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metadata
license: apache-2.0
base_model: unsloth/SmolLM-1.7B-Instruct
tags:
  - alignment-handbook
  - trl
  - unsloth
  - mlx
datasets:
  - Magpie-Align/Magpie-Pro-300K-Filtered
  - bigcode/self-oss-instruct-sc2-exec-filter-50k
  - teknium/OpenHermes-2.5
  - HuggingFaceTB/everyday-conversations-llama3.1-2k
library_name: transformers
language:
  - en

shashikanth-a/SmolLM-1.7B-Instruct-4bit

The Model shashikanth-a/SmolLM-1.7B-Instruct-4bit was converted to MLX format from unsloth/SmolLM-1.7B-Instruct using mlx-lm version 0.19.3.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("shashikanth-a/SmolLM-1.7B-Instruct-4bit")

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)