Instructions to use facebook/xmod-base-60-125k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/xmod-base-60-125k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="facebook/xmod-base-60-125k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/xmod-base-60-125k") model = AutoModelForMaskedLM.from_pretrained("facebook/xmod-base-60-125k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8242b359768579d1a4a56c98280d95591771880fac98118c33aaa21d303da7fd
- Size of remote file:
- 2.82 GB
- SHA256:
- 2ff037d794e61b190a950d52a8378f56f6c345493e43dd653b2e0f0bf3e2d7fe
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