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AI モデル 450

• Llama-3.2-3B-Instruct-abliterated-GGUF↗

  QuantFactory

  library_name: transformers license: llama3.2 base_model: meta-llama/Llama-3.2-3B-Instruct tags: - abliterated - uncensored This is quantized version of huihui-ai/Llama-3.2-3B-Instruct-abliterated created using llama.cpp This is an uncensored version of Llama 3.2 3B Instruct created with abliteration (see this article to know more about it).

• Dia-1.6B↗

  nari-labs

  Dia is a 1.6B parameter text to speech model created by Nari Labs. It was pushed to the Hub using the PytorchModelHubMixin integration. Dia **directly generates highly realistic dialogue from a transcript**. You can condition the output on audio, enabling emotion and tone control. The model can also produce nonverbal communications like laughter, coughing, clearing throat, etc. To accelerate research, we are providing access to pretrained model checkpoints and inference code. The model weights are hosted on Hugging Face. The model only supports English generation at the moment.

• ibm-granite_-_granite-20b-code-instruct-gguf↗

  RichardErkhov

  granite-20b-code-instruct - GGUF - Model creator: https://huggingface.co/ibm-granite/ - Original model: https://huggingface.co/ibm-granite/granite-20b-code-instruct/ Original model description: --- pipeline_tag: text-generation base_model: ibm-granite/granite-20b-code-base inference: true license: apache-2.0 datasets: - bigcode/commitpackft - TIGER-Lab/MathInstruct - meta-math/MetaMathQA - glaiveai/glaive-code-assistant-v3 - glaive-function-calling-v2 - bugdaryan/sql-create-context-instruction - garage-bAInd/Open-Platypus - nvidia/HelpSteer metrics: - code_eval library_name: transformers tags: - code - granite model-index: - name: granite-20b-code-instruct results: - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalSynthesis(Python) metrics: - name: pass@1 type: pass@1 value: 60.4 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalSynthesis(JavaScript) metrics: - name: pass@1 type: pass@1 value: 53.7 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalSynthesis(Java) metrics: - name: pass@1 type: pass@1 value: 58.5 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalSynthesis(Go) metrics: - name: pass@1 type: pass@1 value: 42.1 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalSynthesis(C++) metrics: - name: pass@1 type: pass@1 value: 45.7 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalSynthesis(Rust) metrics: - name: pass@1 type: pass@1 value: 42.7 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalExplain(Python) metrics: - name: pass@1 type: pass@1 value: 44.5 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalExplain(JavaScript) metrics: - name: pass@1 type: pass@1 value: 42.7 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalExplain(Java) metrics: - name: pass@1 type: pass@1 value: 49.4 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalExplain(Go) metrics: - name: pass@1 type: pass@1 value: 32.3 veriefied: false - task: type: text-generation dataset: type: bigcode/humanevalpack name: HumanEvalE

• Huihui-Qwen3-4B-Instruct-2507-abliterated↗

  huihui-ai

  This is an uncensored version of Qwen/Qwen3-4B-Instruct-2507 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use this model in your applications by loading it with Hugging Face's `transformers` library: If you like it, please click 'like' and follow us for more updates. You can follow x.com/support_huihui to get the latest model information from huihui.ai.

• Huihui-NeoHorse-1-4B-abliterated-GGUF↗

  huihui-ai

  This is an uncensored version of TokenRhythm/NeoHorse-1-4B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The MTP and Visual components were extracted from the original Qwen/Qwen3.5-4B and can provide excellent support.

• Wan2.1_14B_VACE-GGUF↗

  QuantStack

  This is a direct GGUF conversion of Wan-AI/Wan2.1-VACE-14B All quants are created from the FP32 base file, though I only uploaded the Q8_0 and less, if you want the F16 or BF16 one I would upload it per request. The model files can be used with the ComfyUI-GGUF custom node.

• create-nsfw↗

  Bigfawg6669

  The **FLUX Uncensored LoRA v2** is an enhanced version of the original FLUX Uncensored LoRA, designed for the base model `black-forest-labs/FLUX.1-dev`. This version addresses issues present in the previous release and offers improved performance and stability. The LoRA weights have been fine-tuned to remove the base model's content restrictions, allowing for the generation of NSFW (Not Safe For Work) and other uncensored content. This LoRA extension can be loaded into the `FLUX.1-dev` pipeline using the `diffusers` library. It is optimized for high-quality, explicit image generation based on user-provided prompts. The model is intended for research and personal use, and adheres to the non-commercial license terms. > **Warning:** This model allows the generation of explicit content. Users should exercise caution and adhere to legal and ethical guidelines.

• Huihui-Qwen3.8-27B-abliterated-GGUF↗

  yachiyo8080

  This is an uncensored version of Qwen/Qwen3.8-27B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The newly added **Huihui-Qwen3.8-27B-abliterated-Underdog-Saluki** series come from ConwayResearch/Underdog-Saluki-27B-1.0 and ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. Due to ConwayResearch/Underdog-Saluki-27B-1.0 not providing an imatrix file, we will attempt to perform ablation by mixing the GGUF weights of Swift-1.5 and ConwayResearch/Underdog-Saluki-27B-1.0.

• QwQ-32B-MLX-4bit↗

  lmstudio-community

  *👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord*. Compatibility: Apple Silicon Macs **Model creator:** Qwen **Original model**: QwQ-32B **MLX quantizations:** provided by bartowski from mlx-examples LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models. LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.

• gemma-3-12b-it-lenientchatfix↗

  m8than

  * [Gemma 3 Technical Report][g3-tech-report] * [Responsible Generative AI Toolkit][rai-toolkit] * [Gemma on Kaggle][kaggle-gemma] * [Gemma on Vertex Model Garden][vertex-mg-gemma3] Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma 3 models are multimodal, handling text and image input and generating text output, with open weights for both pre-trained variants and instruction-tuned variants. Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. - **Input:** - Text string, such as a question, a prompt, or a document to be summarized - Images, normalized to 896 x 896 resolution and encoded to 256 tokens each - Total input context of 128K tokens for the 4B, 12B, and 27B sizes, and 32K tokens for the 1B size