Instructions to use nz/RITA_s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nz/RITA_s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nz/RITA_s", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nz/RITA_s", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "nz/RITA_s", | |
| "architectures": [ | |
| "RITAModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "rita_configuration.RITAConfig", | |
| "AutoModel": "rita_modeling.RITAModel" | |
| }, | |
| "d_feedforward": 3072, | |
| "d_model": 768, | |
| "dropout": 0.0, | |
| "eos_token_id": 2, | |
| "max_seq_len": 1024, | |
| "model_type": "rita", | |
| "num_heads": 12, | |
| "num_layers": 12, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.18.0", | |
| "vocab_size": 26 | |
| } | |