Instructions to use ielabgroup/Pairwise_In_Batch_Random_Amazon_esci with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ielabgroup/Pairwise_In_Batch_Random_Amazon_esci with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ielabgroup/Pairwise_In_Batch_Random_Amazon_esci")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ielabgroup/Pairwise_In_Batch_Random_Amazon_esci") model = AutoModel.from_pretrained("ielabgroup/Pairwise_In_Batch_Random_Amazon_esci", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ielabgroup/Pairwise_In_Batch_Random_Amazon_esci: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/ielabgroup/Pairwise_In_Batch_Random_Amazon_esci/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ielabgroup/Pairwise_In_Batch_Random_Amazon_esci/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ielabgroup/Pairwise_In_Batch_Random_Amazon_esci/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 202186cd62f256157717b5dd06c6fd722f728cb8eca566dff6219be40fbaec6f
- Size of remote file:
- 265 MB
- SHA256:
- 1d0fbc363befe85c058df6618011f8a35c4f0e6c68aca5173c3bf3a8d739bd7d
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