andito_-_mlx_summarization-gguf

Quantization made by Richard Erkhov.

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mlx_summarization - GGUF

• Model creator: https://huggingface.co/andito/
• Original model: https://huggingface.co/andito/mlx_summarization/

Original model description:

library_name: transformers tags:

• mlx base_model: HuggingFaceTB/SmolLM2-1.7B-Intermediate-SFT-v2-summarization-lora-r32-a64-merged-2

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andito/mlx_summarization

The Model andito/mlx_summarization was converted to MLX format from HuggingFaceTB/SmolLM2-1.7B-Intermediate-SFT-v2-summarization-lora-r32-a64-merged-2 using mlx-lm version 0.19.2.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("andito/mlx_summarization")

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)