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 +2 -1
RepoPipeline.py
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import ast
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import tarfile
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from ast import AsyncFunctionDef, ClassDef, FunctionDef, Module
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import torch
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import requests
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from transformers import Pipeline
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from tqdm.auto import tqdm
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import ast
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import tarfile
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import torch
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import requests
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import numpy as np
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from ast import AsyncFunctionDef, ClassDef, FunctionDef, Module
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from transformers import Pipeline
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from tqdm.auto import tqdm
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