Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000") model = AutoModelForSequenceClassification.from_pretrained("ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000/resolve/main/training_args.bin
- Command line
-
hf download hf://ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ASCCCCCCCC/distilbert-base-multilingual-cased-amazon_zh_20000/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 4d43d8ad39595b0e52b9136ee23e739245fe68f02e06a982603297aa344d9181
- Size of remote file:
- 3.06 kB
- SHA256:
- f49af9742a5d8cb7d602a4b6bd3d057c0417091d255c617729e45f2b33e33362
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