Instructions to use ULFBERTO/OxideLLM_5M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ULFBERTO/OxideLLM_5M with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ULFBERTO/OxideLLM_5M") - Notebooks
- Google Colab
- Kaggle
| { | |
| "vocab_size": 221, | |
| "d_model": 256, | |
| "num_heads": 4, | |
| "dff": 512, | |
| "num_layers": 4, | |
| "max_len": 128, | |
| "dropout": 0.1 | |
| } |