metadata
license: other
tags:
- generated_from_trainer
- mlx
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- cognitivecomputations/Dolphin-2.9
- teknium/OpenHermes-2.5
- m-a-p/CodeFeedback-Filtered-Instruction
- cognitivecomputations/dolphin-coder
- cognitivecomputations/samantha-data
- HuggingFaceH4/ultrachat_200k
- microsoft/orca-math-word-problems-200k
- abacusai/SystemChat-1.1
- Locutusque/function-calling-chatml
- internlm/Agent-FLAN
model-index:
- name: out
results: []
3thn/dolphin-2.9-llama3-8b-4bit
This model was converted to MLX format from cognitivecomputations/dolphin-2.9-llama3-8b
using mlx-lm version 0.10.0.
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("3thn/dolphin-2.9-llama3-8b-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)