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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c424155a592f6801cd1c7e23538d566043dfcd123988fedd80e365584888180b
- Size of remote file:
- 3.31 kB
- SHA256:
- d071a74a7be06063e9051e3b4b76ca2e88f3ebea1cd21081ec84f7f9789dae42
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