metadata
license: llama3
tags:
- generated_from_trainer
- axolotl
- mlx
base_model: meta-llama/Meta-Llama-3-70B
datasets:
- cognitivecomputations/Dolphin-2.9
- teknium/OpenHermes-2.5
- m-a-p/CodeFeedback-Filtered-Instruction
- cognitivecomputations/dolphin-coder
- cognitivecomputations/samantha-data
- microsoft/orca-math-word-problems-200k
- Locutusque/function-calling-chatml
- internlm/Agent-FLAN
model-index:
- name: out
results: []
mlx-community/dolphin-2.9.1-llama-3-70b-2bit
This model was converted to MLX format from cognitivecomputations/dolphin-2.9.1-llama-3-70b
using mlx-lm version 0.12.1.
Refer to the original model card for more details on the model.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/dolphin-2.9.1-llama-3-70b-2bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)