Instructions to use ibm-research/materials.selfies-ted2m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/materials.selfies-ted2m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ibm-research/materials.selfies-ted2m")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ibm-research/materials.selfies-ted2m") model = AutoModelForSeq2SeqLM.from_pretrained("ibm-research/materials.selfies-ted2m") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf874c7e75397fb845312c7b7ecbc4ef91793c3542849f7ccdf3fa4a5030c1fa
- Size of remote file:
- 8.92 MB
- SHA256:
- c56beb1afc07c44598564b3ff802d63bb2c3d364c068b0f27b126ff9f9df62bc
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