Instructions to use tejaskamtam/testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tejaskamtam/testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tejaskamtam/testing")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tejaskamtam/testing") model = AutoModelForMaskedLM.from_pretrained("tejaskamtam/testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9440a12911ed01c392954a6f030d7201b0bffa38b828e88b9bd9b992feb9877e
- Size of remote file:
- 4.79 kB
- SHA256:
- f965bf055c5f3861319e33b66017476def604ebeeea54121c60465299b390a86
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