Instructions to use research-dump/roberta-base_temp_classifier_bootstrapped_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/roberta-base_temp_classifier_bootstrapped_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/roberta-base_temp_classifier_bootstrapped_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/roberta-base_temp_classifier_bootstrapped_v2") model = AutoModelForSequenceClassification.from_pretrained("research-dump/roberta-base_temp_classifier_bootstrapped_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cff2a84b352e510591ebaefecf742c33074f96878bd8a4a40c5e5d66b89e71be
- Size of remote file:
- 499 MB
- SHA256:
- 0f37d388efbd12e9ccbbfc859c67b8917acba9a0dc026f78da2114357b78c26c
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