Instructions to use Taykhoom/RNA-MSM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/RNA-MSM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/RNA-MSM", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/RNA-MSM", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 675 Bytes
00e6e55 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | {
"auto_map": {
"AutoConfig": "configuration_rnamsm.RNAMSMConfig",
"AutoModel": "modeling_rnamsm.RNAMSMModel",
"AutoModelForMaskedLM": "modeling_rnamsm.RNAMSMForMaskedLM"
},
"activation_dropout": 0.1,
"architectures": [
"RNAMSMForMaskedLM"
],
"attention_dropout": 0.1,
"cls_idx": 0,
"dropout": 0.1,
"embed_dim": 768,
"embed_positions_msa": true,
"eos_idx": 2,
"ffn_embed_dim": 3072,
"mask_idx": 11,
"max_alignments": 1024,
"max_positions": 1024,
"max_tokens_per_msa": 16384,
"model_type": "rnamsm",
"num_attention_heads": 12,
"num_layers": 10,
"padding_idx": 1,
"transformers_version": "4.57.6",
"vocab_size": 12
}
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