metadata
language:
- en
license: apache-2.0
tags:
- mlx
- mlx
datasets:
- cerebras/SlimPajama-627B
- bigcode/starcoderdata
- HuggingFaceH4/ultrachat_200k
- HuggingFaceH4/ultrafeedback_binarized
widget:
- text: >
<|system|>
You are a chatbot who can help code!</s>
<|user|>
Write me a function to calculate the first 10 digits of the fibonacci
sequence in Python and print it out to the CLI.</s>
<|assistant|>
base_model: mlx-community/TinyLlama-1.1B-Chat-v1.0-mlx
jbeiroa/tinyllama-mlx-ft
The Model jbeiroa/tinyllama-mlx-ft was converted to MLX format from mlx-community/TinyLlama-1.1B-Chat-v1.0-mlx using mlx-lm version 0.20.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("jbeiroa/tinyllama-mlx-ft")
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)