Translation
Transformers
Safetensors
t5
text2text-generation
codet5
nl2cmd
text-generation-inference
Instructions to use diethylene/codet5-small-nl2cmd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diethylene/codet5-small-nl2cmd with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="diethylene/codet5-small-nl2cmd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("diethylene/codet5-small-nl2cmd") model = AutoModelForSeq2SeqLM.from_pretrained("diethylene/codet5-small-nl2cmd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
release iteration 2
Browse files
README.md
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base_model_relation: finetune
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license: apache-2.0
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library_name: transformers
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pipeline_tag:
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tags:
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- codet5
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- nl2cmd
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---
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This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the combined datasets cited below.
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## Dataset Citations
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base_model_relation: finetune
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license: apache-2.0
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library_name: transformers
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pipeline_tag: translation
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tags:
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- codet5
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- nl2cmd
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- translation
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---
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This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the combined datasets cited below, plus synthetically generated data based on the referenced datasets.
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## Dataset Citations
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