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--- |
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base_model: karakuri-ai/karakuri-lm-8x7b-instruct-v0.1 |
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datasets: |
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- databricks/databricks-dolly-15k |
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- glaiveai/glaive-code-assistant-v3 |
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- glaiveai/glaive-function-calling-v2 |
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- gretelai/synthetic_text_to_sql |
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- meta-math/MetaMathQA |
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- microsoft/orca-math-word-problems-200k |
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- neural-bridge/rag-dataset-12000 |
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- neural-bridge/rag-hallucination-dataset-1000 |
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- nvidia/HelpSteer |
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- OpenAssistant/oasst2 |
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language: |
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- en |
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- ja |
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library_name: transformers |
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license: apache-2.0 |
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tags: |
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- mixtral |
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- steerlm |
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- mlx |
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--- |
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# mlx-community/karakuri-lm-8x7b-instruct-v0.1 |
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The Model [mlx-community/karakuri-lm-8x7b-instruct-v0.1](https://huggingface.co/mlx-community/karakuri-lm-8x7b-instruct-v0.1) was converted to MLX format from [karakuri-ai/karakuri-lm-8x7b-instruct-v0.1](https://huggingface.co/karakuri-ai/karakuri-lm-8x7b-instruct-v0.1) using mlx-lm version **0.19.0**. |
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## Use with mlx |
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```bash |
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pip install mlx-lm |
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``` |
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```python |
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from mlx_lm import load, generate |
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model, tokenizer = load("mlx-community/karakuri-lm-8x7b-instruct-v0.1") |
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prompt="hello" |
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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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response = generate(model, tokenizer, prompt=prompt, verbose=True) |
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``` |
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