Text Classification
Transformers
Safetensors
roberta
quantum-computing
quantum-software-engineering
code-classification
codebert
c2q
Instructions to use boshuai1/c2q-parser-codebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boshuai1/c2q-parser-codebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="boshuai1/c2q-parser-codebert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("boshuai1/c2q-parser-codebert") model = AutoModelForSequenceClassification.from_pretrained("boshuai1/c2q-parser-codebert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f6f0546e0e1c1e747540d2b972db32d7e4ba118857db090a2d2e08f3a797a8e
- Size of remote file:
- 499 MB
- SHA256:
- 6365393edf34d74ae569b76ab65839dc6293b3ae4415c75533a289dceb1544c1
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