Instructions to use xfcxcxcdfdfd/tesdfdfv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xfcxcxcdfdfd/tesdfdfv1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("xfcxcxcdfdfd/tesdfdfv1") model = AutoModel.from_pretrained("xfcxcxcdfdfd/tesdfdfv1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from xfcxcxcdfdfd/tesdfdfv1: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/xfcxcxcdfdfd/tesdfdfv1/resolve/main/tokenizer.json
- Command line
-
hf download hf://xfcxcxcdfdfd/tesdfdfv1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/xfcxcxcdfdfd/tesdfdfv1/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 725bdd58ea6e9a8cdc2069b3a23c09a3e3310f0f6395e19c566c1c11de4385e2
- Size of remote file:
- 17.2 MB
- SHA256:
- 65ff5472d095ccd9332d9e723153d7bc7226cb6be9c1bffda738b5ba2e71bf26
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