Text Classification
Transformers
TensorBoard
Safetensors
English
Russian
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use stepanom/XLMRoberta-base-amazon-massive-Intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stepanom/XLMRoberta-base-amazon-massive-Intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stepanom/XLMRoberta-base-amazon-massive-Intent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("stepanom/XLMRoberta-base-amazon-massive-Intent") model = AutoModelForSequenceClassification.from_pretrained("stepanom/XLMRoberta-base-amazon-massive-Intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from stepanom/XLMRoberta-base-amazon-massive-Intent: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/stepanom/XLMRoberta-base-amazon-massive-Intent/resolve/main/tokenizer.json
- Command line
-
hf download hf://stepanom/XLMRoberta-base-amazon-massive-Intent/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/stepanom/XLMRoberta-base-amazon-massive-Intent/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 900d575674d5bfcd5c2b9059c9221a42f92c957ed7230f7e096d3e9580c3e4c2
- Size of remote file:
- 17.1 MB
- SHA256:
- 883b037111086fd4dfebbbc9b7cee11e1517b5e0c0514879478661440f137085
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.