Text Classification
Transformers
Safetensors
Russian
English
bert
tiny-bert
rubert-tiny2
binary-classification
jobs
developer-classification
data-analyst-classification
business-analyst-classification
dev-plus-da-plus-ba
r95
v2
Eval Results (legacy)
text-embeddings-inference
Instructions to use AndreiTolmachev/dev_da_roles_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndreiTolmachev/dev_da_roles_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AndreiTolmachev/dev_da_roles_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AndreiTolmachev/dev_da_roles_1") model = AutoModelForSequenceClassification.from_pretrained("AndreiTolmachev/dev_da_roles_1") - Notebooks
- Google Colab
- Kaggle
File size: 596 Bytes
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"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
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"truncation_strategy": "longest_first",
"unk_token": "[UNK]"
}
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