Repository: localaiLicense: apache-2.0

# 🔥 Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled A reasoning SFT fine-tune of `Qwen/Qwen3.6-35B-A3B` on chain-of-thought (CoT) distillation mostly sourced from Claude Opus 4.6. The goal is to preserve Qwen3.6's strong agentic coding and reasoning base while nudging the model toward structured Claude Opus-style reasoning traces and more stable long-form problem solving. The training path is text-only. The Qwen3.6 base architecture includes a vision encoder, but this fine-tuning run did not train on image or video examples. - **Developed by:** @hesamation - **Base model:** `Qwen/Qwen3.6-35B-A3B` - **License:** apache-2.0 This fine-tuning run is inspired by Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled, including the notebook/training workflow style and Claude Opus reasoning-distillation direction. [](https://x.com/Hesamation) [](https://discord.gg/vtJykN3t) ## Benchmark Results The MMLU-Pro pass used 70 total questions per model: `--limit 5` across 14 MMLU-Pro subjects. Treat this as a smoke/comparative check, not a release-quality full benchmark. ...
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This is an uncensored version of unsloth/gpt-oss-20b-BF16 created with abliteration (see remove-refusals-with-transformers to know more about it).
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Developed by: EpistemeAI License: apache-2.0 Finetuned from model : unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit Finetuned methods: DPO (Direct Preference Optimization) & ORPO (Odds Ratio Preference Optimization)
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Repository: localaiLicense: apache-2.0
Alongside the release of Pygmalion-3, we present an additional roleplay model based on Mistral's Nemo Base named Eleusis, a unique model that has a distinct voice among its peers. Though it was meant to be a test run for further experiments, this model was received warmly to the point where we felt it was right to release it publicly. We release the weights of Eleusis under the Apache 2.0 license, ensuring a free and open ecosystem for it to flourish under.
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Repository: localaiLicense: apache-2.0
FLUX.1 [schnell] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post. Key Features Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives. Trained using latent adversarial diffusion distillation, FLUX.1 [schnell] can generate high-quality images in only 1 to 4 steps. Released under the apache-2.0 licence, the model can be used for personal, scientific, and commercial purposes.
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