Instructions to use peter-nagy/deep-grader-unixcoder-cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter-nagy/deep-grader-unixcoder-cpp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="peter-nagy/deep-grader-unixcoder-cpp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("peter-nagy/deep-grader-unixcoder-cpp") model = AutoModelForSequenceClassification.from_pretrained("peter-nagy/deep-grader-unixcoder-cpp") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("peter-nagy/deep-grader-unixcoder-cpp")
model = AutoModelForSequenceClassification.from_pretrained("peter-nagy/deep-grader-unixcoder-cpp")Quick Links
Deep Grader is a programming language model leveraging large pre-trained models (CodeBERT, UniXcoder) fine-tuned on the task of Automatic Program Grading with Python and C++ programming languages.
For more information, see: https://github.com/peter-nagy1/Deep-Grader
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="peter-nagy/deep-grader-unixcoder-cpp")