Instructions to use Jumpr/hf-automodel-compatible-test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jumpr/hf-automodel-compatible-test-model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Jumpr/hf-automodel-compatible-test-model", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "LightningTransformerModel" | |
| ], | |
| "cfg": { | |
| "batch_size": 1, | |
| "block_num": 6, | |
| "embed_dims": 512, | |
| "head_size": 64, | |
| "iterations": 250, | |
| "lr": 0.0002, | |
| "num_heads": 8, | |
| "seq_len": 164, | |
| "use_liger": true, | |
| "vocab_size": 49152 | |
| }, | |
| "dtype": "float32", | |
| "model_type": "lightning_transformer", | |
| "transformers_version": "5.12.0" | |
| } | |