Instructions to use mlx-community/stablelm-2-12b-chat-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/stablelm-2-12b-chat-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir stablelm-2-12b-chat-4bit mlx-community/stablelm-2-12b-chat-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Create README.md
Browse files
README.md
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---
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language:
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- en
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license: other
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tags:
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- causal-lm
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- mlx
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datasets:
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- HuggingFaceH4/ultrachat_200k
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- allenai/ultrafeedback_binarized_cleaned
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- meta-math/MetaMathQA
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- WizardLM/WizardLM_evol_instruct_V2_196k
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- openchat/openchat_sharegpt4_dataset
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- LDJnr/Capybara
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- Intel/orca_dpo_pairs
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- hkust-nlp/deita-10k-v0
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- teknium/OpenHermes-2.5
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extra_gated_fields:
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Name: text
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Email: text
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Country: text
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Organization or Affiliation: text
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I ALLOW Stability AI to email me about new model releases: checkbox
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---
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# mlx-community/stablelm-2-12b-chat-4bit
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This model was converted to MLX format from [`stabilityai/stablelm-2-12b-chat`]() using mlx-lm version **0.8.0**.
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Model added by [Prince Canuma](https://twitter.com/Prince_Canuma).
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Refer to the [original model card](https://huggingface.co/stabilityai/stablelm-2-12b-chat) for more details on the model.
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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/stablelm-2-12b-chat-4bit")
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response = generate(model, tokenizer, prompt="hello", verbose=True)
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```
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