metareflection/dafny-annotator-modular-vfp-4B
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("metareflection/dafny-annotator-modular-vfp-4B")
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)
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Model size
4B params
Tensor type
F32
·
Hardware compatibility
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Quantized
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("metareflection/dafny-annotator-modular-vfp-4B") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True)