metadata
license: apache-2.0
language:
- en
base_model: SupraLabs/Supra-1.5-50M-Instruct-exp
pipeline_tag: text-generation
tags:
- Supra
- Project-Chimera
- chimera
- QnA
- GPT
- CPU
- tiny
- SLM
- open
- open-source
- 50M
- llama
- mlx
usermma/Supra-1.5-50M-Instruct-exp-mlx-8bit
The Model usermma/Supra-1.5-50M-Instruct-exp-mlx-8bit was converted to MLX format from SupraLabs/Supra-1.5-50M-Instruct-exp using mlx-lm version 0.31.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("usermma/Supra-1.5-50M-Instruct-exp-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)