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
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: CodeGeneration-CodeT5-base | |
| results: [] | |
| datasets: | |
| - ThoughtFocusAI/Python-CodeGeneration | |
| <!-- This model card has been generated automatically according to the information Keras had access to. You should | |
| probably proofread and complete it, then remove this comment. --> | |
| # CodeGeneration-CodeT5-base | |
| This model was trained from the pretrained CodeT5-base model on [ThoughtFocusAI/Python-CodeGeneration](https://huggingface.co/datasets/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](https://huggingface.co/datasets/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 |