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:
- b3754fb8400dc25e0dfa3291d5f7b840e806a8ec0ae9415c6d48fd34eb47e681
- Size of remote file:
- 536 MB
- SHA256:
- 89f9d61221d9e2b58ff7b8591abcd64e2ec147b05e6408dbfcce601025cbf555
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