Instructions to use sms1097/retrieval_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sms1097/retrieval_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sms1097/retrieval_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sms1097/retrieval_model") model = AutoModelForSequenceClassification.from_pretrained("sms1097/retrieval_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5afdd73cd0cf3635181b7194d35d825af52beb3d9b107136f02cfd9654d20c4
- Size of remote file:
- 536 MB
- SHA256:
- 71bd8ce66b80de53f7b3c23806fbc52a0b452747cda90b2f558d94bacca318c5
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