metadata
library_name: transformers
datasets:
- pasukka/autoparts_filters
license: apache-2.0
language:
- ru
metrics:
- f1
- accuracy
base_model: ai-forever/ruRoberta-large
Model Card for Model ID
Model Details
Model Description
- Language(s) (NLP): Russian
- License: apache-2.0
- Finetuned from model: ai-forever/ruRoberta-large
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("pasukka/auto-filters-term-classifier-v.0.2")
tokenizer = AutoTokenizer.from_pretrained('ai-forever/ruRoberta-large')
term = 'фильтр топливный'
outputs = model.forward(**tokenizer(term, return_tensors='pt').to(device='cuda'))
id = outputs.logits.argmax(dim=1)[0].item()
print(model.config.id2label[id])
Result:
фильтр
Direct Use
[More Information Needed]
Downstream Use [optional]
[More Information Needed]
Out-of-Scope Use
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
Training Details
Training Data
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]