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)
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Model size
2B params
Tensor type
F16
ยท
MLX
Hardware compatibility
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andito/mlx_summarization ยท Hugging Face

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)
Downloads last month
10
Safetensors
Model size
2B params
Tensor type
F16
ยท
MLX
Hardware compatibility
Log In to add your hardware

Quantized

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for andito/mlx_summarization