README.md

metadata

license: llama3
language:
  - en
tags:
  - finance
  - mlx
datasets:
  - Open-Orca/OpenOrca
  - GAIR/lima
  - WizardLM/WizardLM_evol_instruct_V2_196k
base_model: instruction-pretrain/finance-Llama3-8B
pipeline_tag: text-generation
library_name: mlx

tniccum21/finance-Llama3-8B

This model tniccum21/finance-Llama3-8B was converted to MLX format from instruction-pretrain/finance-Llama3-8B using mlx-lm version 0.24.0.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("tniccum21/finance-Llama3-8B")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)