Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
nlu
Eval Results (legacy)
text-embeddings-inference
Instructions to use cartesinus/multilingual_minilm-amazon_massive-intent_eu7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cartesinus/multilingual_minilm-amazon_massive-intent_eu7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cartesinus/multilingual_minilm-amazon_massive-intent_eu7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cartesinus/multilingual_minilm-amazon_massive-intent_eu7") model = AutoModelForSequenceClassification.from_pretrained("cartesinus/multilingual_minilm-amazon_massive-intent_eu7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cartesinus/multilingual_minilm-amazon_massive-intent_eu7: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/cartesinus/multilingual_minilm-amazon_massive-intent_eu7/resolve/main/training_args.bin
- Command line
-
hf download hf://cartesinus/multilingual_minilm-amazon_massive-intent_eu7/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cartesinus/multilingual_minilm-amazon_massive-intent_eu7/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 27ad6387dc3a3b90a81a67add6980b33bc730ce9aab4bd31f68a26daf65f5ac1
- Size of remote file:
- 3.45 kB
- SHA256:
- e4309cbd0aaea35486b6c76827ffa0abad760781d4b9934a8c0a2b32e9090a55
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.