Instructions to use Fsoft-AIC/dopamin-python-usage with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fsoft-AIC/dopamin-python-usage with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fsoft-AIC/dopamin-python-usage")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fsoft-AIC/dopamin-python-usage") model = AutoModelForSequenceClassification.from_pretrained("Fsoft-AIC/dopamin-python-usage", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Fsoft-AIC/dopamin-python-usage: direct link, hf CLI and curl.
- Browser
- Download file 612 MB
-
https://huggingface.co/Fsoft-AIC/dopamin-python-usage/resolve/main/model.safetensors
- Command line
-
hf download hf://Fsoft-AIC/dopamin-python-usage/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Fsoft-AIC/dopamin-python-usage/resolve/main/model.safetensors
612 MB
- Xet hash:
- 6cd59556543150b21b408d1a71e706830437276fa77acb0eefd4141bc8b781f9
- Size of remote file:
- 612 MB
- SHA256:
- d0da165d15bcf5369c61724f11af7792194f48c9ec4759e3328b6c2612a1f6db
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