README.md

metadata

tags:
  - autotrain
  - text-generation-inference
  - text-generation
  - peft
  - mlx
library_name: transformers
base_model: ben-at-jorah/emergency-llama32-1b-finetune-rmsys3
widget:
  - messages:
      - role: user
        content: What is your favorite condiment?
license: other
datasets:
  - ben-at-jorah/emergency-training-data_2024-11-20

ben-at-jorah/emergency-llama32-1b-finetune-rmsys3_mlx-8bit

The Model ben-at-jorah/emergency-llama32-1b-finetune-rmsys3_mlx-8bit was converted to MLX format from ben-at-jorah/emergency-llama32-1b-finetune-rmsys3 using mlx-lm version 0.19.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("ben-at-jorah/emergency-llama32-1b-finetune-rmsys3_mlx-8bit")

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)