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 +7 -6
RepoPipeline.py
CHANGED
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@@ -42,15 +42,16 @@ def extract_requirements(lines):
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"""
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requirements_set = set()
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for line in lines:
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try:
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if
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requirements_set.add(splitLine[0])
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except:
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pass
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return requirements_set
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"""
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requirements_set = set()
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for line in lines:
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line = line.replace("\n", "").strip()
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try:
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if " == " in line:
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splitLine = line.split(" == ")
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elif "==" in line:
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splitLine = line.split("==")
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requirements_set.add(splitLine[0])
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except:
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pass
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+
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return requirements_set
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