Instructions to use Tanor/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tanor/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tanor/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tanor/model") model = AutoModelForSequenceClassification.from_pretrained("Tanor/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Tanor/model: direct link, hf CLI and curl.
- Browser
- Download file 574 MB
-
https://huggingface.co/Tanor/model/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Tanor/model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Tanor/model/resolve/refs%2Fpr%2F1/pytorch_model.bin
574 MB
- Xet hash:
- 5c32e31e90df55f5a1c4366efe3e31e91aa6800f736f1a95db86283c73a9fcb7
- Size of remote file:
- 574 MB
- SHA256:
- 2de422d2b599a93c513b5dea7bafad35df0d81e9259687fafa602991cd23cef2
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