Instructions to use mlx-community/Mellum-4b-sft-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Mellum-4b-sft-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("mlx-community/Mellum-4b-sft-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 mlx-community/Mellum-4b-sft-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 "mlx-community/Mellum-4b-sft-python" --prompt "Once upon a time"
| license: apache-2.0 | |
| datasets: | |
| - bigcode/the-stack | |
| - bigcode/the-stack-v2 | |
| - bigcode/starcoderdata | |
| - bigcode/commitpack | |
| library_name: mlx | |
| tags: | |
| - code | |
| - mlx | |
| base_model: JetBrains/Mellum-4b-sft-python | |
| pipeline_tag: text-generation | |
| model-index: | |
| - name: Mellum-4b-sft-python | |
| results: | |
| - task: | |
| type: text-generation | |
| dataset: | |
| name: RepoBench 1.1 (Python) | |
| type: tianyang/repobench_python_v1.1 | |
| metrics: | |
| - type: exact_match | |
| value: 0.2837 | |
| name: EM | |
| verified: false | |
| - type: exact_match | |
| value: 0.2987 | |
| name: EM ≤ 8k | |
| verified: false | |
| - type: exact_match | |
| value: 0.2924 | |
| name: EM | |
| verified: false | |
| - type: exact_match | |
| value: 0.306 | |
| name: EM | |
| verified: false | |
| - type: exact_match | |
| value: 0.2977 | |
| name: EM | |
| verified: false | |
| - type: exact_match | |
| value: 0.268 | |
| name: EM | |
| verified: false | |
| - type: exact_match | |
| value: 0.2543 | |
| name: EM | |
| verified: false | |
| - task: | |
| type: text-generation | |
| dataset: | |
| name: SAFIM | |
| type: gonglinyuan/safim | |
| metrics: | |
| - type: pass@1 | |
| value: 0.4212 | |
| name: pass@1 | |
| verified: false | |
| - type: pass@1 | |
| value: 0.3316 | |
| name: pass@1 | |
| verified: false | |
| - type: pass@1 | |
| value: 0.3611 | |
| name: pass@1 | |
| verified: false | |
| - type: pass@1 | |
| value: 0.571 | |
| name: pass@1 | |
| verified: false | |
| - task: | |
| type: text-generation | |
| dataset: | |
| name: HumanEval Infilling (Single-Line) | |
| type: loubnabnl/humaneval_infilling | |
| metrics: | |
| - type: pass@1 | |
| value: 0.8045 | |
| name: pass@1 | |
| verified: false | |
| - type: pass@1 | |
| value: 0.4819 | |
| name: pass@1 | |
| verified: false | |
| - type: pass@1 | |
| value: 0.3768 | |
| name: pass@1 | |
| verified: false | |
| # mlx-community/Mellum-4b-sft-python | |
| This model [mlx-community/Mellum-4b-sft-python](https://huggingface.co/mlx-community/Mellum-4b-sft-python) was | |
| converted to MLX format from [JetBrains/Mellum-4b-sft-python](https://huggingface.co/JetBrains/Mellum-4b-sft-python) | |
| using mlx-lm version **0.25.2**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("mlx-community/Mellum-4b-sft-python") | |
| prompt = "hello" | |
| if tokenizer.chat_template is not None: | |
| messages = [{"role": "user", "content": prompt}] | |
| prompt = tokenizer.apply_chat_template( | |
| messages, add_generation_prompt=True | |
| ) | |
| response = generate(model, tokenizer, prompt=prompt, verbose=True) | |
| ``` | |