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:
- b677e01cccc149aee2f70b77fd160c42614f9ee75c50682df1a874766cf7a78f
- Size of remote file:
- 17.8 MB
- SHA256:
- 194a00dd868d2861c1ba80e94cdf387b07d5580369addce87e36e9f199c32b77
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