Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use philschmid/distilbert-base-multilingual-cased-sentiment-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/distilbert-base-multilingual-cased-sentiment-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/distilbert-base-multilingual-cased-sentiment-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/distilbert-base-multilingual-cased-sentiment-2") model = AutoModelForSequenceClassification.from_pretrained("philschmid/distilbert-base-multilingual-cased-sentiment-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from philschmid/distilbert-base-multilingual-cased-sentiment-2: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/philschmid/distilbert-base-multilingual-cased-sentiment-2/resolve/main/training_args.bin
- Command line
-
hf download hf://philschmid/distilbert-base-multilingual-cased-sentiment-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/philschmid/distilbert-base-multilingual-cased-sentiment-2/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 8f9181fa1c89da65e56ce924986ff5013cfdb4b5208838f10391bfd42ed1e88e
- Size of remote file:
- 2.86 kB
- SHA256:
- 1caef4b0094b68b9e7333685c003d7bb9d0f4efc3840c9c746e5be60d3cded88
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