Text Classification
Transformers
PyTorch
ONNX
Safetensors
distilbert
sentiment-analysis
zero-shot-distillation
distillation
zero-shot-classification
debarta-v3
text-embeddings-inference
Instructions to use lxyuan/distilbert-base-multilingual-cased-sentiments-student with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lxyuan/distilbert-base-multilingual-cased-sentiments-student with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lxyuan/distilbert-base-multilingual-cased-sentiments-student")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lxyuan/distilbert-base-multilingual-cased-sentiments-student") model = AutoModelForSequenceClassification.from_pretrained("lxyuan/distilbert-base-multilingual-cased-sentiments-student", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lxyuan/distilbert-base-multilingual-cased-sentiments-student: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/lxyuan/distilbert-base-multilingual-cased-sentiments-student/resolve/main/training_args.bin
- Command line
-
hf download hf://lxyuan/distilbert-base-multilingual-cased-sentiments-student/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lxyuan/distilbert-base-multilingual-cased-sentiments-student/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 3a420b4c08a3a8abc21e7f97379a584fa4309caacd0eacfe07d283e3ffeac66e
- Size of remote file:
- 3.64 kB
- SHA256:
- d0a703ae5fa8faeb9b4595394703a0f1fdd7a4f8d8436acf449c8032d939e519
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