Instructions to use ThoughtFocusAI/CodeGeneration-CodeT5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThoughtFocusAI/CodeGeneration-CodeT5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ThoughtFocusAI/CodeGeneration-CodeT5-base") model = AutoModelForSeq2SeqLM.from_pretrained("ThoughtFocusAI/CodeGeneration-CodeT5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ThoughtFocusAI/CodeGeneration-CodeT5-base: direct link, hf CLI and curl.
- Browser
- Download file 1.48 kB
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https://huggingface.co/ThoughtFocusAI/CodeGeneration-CodeT5-base/resolve/main/README.md
- Command line
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hf download hf://ThoughtFocusAI/CodeGeneration-CodeT5-base/README.md
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curl -L -o README.md https://huggingface.co/ThoughtFocusAI/CodeGeneration-CodeT5-base/resolve/main/README.md
1.48 kB
metadata
tags:
- generated_from_keras_callback
model-index:
- name: CodeGeneration-CodeT5-base
results: []
datasets:
- ThoughtFocusAI/Python-CodeGeneration
CodeGeneration-CodeT5-base
This model was trained from the pretrained CodeT5-base model on ThoughtFocusAI/Python-CodeGeneration dataset. It achieves the following results on the evaluation set:
- ngram match: 0.014948515566713798
- weighted ngram match: 0.017803898905793227
- syntax_match: 0.21961325966850828
- dataflow_match: 0.36255924170616116
- bleu = 1.87
- codebleu = 15.3731
- exact match = 0.0
Model description
This model was trained from the pretrained CodeT5-base model Salesforce and has been fine tuned for Python Code Genertion.
Intended uses & limitations
Python Code Generation. Limited to simple queries.
Training and evaluation data
ThoughtFocusAI/Python-CodeGeneration
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.29.2
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3