metadata
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)