license: apache-2.0
base_model: DavidAU/Llama-3.2-PKD-Deckard-Almost-Human-abliterated-uncensored-7B
datasets:

• DavidAU/The-works-PK-Dick
  language:
• en
  pipeline_tag: text-generation
  tags:
• programming
• code generation
• code
• coding
• coder
• chat
• brainstorm
• llama 3.2
• llama
• llama-3.2
• brainstorm 40x
• all uses cases
• finetune
• unsloth
• not-for-all-audiences
• mlx
  library_name: mlx

Llama-3.2-PKD-Deckard-Almost-Human-abliterated-uncensored-7B-qx86-hi-mlx

This model Llama-3.2-PKD-Deckard-Almost-Human-abliterated-uncensored-7B-qx86-hi-mlx was
converted to MLX format from DavidAU/Llama-3.2-PKD-Deckard-Almost-Human-abliterated-uncensored-7B
using mlx-lm version 0.28.0.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("Llama-3.2-PKD-Deckard-Almost-Human-abliterated-uncensored-7B-qx86-hi-mlx")

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)