metadata
license: apache-2.0
datasets:
- CohereForAI/aya_dataset
- argilla/databricks-dolly-15k-curated-multilingual
- Gael540/dataSet_ens_sup_fr-v1
- ai2-adapt-dev/flan_v2_converted
- OpenAssistant/oasst1
language:
- fr
- en
- de
- it
- es
base_model: OpenLLM-France/Lucie-7B-Instruct-human-data
pipeline_tag: text-generation
tags:
- mlx
alexgusevski/Lucie-7B-Instruct-human-data-mlx
The Model alexgusevski/Lucie-7B-Instruct-human-data-mlx was converted to MLX format from OpenLLM-France/Lucie-7B-Instruct-human-data using mlx-lm version 0.21.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("alexgusevski/Lucie-7B-Instruct-human-data-mlx")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)