README.md

metadata

license: llama3.1
datasets:
  - DebateLabKIT/deepa2-conversations
  - DebateLabKIT/deep-argmap-conversations
  - allenai/tulu-3-sft-mixture
base_model: DebateLabKIT/Llama-3.1-Argunaut-1-8B-SFT
pipeline_tag: text-generation
library_name: transformers
tags:
  - logic
  - argumentation
  - critical-thinking
  - argument-mapping
  - trl
  - sft
  - mlx
  - mlx-my-repo

ggbetz/Llama-3.1-Argunaut-1-8B-SFT-Q4-mlx

The Model ggbetz/Llama-3.1-Argunaut-1-8B-SFT-Q4-mlx was converted to MLX format from DebateLabKIT/Llama-3.1-Argunaut-1-8B-SFT using mlx-lm version 0.20.5.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("ggbetz/Llama-3.1-Argunaut-1-8B-SFT-Q4-mlx")

prompt="hello"

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

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