Model Card for Model ID
This model identifies foreign code and determines the recognized programming language. It is currently not further trained and has been completely adopted by huggingface/CodeBERTa-language-id. [source: https://huggingface.co/huggingface/CodeBERTa-language-id ]
Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by: Husain, Hamel and Wu, Ho-Hsiang and Gazit, Tiferet and Allamanis, Miltiadis and Brockschmidt, Marc
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- Language(s) (NLP): [More Information Needed]
- License: apache-2.0
- Finetuned from model [optional]: huggingface/CodeBERTa-language-id
- base_model: huggingface/CodeBERTa-small-v1
Model Sources [optional]
- Repository: https://huggingface.co/huggingface/CodeBERTa-language-id/edit/main/README.md
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Uses
from transformers import pipeline, TextClassificationPipeline, AutoTokenizer, AutoModelForSequenceClassification
checkpoint = "malteklaes/based-CodeBERTa-language-id-llm-module"
myPipeline = TextClassificationPipeline(
model=AutoModelForSequenceClassification.from_pretrained(checkpoint),
tokenizer=AutoTokenizer.from_pretrained(checkpoint)
)
CODE_TO_IDENTIFY = "print('hello world')"
myPipeline(CODE_TO_IDENTIFY)
Direct Use
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
code_search_net
Training Procedure
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Training Hyperparameters
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Evaluation
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Results
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Summary
Model Examination [optional]
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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