Instructions to use rose-e-wang/tools_a6000_0.00001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rose-e-wang/tools_a6000_0.00001 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rose-e-wang/tools_a6000_0.00001")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rose-e-wang/tools_a6000_0.00001") model = AutoModelForSequenceClassification.from_pretrained("rose-e-wang/tools_a6000_0.00001", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rose-e-wang/tools_a6000_0.00001: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/rose-e-wang/tools_a6000_0.00001/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rose-e-wang/tools_a6000_0.00001/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rose-e-wang/tools_a6000_0.00001/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- db3f02d0908af56ac2ca61f9d86317216f4946cc0acccfd5cb5fc28caac96eb1
- Size of remote file:
- 1.42 GB
- SHA256:
- e7fdae504e18ddd3e7908f5ab5464cb45dc14c5dee0385e17524bfa723e27d81
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