Feature Extraction
Transformers
PyTorch
roberta
code-understanding
unixcoder
text-embeddings-inference
Instructions to use Henry65/RepoSim4Py with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Henry65/RepoSim4Py with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Henry65/RepoSim4Py")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Henry65/RepoSim4Py") model = AutoModel.from_pretrained("Henry65/RepoSim4Py") - Notebooks
- Google Colab
- Kaggle
Update RepoPipeline.py
Browse files- RepoPipeline.py +1 -1
RepoPipeline.py
CHANGED
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@@ -128,7 +128,7 @@ class RepoPipeline(Pipeline):
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input_ = [input_]
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# Building token
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-
github_token = preprocess_parameters["
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headers = {"Accept": "application/vnd.github+json"}
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token = github_token or self.github_token
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if token:
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input_ = [input_]
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# Building token
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+
github_token = preprocess_parameters["github_token"]
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headers = {"Accept": "application/vnd.github+json"}
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token = github_token or self.github_token
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if token:
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