07/03: ⚠️ make sure your torch (>=2.10) & cuda (>=13.0) are up to date, otherwise you won't see a speed boost using nvfp4, may even be slower ⚠️ Various formats of LTX-2.3, all created from official BF16 versions. Made with Silveroxides/convert_to_quant script: Smaller formats look a bit "fuzzy" around the edges in the outputs, but motion, audio, and lighting are still looking good.
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View details ↗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-Ternary** series come from prism-ml/Ternary-Bonsai-2-27B-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. The size after conversion may differ from the original GGUF (Some of the weights are converted from PTQ1 to Q2_K or Q3_K.). This is just a test/validation. The ternary hybrid-attention kernels live in the PrismML-Eng/llama.cpp fork. **Stock llama.cpp will not run these files.**
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View details ↗本项目基于Mistral发布的模型Mixtral-8x7B进行了中文扩词表增量预训练,希望进一步促进中文自然语言处理社区对MoE模型的研究。我们扩充后的词表显著提高了模型对中文的编解码效率,并通过大规模开源语料对扩词表模型进行增量预训练,使模型具备了强大的中文生成和理解能力。 Chinese-Mixtral-8x7B支持完整的Mixtral-8x7B模型生态,包括使用`vLLM`、`Flash Attention 2`进行加速,使用`bitsandbytes`进行模型量化等。以下是使用Chinese-Mixtral-8x7B进行推理的代码示例。 根据Mistral发布的技术报告,Mixtral-8x7B在推理时将激活13B参数。下表为Chinese-Mixtral-8x7B与其他13B规模的中文扩词表模型在各个评测数据集上的5-shot结果:
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