Instructions to use ibm-research/materials.selfies-ted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/materials.selfies-ted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ibm-research/materials.selfies-ted")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ibm-research/materials.selfies-ted") model = AutoModelForSeq2SeqLM.from_pretrained("ibm-research/materials.selfies-ted") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1772d7fc792d5d6ebb3b6815c359897fec05534008e88f7a50fe8633c103770a
- Size of remote file:
- 3.9 kB
- SHA256:
- 1bec6279d9e166b08d5c6105ca862d1845f1f07a258ca75b2ae91abad1ecfa42
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