Instructions to use rose-e-wang/tools_a6000_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rose-e-wang/tools_a6000_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rose-e-wang/tools_a6000_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rose-e-wang/tools_a6000_2") model = AutoModelForSequenceClassification.from_pretrained("rose-e-wang/tools_a6000_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8787fb8cdd120962026fec1f67462ede4b85e9e675b28580cd263b8be0c9c92
- Size of remote file:
- 4.09 kB
- SHA256:
- 958719e23f1bccea59e686d5790310408a3dfed12efd8841ccab12995adff5dd
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