Text Classification
Transformers
Safetensors
English
bert
MOF
metal-organic-framework
material-science
synthesis-classification
Instructions to use noellzhao/MOF_SynthesisDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noellzhao/MOF_SynthesisDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="noellzhao/MOF_SynthesisDetection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("noellzhao/MOF_SynthesisDetection") model = AutoModelForSequenceClassification.from_pretrained("noellzhao/MOF_SynthesisDetection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc22b8a8043795e442c98d34ed70800a5d70707247811e63ccae9d61f0a0e9f6
- Size of remote file:
- 438 MB
- SHA256:
- 369980954b22e11a85ea0c24bd9508c6e1f561766a26d5a163c0e99b67225f26
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