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
| 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 | |