# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("sandspeare/llasm-encoder", trust_remote_code=True)
model = AutoModel.from_pretrained("sandspeare/llasm-encoder", trust_remote_code=True)Quick Links
llasm: Naming Functions in Binaries by Fusing Encoder-only and Decoder-only LLMs
About
llasm, is a novel framework that fuses encoder-only and decoder-only LLMs, which utilizes their capabilities to better comprehend assembly language and have better generalizability at function naming.
This is the encoder of llasm.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sandspeare/llasm-encoder", trust_remote_code=True)