Instructions to use unikei/bert-base-smiles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unikei/bert-base-smiles with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="unikei/bert-base-smiles")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("unikei/bert-base-smiles") model = AutoModelForPreTraining.from_pretrained("unikei/bert-base-smiles", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ImportError: cannot import name 'BertTokenizerFast' from 'transformers'
#1
by xuwei1 - opened
Name: transformers
Version: 4.36.2
Summary: State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Home-page: https://github.com/huggingface/transformers
Author: The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/transformers/graphs/contributors)
Author-email: transformers@huggingface.co
License: Apache 2.0 License
Location: D:\software\anaconda3\Lib\site-packages
Requires: filelock, huggingface-hub, numpy, packaging, pyyaml, regex, requests, safetensors, tokenizers, tqdm
Required-by:
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