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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07e807c31a7b6b27f4565062d7a3b6522ca3dafaaa8a5395a225f4da6604d5d4
- Size of remote file:
- 134 MB
- SHA256:
- 175deb04b5d18c069ef4a7ba8c564bd106cb7afb3444a070bf2f80eb1f8b37c2
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