Instructions to use ninja/Sentiment_Analysis2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ninja/Sentiment_Analysis2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ninja/Sentiment_Analysis2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ninja/Sentiment_Analysis2") model = AutoModelForSequenceClassification.from_pretrained("ninja/Sentiment_Analysis2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ninja/Sentiment_Analysis2: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/ninja/Sentiment_Analysis2/resolve/ae53f7809d16dc32fdbc4b2e620fedbf9d7cc7ef/training_args.bin
- Command line
-
hf download hf://ninja/Sentiment_Analysis2@ae53f7809d16dc32fdbc4b2e620fedbf9d7cc7ef/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ninja/Sentiment_Analysis2/resolve/ae53f7809d16dc32fdbc4b2e620fedbf9d7cc7ef/training_args.bin
5.11 kB
- Xet hash:
- 72b08c019c708d8442b811462d0010d506019370855d0b35ce4009c6860d0708
- Size of remote file:
- 5.11 kB
- SHA256:
- 523a18009467093c7d5313fb29854fffa0522daaf8ab71744c11837d9bb2b8ea
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