Instructions to use ielabgroup/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/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/In_Batch_Random_Amazon_esci")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ielabgroup/In_Batch_Random_Amazon_esci") model = AutoModel.from_pretrained("ielabgroup/In_Batch_Random_Amazon_esci", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ielabgroup/In_Batch_Random_Amazon_esci: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/ielabgroup/In_Batch_Random_Amazon_esci/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ielabgroup/In_Batch_Random_Amazon_esci/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ielabgroup/In_Batch_Random_Amazon_esci/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 29034e307b52499b7fa2989d1769236096d82d8513b06b714ec09c66847e0e7a
- Size of remote file:
- 265 MB
- SHA256:
- a7eba8a8629b6d46fd33c876177fe998da4fe9a186e199310e40d930cba73821
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