Instructions to use asaderu-ai/ssclass_best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asaderu-ai/ssclass_best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="asaderu-ai/ssclass_best")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("asaderu-ai/ssclass_best") model = AutoModelForSequenceClassification.from_pretrained("asaderu-ai/ssclass_best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from asaderu-ai/ssclass_best: direct link, hf CLI and curl.
- Browser
- Download file 733 kB
-
https://huggingface.co/asaderu-ai/ssclass_best/resolve/main/tokenizer.json
- Command line
-
hf download hf://asaderu-ai/ssclass_best/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/asaderu-ai/ssclass_best/resolve/main/tokenizer.json
733 kB
- Xet hash:
- f9ea616c5ca620118744373fbcf83e9c9fd1217d8f8dbef969637ed09f3353df
- Size of remote file:
- 733 kB
- SHA256:
- 344a60406e93928110576ad4aa7d4bc683e4cef21eee37677a98a0b872d45b0f
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