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:
- 6e10d2f6b2dca6b8909571fafa5db375ff54c046f39b91d01cee5e3826363b69
- Size of remote file:
- 1.43 GB
- SHA256:
- f0fc5db168f5ea872b281aee6afc3eee43a8da7c66d0576e7b1fff906a16b8fb
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