metadata
license: apache-2.0
pipeline_tag: text-generation
language:
- en
- he
tags:
- pretrained
- mlx
- mlx-my-repo
inference:
parameters:
temperature: 0.6
base_model: dicta-il/DictaLM-3.0-1.7B-Instruct
ssdataanalysis/DictaLM-3.0-1.7B-Instruct-mlx-8Bit
The Model ssdataanalysis/DictaLM-3.0-1.7B-Instruct-mlx-8Bit was converted to MLX format from dicta-il/DictaLM-3.0-1.7B-Instruct using mlx-lm version 0.29.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("ssdataanalysis/DictaLM-3.0-1.7B-Instruct-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)