Instructions to use leukas/amlm_hd_fail with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leukas/amlm_hd_fail with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="leukas/amlm_hd_fail")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("leukas/amlm_hd_fail") model = AutoModelForMaskedLM.from_pretrained("leukas/amlm_hd_fail") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf73ed8d081c95b744f6012d026cc4fbac2f1349bd5d930637ab60ef4c0bf9c0
- Size of remote file:
- 927 kB
- SHA256:
- 11fb36c4badc2b9f0efb56af3e0fba0cf465036b966940e717456f55131b5ec1
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