| base_model: google/gemma-2-2b | |
| datasets: | |
| - cognitivecomputations/Dolphin-2.9 | |
| - m-a-p/CodeFeedback-Filtered-Instruction | |
| - cognitivecomputations/dolphin-coder | |
| - cognitivecomputations/samantha-data | |
| - microsoft/orca-math-word-problems-200k | |
| - mlabonne/FineTome-100k | |
| - arcee/agent_data | |
| - PawanKrd/math-gpt-4o-200k | |
| - cognitivecomputations/SystemChat-2.0 | |
| license: gemma | |
| tags: | |
| - generated_from_trainer | |
| - mlx | |
| # cmcmaster/rheum-dolphin-2.9.4-gemma2-2b | |
| The Model [cmcmaster/rheum-dolphin-2.9.4-gemma2-2b](https://huggingface.co/cmcmaster/rheum-dolphin-2.9.4-gemma2-2b) was converted to MLX format from [cognitivecomputations/dolphin-2.9.4-gemma2-2b](https://huggingface.co/cognitivecomputations/dolphin-2.9.4-gemma2-2b) using mlx-lm version **0.18.0**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("cmcmaster/rheum-dolphin-2.9.4-gemma2-2b") | |
| response = generate(model, tokenizer, prompt="hello", verbose=True) | |
| ``` | |