README.md

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

cmcmaster/rheum-dolphin-2.9.4-gemma2-2b

The Model cmcmaster/rheum-dolphin-2.9.4-gemma2-2b was converted to MLX format from cognitivecomputations/dolphin-2.9.4-gemma2-2b using mlx-lm version 0.18.0.

Use with mlx

pip install mlx-lm

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)