Instructions to use Pankayaraj/gemma-2b-LLM2REC_simcse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pankayaraj/gemma-2b-LLM2REC_simcse with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Pankayaraj/gemma-2b-LLM2REC_simcse") model = AutoModel.from_pretrained("Pankayaraj/gemma-2b-LLM2REC_simcse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59fe0c8292bceb5a639c8a63760c3c21e1df4337ff097bf006b4b3f0393e798e
- Size of remote file:
- 17.5 MB
- SHA256:
- 9ed96f4e4267b0f1472ae514c04292c2a1b7dd941150d6639dee54d9995df7e9
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