Fill-Mask
Transformers
PyTorch
English
caduceus
DNA
genomics
fish
Caduceus
masked-language-model
nucleotide-modeling
foundation-model
reverse-complement
custom-code
FishCaduceus
custom_code
Instructions to use FishCaduceus/FishCaduceus-28L-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FishCaduceus/FishCaduceus-28L-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FishCaduceus/FishCaduceus-28L-512", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("FishCaduceus/FishCaduceus-28L-512", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "FishCaduceus-28L-512", | |
| "architectures": [ | |
| "CaduceusForMaskedLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_caduceus.CaduceusConfig", | |
| "AutoModel": "modeling_caduceus.Caduceus", | |
| "AutoModelForMaskedLM": "modeling_caduceus.CaduceusForMaskedLM", | |
| "AutoModelForSequenceClassification": "modeling_caduceus.CaduceusForSequenceClassification" | |
| }, | |
| "bidirectional": true, | |
| "bidirectional_strategy": "add", | |
| "bidirectional_weight_tie": true, | |
| "complement_map": { | |
| "0": 0, | |
| "1": 1, | |
| "2": 2, | |
| "3": 6, | |
| "4": 5, | |
| "5": 4, | |
| "6": 3, | |
| "7": 7 | |
| }, | |
| "d_model": 768, | |
| "fused_add_norm": true, | |
| "initializer_cfg": { | |
| "initializer_range": 0.02, | |
| "n_residuals_per_layer": 1, | |
| "rescale_prenorm_residual": true | |
| }, | |
| "model_type": "caduceus", | |
| "n_layer": 28, | |
| "norm_epsilon": 1e-05, | |
| "pad_token_id": -100, | |
| "pad_vocab_size_multiple": 8, | |
| "rcps": true, | |
| "residual_in_fp32": true, | |
| "rms_norm": true, | |
| "ssm_cfg": { | |
| "bias": false, | |
| "conv_bias": true, | |
| "d_conv": 4, | |
| "d_state": 16, | |
| "dt_init": "random", | |
| "dt_init_floor": 0.0001, | |
| "dt_max": 0.1, | |
| "dt_min": 0.001, | |
| "dt_rank": "auto", | |
| "dt_scale": 1.0, | |
| "expand": 2, | |
| "use_fast_path": true | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.46.3", | |
| "vocab_size": 8 | |
| } | |