Instructions to use allispaul/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allispaul/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="allispaul/test-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("allispaul/test-model") model = AutoModelForMaskedLM.from_pretrained("allispaul/test-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c61d51c63a0e2f87c1734506a851fa0342ccd98e29f3a47f87687fd294d5d1d
- Size of remote file:
- 433 MB
- SHA256:
- 283b7b2e8fc1d79cfe3106fc4cdc44633798d4f94204a12ea614ed808269efba
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.