Instructions to use routellm/bert_gpt4_augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use routellm/bert_gpt4_augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="routellm/bert_gpt4_augmented")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("routellm/bert_gpt4_augmented") model = AutoModelForSequenceClassification.from_pretrained("routellm/bert_gpt4_augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from routellm/bert_gpt4_augmented: direct link, hf CLI and curl.
- Browser
- Download file 2.22 GB
-
https://huggingface.co/routellm/bert_gpt4_augmented/resolve/main/optimizer.pt
- Command line
-
hf download hf://routellm/bert_gpt4_augmented/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/routellm/bert_gpt4_augmented/resolve/main/optimizer.pt
2.22 GB
- Xet hash:
- 2bd966e8a1a2a0f063fd8e26f79d26dcdfd75f218a8d2afcdb361db468424080
- Size of remote file:
- 2.22 GB
- SHA256:
- f10419e94a765ca488575093ca0e4f7c4deb4dd1e16e0b9abb34f9ffe4ce896e
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