Fill-Mask
Transformers
ONNX
Safetensors
Bashkir
bashkir-roberta-preln
bashkir
masked-language-modeling
roberta
sentencepiece
custom-code
onnxruntime
custom_code
Instructions to use failed09/bashkir-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use failed09/bashkir-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="failed09/bashkir-roberta", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("failed09/bashkir-roberta", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Remove misplaced metadata copy
Browse files- config.json//config.json +0 -41
config.json//config.json
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{
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"transformers_version": "5.15.1",
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"architectures": [
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"BashkirRobertaForMaskedLM"
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],
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"output_hidden_states": false,
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"return_dict": true,
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"dtype": "float32",
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"chunk_size_feed_forward": 0,
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"is_encoder_decoder": false,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"problem_type": null,
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"_name_or_path": "",
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"pad_token_id": 0,
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"bos_token_id": 2,
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"eos_token_id": 3,
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"cls_token_id": 4,
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"sep_token_id": 5,
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"mask_token_id": 6,
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"tie_word_embeddings": true,
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"vocab_size": 16384,
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"hidden_size": 640,
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"num_hidden_layers": 8,
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"num_attention_heads": 10,
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"intermediate_size": 2560,
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"max_position_embeddings": 256,
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"hidden_dropout_prob": 0.1,
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"model_type": "bashkir-roberta-preln",
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"output_attentions": false,
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"auto_map": {
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"AutoConfig": "configuration_bashkir_roberta.BashkirRobertaConfig",
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"AutoModelForMaskedLM": "modeling_bashkir_roberta.BashkirRobertaForMaskedLM"
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}
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}
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