Instructions to use Taykhoom/AIDO.RNA-650M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/AIDO.RNA-650M with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Taykhoom/AIDO.RNA-650M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_linear_bias": true, | |
| "attention_probs_dropout_prob": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_aidorna.AIDORNAConfig", | |
| "AutoModel": "modeling_aidorna.AIDORNAModel", | |
| "AutoModelForMaskedLM": "modeling_aidorna.AIDORNAForMaskedLM" | |
| }, | |
| "hidden_act": "swiglu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 1280, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3392, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 1024, | |
| "model_type": "aidorna", | |
| "normalization_type": "LayerNorm", | |
| "num_attention_heads": 20, | |
| "num_hidden_layers": 33, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "rope", | |
| "rotary_percent": 1.0, | |
| "seq_len_interpolation_factor": null, | |
| "transformers_version": "4.57.6", | |
| "vocab_size": 16 | |
| } |