Instructions to use ArmandS11/DeepSeekR1-7B-FineTuned-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use ArmandS11/DeepSeekR1-7B-FineTuned-python with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("ArmandS11/DeepSeekR1-7B-FineTuned-python") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use ArmandS11/DeepSeekR1-7B-FineTuned-python with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "ArmandS11/DeepSeekR1-7B-FineTuned-python" --prompt "Once upon a time"
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license: mit
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---
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license: mit
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datasets:
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- iamtarun/python_code_instructions_18k_alpaca
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language:
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- en
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
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pipeline_tag: text-generation
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library_name: mlx
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tags:
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- python
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- code
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- lora
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- fine-tuned
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