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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ datasets:
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+ - anthracite-org/kalo-opus-instruct-22k-no-refusal
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+ - Nopm/Opus_WritingStruct
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+ - Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
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+ - Gryphe/Sonnet3.5-Charcard-Roleplay
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+ - Gryphe/ChatGPT-4o-Writing-Prompts
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+ - Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
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+ - Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
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+ - nothingiisreal/Reddit-Dirty-And-WritingPrompts
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+ - allura-org/Celeste-1.x-data-mixture
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+ - cognitivecomputations/dolphin-2.9.3
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+ base_model: GoraPakora/QwenQwen2
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+ tags:
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+ - generated_from_trainer
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+ - mlx
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+ - mlx-my-repo
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+ model-index:
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+ - name: EVA-Qwen2.5-32B-SFFT-v0.1
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+ results: []
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+ ---
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+
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+ # Fmuaddib/QwenQwen2-mlx-8Bit
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+
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+ The Model [Fmuaddib/QwenQwen2-mlx-8Bit](https://huggingface.co/Fmuaddib/QwenQwen2-mlx-8Bit) was converted to MLX format from [GoraPakora/QwenQwen2](https://huggingface.co/GoraPakora/QwenQwen2) using mlx-lm version **0.22.1**.
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+
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+ ## Use with mlx
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+
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+ ```bash
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+ pip install mlx-lm
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+ ```
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("Fmuaddib/QwenQwen2-mlx-8Bit")
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+
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+ prompt="hello"
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+
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+ if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
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+ messages = [{"role": "user", "content": prompt}]
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+ prompt = tokenizer.apply_chat_template(
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+ messages, tokenize=False, add_generation_prompt=True
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+ )
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+
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+ response = generate(model, tokenizer, prompt=prompt, verbose=True)
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+ ```