Instructions to use bumblebee-testing/tiny-random-Phi3Model-rope_scaling-longrope-original_max_position_embeddings-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bumblebee-testing/tiny-random-Phi3Model-rope_scaling-longrope-original_max_position_embeddings-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bumblebee-testing/tiny-random-Phi3Model-rope_scaling-longrope-original_max_position_embeddings-256")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bumblebee-testing/tiny-random-Phi3Model-rope_scaling-longrope-original_max_position_embeddings-256") model = AutoModel.from_pretrained("bumblebee-testing/tiny-random-Phi3Model-rope_scaling-longrope-original_max_position_embeddings-256") - Notebooks
- Google Colab
- Kaggle