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coderavi/Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-High-Reasoning-mlx-8Bit
Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-High-Reasoning-mlx-8Bit is a text generation model from coderavi. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
The Model coderavi/Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-High-Reasoning-mlx-8Bit was converted to MLX format from DavidAU/Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-Hig…
Downloads · 30 days
2.1K
8% of all-time downloads
All-time downloads
25.5K
Public
Parameters
8B
8.5 GB on disk
Likes
13
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.safetensors8.5 GB · 100%
How the weights are stored.
U328B · 100%
From the Hugging Face model README
The Model coderavi/Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-High-Reasoning-mlx-8Bit was converted to MLX format from DavidAU/Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-High-Reasoning using mlx-lm version 0.29.1.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("coderavi/Llama3.3-8B-Instruct-Thinking-Heretic-Uncensored-Claude-4.5-Opus-High-Reasoning-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)