Instructions to use HydraLM/bge-large-classifier-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HydraLM/bge-large-classifier-32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HydraLM/bge-large-classifier-32")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HydraLM/bge-large-classifier-32") model = AutoModelForSequenceClassification.from_pretrained("HydraLM/bge-large-classifier-32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Alpay Ariyak commited on
Commit Β·
af1e80e
1
Parent(s): 7751fd3
Training in progress, step 23000
Browse files- {checkpoint-7000 β checkpoint-23000}/config.json +0 -0
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- {checkpoint-7000 β checkpoint-23000}/rng_state.pth +1 -1
- {checkpoint-7000 β checkpoint-23000}/scheduler.pt +1 -1
- {checkpoint-7000 β checkpoint-23000}/trainer_state.json +0 -0
- {checkpoint-7000 β checkpoint-23000}/training_args.bin +0 -0
- pytorch_model.bin +1 -1
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