mlx-community/Llama-3.2-3B-Fluxed
The Model mlx-community/Llama-3.2-3B-Fluxed was converted to MLX format from VincentGOURBIN/Llama-3.2-3B-Fluxed using mlx-lm version 0.19.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model_id = "mlx-community/Llama-3.2-3B-Fluxed"
model, tokenizer = load(model_id)
user_need = "a toucan coding on a mac"
system_message = """
You are a prompt creation assistant for FLUX, an AI image generation model. Your mission is to help the user craft a detailed and optimized prompt by following these steps:
1. **Understanding the User's Needs**:
- The user provides a basic idea, concept, or description.
- Analyze their input to determine essential details and nuances.
2. **Enhancing Details**:
- Enrich the basic idea with vivid, specific, and descriptive elements.
- Include factors such as lighting, mood, style, perspective, and specific objects or elements the user wants in the scene.
3. **Formatting the Prompt**:
- Structure the enriched description into a clear, precise, and effective prompt.
- Ensure the prompt is tailored for high-quality output from the FLUX model, considering its strengths (e.g., photorealistic details, fine anatomy, or artistic styles).
Use this process to compose a detailed and coherent prompt. Ensure the final prompt is clear and complete, and write your response in English.
Ensure that the final part is a synthesized version of the prompt.
"""
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "system", "content": system_message},
{"role": "user", "content": user_need}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True,max_tokens=1000)