Reinforcer
Collection
4 items • Updated
How to use reinforcer/xlm-roberta-se-sentiments-x with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="reinforcer/xlm-roberta-se-sentiments-x") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("reinforcer/xlm-roberta-se-sentiments-x")
model = AutoModelForSequenceClassification.from_pretrained("reinforcer/xlm-roberta-se-sentiments-x", device_map="auto")Base Model: xlm-roberta-base
Model Name: reinforcer/xlm-roberta-se-sentiments-x
Task: Text Classification (Sentiment Analysis)
Languages: Multilingual
Training Parameters:
| Metric | Score |
|---|---|
| Accuracy | 85.5% |
| Precision | 85.4% |
| Recall | 85.5% |
| F1 Score | 85.4% |
from transformers import pipeline
# For private repository access:
# analyzer = pipeline(..., token="your_hf_token_here")
analyzer = pipeline(
"text-classification",
model="reinforcer/xlm-roberta-se-sentiments-x"
)
result = analyzer("This product delivers excellent performance!")
Base model
FacebookAI/xlm-roberta-base