Instructions to use saracandu/stldec_formulae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saracandu/stldec_formulae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="saracandu/stldec_formulae", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("saracandu/stldec_formulae", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "activation_dropout": 0.0, | |
| "activation_function": "gelu", | |
| "add_cross_attention": true, | |
| "architectures": [ | |
| "STLDecoderModel" | |
| ], | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_stldec.STLDecoderConfig", | |
| "AutoModel": "modeling_stldec.STLDecoderModel", | |
| "AutoModelForCausalLM": "modeling_stldec.STLDecoderModel", | |
| "AutoTokenizer": [ | |
| "tokenizer_stldec.STLTokenizer", | |
| null | |
| ] | |
| }, | |
| "bos_token_id": 2, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "embedding_dim_target": 1024, | |
| "encoder_hidden_size": 1024, | |
| "eos_token_id": 3, | |
| "hidden_size": 1024, | |
| "init_std": 0.02, | |
| "intermediate_size": 4096, | |
| "is_decoder": true, | |
| "max_position_embeddings": 512, | |
| "model_type": "stl_decoder", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "scale_embedding": false, | |
| "transformers_version": "4.57.3", | |
| "use_cache": true, | |
| "vocab_size": 35 | |
| } | |