Instructions to use frameee17/exp_number1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frameee17/exp_number1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="frameee17/exp_number1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("frameee17/exp_number1") model = AutoModelForSequenceClassification.from_pretrained("frameee17/exp_number1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from frameee17/exp_number1: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/frameee17/exp_number1/resolve/main/tokenizer.json
- Command line
-
hf download hf://frameee17/exp_number1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/frameee17/exp_number1/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 65aeedce657e0b03c11cd2c0fc8a3d2c8d641c0b2bad0bae89ccd9b3372bc8b6
- Size of remote file:
- 17.1 MB
- SHA256:
- abf1c7593e6054866d04138a9d5c22e9457b3942a92d5fe0e178c0e21868e07d
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