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
v2: add Business Analyst class, longer context (384/2000), precision 0.880→0.922
Browse files- model.safetensors +1 -1
- tokenizer.json +2 -2
model.safetensors
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tokenizer.json
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length":
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"strategy": "LongestFirst",
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"stride": 0
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"padding": {
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"strategy": {
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"Fixed":
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"direction": "Right",
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"pad_to_multiple_of": null,
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length": 384,
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"strategy": "LongestFirst",
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"stride": 0
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"padding": {
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"strategy": {
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"Fixed": 384
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"direction": "Right",
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"pad_to_multiple_of": null,
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