SiddhJagani/cac-v0.1-mlx-Q2
The Model SiddhJagani/cac-v0.1-mlx-Q2 was converted to MLX format from codemateai/cac-v0.1 using mlx-lm version 0.28.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("SiddhJagani/cac-v0.1-mlx-Q2")
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
0.6B params
Tensor type
F16
·
U32 ·
Hardware compatibility
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2-bit
Model tree for SiddhJagani/cac-v0.1-mlx-Q2
Base model
deepseek-ai/deepseek-coder-6.7b-base Finetuned
codemateai/cac-v0.1