Instructions to use futuredatascience/welcome_message_prod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use futuredatascience/welcome_message_prod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="futuredatascience/welcome_message_prod")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("futuredatascience/welcome_message_prod", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from futuredatascience/welcome_message_prod: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/futuredatascience/welcome_message_prod/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://futuredatascience/welcome_message_prod@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/futuredatascience/welcome_message_prod/resolve/refs%2Fpr%2F1/tokenizer.json
712 kB
- Xet hash:
- b559dc2f96b3d7329468a7642d97efa6100d183ebefba0c9ae599d7d2665d290
- Size of remote file:
- 712 kB
- SHA256:
- 0d3aef594edd5f9b53e7f814277a9171dc70ff93eb66bda6e01f7aa53997d963
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