Instructions to use amandaraeb/qs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amandaraeb/qs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amandaraeb/qs")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amandaraeb/qs") model = AutoModelForSequenceClassification.from_pretrained("amandaraeb/qs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a0e6b67924ab74dd3605e912004c2b898a4be5c3c422a764a1d966484944a4f5
- Size of remote file:
- 3.31 kB
- SHA256:
- 938794d4ca1e280962291302bd7c8bdca5c1610f375ff5fb3293851244ce24af
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