metadata
license: llama3.3
datasets:
- DebateLabKIT/deepa2-conversations
- DebateLabKIT/deep-argmap-conversations
- allenai/tulu-3-sft-mixture
base_model: DebateLabKIT/Llama-3.3-Argunaut-1-70B-SFT
pipeline_tag: text-generation
library_name: transformers
tags:
- logic
- argumentation
- critical-thinking
- argument-mapping
- trl
- sft
- mlx
- mlx-my-repo
ggbetz/Llama-3.3-Argunaut-1-70B-SFT-Q4-mlx
The Model ggbetz/Llama-3.3-Argunaut-1-70B-SFT-Q4-mlx was converted to MLX format from DebateLabKIT/Llama-3.3-Argunaut-1-70B-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-3.3-Argunaut-1-70B-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)