Instructions to use Taykhoom/RNAErnie2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/RNAErnie2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/RNAErnie2", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/RNAErnie2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 711 Bytes
9e231ea 1c9e5d4 9e231ea | 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 | {
"architectures": [
"RNAErnie2ForMaskedLM"
],
"model_type": "rnaernie2",
"auto_map": {
"AutoConfig": "configuration_rnaernie2.RNAErnie2Config",
"AutoModel": "modeling_rnaernie2.RNAErnie2Model",
"AutoModelForMaskedLM": "modeling_rnaernie2.RNAErnie2ForMaskedLM"
},
"vocab_size": 11,
"hidden_size": 768,
"num_hidden_layers": 12,
"num_attention_heads": 12,
"intermediate_size": 3072,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"attention_probs_dropout_prob": 0.1,
"max_position_embeddings": 2048,
"type_vocab_size": 2,
"layer_norm_eps": 1e-05,
"pad_token_id": 0,
"initializer_range": 0.02,
"transformers_version": "4.57.6",
"model_max_length": 2048
}
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