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epfl-dlab/zip2zip-pp-Llama-3.2-3B-Instruct
zip2zip-pp-Llama-3.2-3B-Instruct is a text generation model from epfl-dlab. Use it when you need the model to write or continue text. It is set up for zip2zip. The card lists the license as llama3.2.
Zip2Zip++ checkpoint based on meta-llama/Llama-3.2-3B-Instruct (training step 8000). The repository keeps the original training checkpoint on main and the user-facing, self-contained inference export on hf.
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From the Hugging Face model README
Zip2Zip++ checkpoint based on meta-llama/Llama-3.2-3B-Instruct (training step
8000). The repository keeps the original training checkpoint on main and
the user-facing, self-contained inference export on hf.
Built with Llama.
pip install "zip2zip>=0.2.0"
from zip2zip import Zip2ZipModel, Zip2ZipTokenizer
repo_id = "epfl-dlab/zip2zip-pp-Llama-3.2-3B-Instruct"
tokenizer = Zip2ZipTokenizer.from_pretrained(
repo_id, revision="hf"
)
model = Zip2ZipModel.from_pretrained(
repo_id, revision="hf", device_map="auto", dtype="auto"
)
inputs = tokenizer("Hello", return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(output[0], skip_special_tokens=True))
Use main only with zip2zip-plus-plus
when resuming training or reproducing the export. It is not a Transformers/zip2zip inference revision.