Instructions to use aieng-lab/Llama-3.2-1B_comment-type-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aieng-lab/Llama-3.2-1B_comment-type-java with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aieng-lab/Llama-3.2-1B_comment-type-java")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aieng-lab/Llama-3.2-1B_comment-type-java") model = AutoModelForSequenceClassification.from_pretrained("aieng-lab/Llama-3.2-1B_comment-type-java", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e21e364084bae006edc6d3807a8413b35726c10a41f1de99e9e0ba2d295e6e0d
- Size of remote file:
- 2.47 GB
- SHA256:
- 46f0efa561a6e8bd7ac130fc26ebd674ebf327293dce59710836d2731bd02054
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.