Instructions to use busycaesar/tinystarcoder-rlhf-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use busycaesar/tinystarcoder-rlhf-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="busycaesar/tinystarcoder-rlhf-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("busycaesar/tinystarcoder-rlhf-model") model = AutoModelForSequenceClassification.from_pretrained("busycaesar/tinystarcoder-rlhf-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f32ba4d1ebccb5df8d4802d9cc90709d6134bf3287bf6f25ed91580c72e01d4
- Size of remote file:
- 5.39 kB
- SHA256:
- 4a464612f41fd73b15b7f631d8ca3fba8817d72fc198dd74c2dff80f80606279
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.