Text Classification
Transformers
Safetensors
English
xlm-roberta
text-generation-inference
unsloth
trl
text-embeddings-inference
Instructions to use cataluna84/LIDL1Bv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cataluna84/LIDL1Bv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cataluna84/LIDL1Bv3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cataluna84/LIDL1Bv3") model = AutoModelForSequenceClassification.from_pretrained("cataluna84/LIDL1Bv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded model
- Developed by: cataluna84
- License: apache-2.0
- Finetuned from model : intfloat/multilingual-e5-large
This xlm-roberta model was trained 2x faster with Unsloth
- Downloads last month
- 8
Model tree for cataluna84/LIDL1Bv3
Base model
intfloat/multilingual-e5-large