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 | |
# mlx-community/dolphin-2.9.4-gemma2-2b-4bit | |
The Model [mlx-community/dolphin-2.9.4-gemma2-2b-4bit](https://huggingface.co/mlx-community/dolphin-2.9.4-gemma2-2b-4bit) 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("mlx-community/dolphin-2.9.4-gemma2-2b-4bit") | |
response = generate(model, tokenizer, prompt="hello", verbose=True) | |
``` | |