Instructions to use DANI001/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DANI001/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DANI001/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DANI001/model") model = AutoModelForMaskedLM.from_pretrained("DANI001/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from DANI001/model: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/DANI001/model/resolve/main/tokenizer.json
- Command line
-
hf download hf://DANI001/model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DANI001/model/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- e1ec70b9eae6e35493692c2536700eed2095695150aabb2b8b184194cf5bff2f
- Size of remote file:
- 17.1 MB
- SHA256:
- 3c088c06cf975b7097e469bd69630cdb0d675c6db1ce3af1042b6e19c6d01f22
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