Instructions to use santoshvutukuri/test_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use santoshvutukuri/test_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="santoshvutukuri/test_train")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("santoshvutukuri/test_train") model = AutoModelForSequenceClassification.from_pretrained("santoshvutukuri/test_train", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from santoshvutukuri/test_train: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/santoshvutukuri/test_train/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://santoshvutukuri/test_train/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/santoshvutukuri/test_train/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- 2856cc1bc1e1860b5fe41063eeafc3afa74b3fd0c2fe86ed6e265f7bb7b2e1eb
- Size of remote file:
- 433 MB
- SHA256:
- 2e1c5536fc062550c0b223f4950bfe5755287992f68da5bc673bc2747319e477
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