metadata
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-mlx
The Model mlx-community/dolphin-2.9.4-gemma2-2b-mlx was converted to MLX format from cognitivecomputations/dolphin-2.9.4-gemma2-2b using mlx-lm version 0.17.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/dolphin-2.9.4-gemma2-2b-mlx")
response = generate(model, tokenizer, prompt="hello", verbose=True)