Feature Extraction
Transformers
Safetensors
llama
binary-code-similarity
assembly
code
representation-learning
Instructions to use mhosseina96/Llama-3.2-1B-LENA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mhosseina96/Llama-3.2-1B-LENA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mhosseina96/Llama-3.2-1B-LENA")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mhosseina96/Llama-3.2-1B-LENA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: other
license_name: llama3.2
license_link: https://www.llama.com/llama3_2/license/
base_model:
- unsloth/Llama-3.2-1B
base_model_relation: finetune
library_name: transformers
pipeline_tag: feature-extraction
tags:
- llama
- transformers
- binary-code-similarity
- assembly
- code
- representation-learning