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:
- 9d5da9eb3e266a07a55825100336b62f0661d6c2e88600bc67c309347fb772af
- Size of remote file:
- 4.6 kB
- SHA256:
- b4e34be44bddfc92defb6120677f695f41778c9b0ea9e81a8a2a0b6e34b89ad1
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