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:
- a23abadb5ee230006c2b3fbbd76ae64f776d007663318e44ae365fe36d4652e9
- Size of remote file:
- 4.6 kB
- SHA256:
- 8c3bbe83a16e4d0795b3103b6f74c9cc86efb22cb921fb0cbc559c28763ac610
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