Instructions to use ibm-research/MoLFormer-XL-both-10pct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ibm-research/MoLFormer-XL-both-10pct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ibm-research/MoLFormer-XL-both-10pct", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("ibm-research/MoLFormer-XL-both-10pct", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fef74d182180d49889faacd4086a86f935dba6e6b2731aee0ae5acf8c6450ce
- Size of remote file:
- 187 MB
- SHA256:
- 93e3fced64b896fcfea4934505ac80275db7afb7320d0b32ee0c691d99ab8678
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