Instructions to use tlam25/phase1_bert_upsampling_replace_aroma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tlam25/phase1_bert_upsampling_replace_aroma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tlam25/phase1_bert_upsampling_replace_aroma")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tlam25/phase1_bert_upsampling_replace_aroma") model = AutoModelForSequenceClassification.from_pretrained("tlam25/phase1_bert_upsampling_replace_aroma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b4939eac8fbbdd4ce219c90a2c0ea160c18d9bf116188a596e0371b325cfd09
- Size of remote file:
- 438 MB
- SHA256:
- f4b59da25a8c35fdd6ef8afaf27a15e1b2fa3bd7f2ecf145d4a897b5eadd94e5
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