971622109413147
},
{
"start": 865,
"end": 868,
"text": "act",
"... |
ReadyArt/Darkness-Incarnate-24B-v3-EXL3 | ReadyArt | 2025-10-24T10:51:07Z | 0 | 1 | null | [
"nsfw",
"explicit",
"roleplay",
"unaligned",
"dangerous",
"ERP",
"license:other",
"region:us"
] | null | 2025-10-24T08:12:51Z | <style>
body {
font-family: 'Quicksand', sans-serif;
background: linear-gradient(135deg, #0a1a1a 0%, #001010 100%);
color: #e1ffff !important;
text-shadow: 0 0 3px rgba(0, 0, 0, 0.7);
margin: 0;
padding: 20px;
transition: all 0.5s ease;
}
@media (prefers-color-scheme: light) {
body {
... | [] |
honcabanthan/lerobot_groot_v1 | honcabanthan | 2025-11-19T01:08:46Z | 0 | 0 | lerobot | [
"lerobot",
"safetensors",
"groot",
"robotics",
"dataset:honcabanthan/lerobot-liamlab-v1",
"license:apache-2.0",
"region:us"
] | robotics | 2025-11-19T01:07:23Z | # Model Card for groot
<!-- Provide a quick summary of what the model is/does. -->
_Model type not recognized — please update this template._
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.... | [] |
agii0114/20260407-gguf | agii0114 | 2026-04-07T06:57:08Z | 0 | 0 | null | [
"gguf",
"llama",
"llama.cpp",
"unsloth",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-04-07T04:26:53Z | # 20260407-gguf : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `llama-cli -hf agii0114/20260407-gguf --jinja`
- For multimodal models: `llama-mtmd-cli -hf agii0114/20260407-gguf --jinja`
## Available Mode... | [] |
wallacebf/AurIA-G3-v1 | wallacebf | 2026-02-23T06:36:11Z | 26 | 1 | null | [
"safetensors",
"gguf",
"gemma3",
"llama.cpp",
"unsloth",
"vision-language-model",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2026-02-23T05:26:34Z | # AurIA-G3-v1 : GGUF
This model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).
**Example usage**:
- For text only LLMs: `./llama.cpp/llama-cli -hf wallacebf/AurIA-G3-v1 --jinja`
- For multimodal models: `./llama.cpp/llama-mtmd-cli -hf wallacebf/AurIA-G3-v1 --jinja... | [] |
Cisco1963/llmplasticity-en_fi_linear_0.5_1-seed42 | Cisco1963 | 2026-04-02T18:41:08Z | 0 | 0 | transformers | [
"transformers",
"safetensors",
"gpt2",
"text-generation",
"generated_from_trainer",
"base_model:openai-community/gpt2",
"base_model:finetune:openai-community/gpt2",
"license:mit",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text-generation | 2026-04-02T12:52:37Z | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llmplasticity-en_fi_linear_0.5_1-seed42
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dat... | [
{
"start": 400,
"end": 408,
"text": "Accuracy",
"label": "evaluation metric",
"score": 0.8821181058883667
},
{
"start": 692,
"end": 705,
"text": "learning_rate",
"label": "evaluation metric",
"score": 0.6832985877990723
},
{
"start": 707,
"end": 712,
"text... |
phanerozoic/threshold-exactly4outof8 | phanerozoic | 2026-01-22T17:25:47Z | 1 | 0 | null | [
"safetensors",
"pytorch",
"threshold-logic",
"neuromorphic",
"license:mit",
"region:us"
] | null | 2026-01-22T17:20:08Z | # threshold-exactly4outof8
Exactly-4-out-of-8 detector. Fires when precisely half the inputs are active. The tie detector.
## Circuit
```
x₀ x₁ x₂ x₃ x₄ x₅ x₆ x₇
│ │ │ │ │ │ │ │
└──┴──┴──┴──┼──┴──┴──┴──┘
│
┌───────┴───────┐
▼ ▼
┌─────────┐ ... | [] |
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