Instructions to use lmeninato/mt5-small-codesearchnet-python3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmeninato/mt5-small-codesearchnet-python3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lmeninato/mt5-small-codesearchnet-python3") model = AutoModelForSeq2SeqLM.from_pretrained("lmeninato/mt5-small-codesearchnet-python3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d09f974f0734431beee335746bb23f0ec9980ef267d93d92d09987adb51f072e
- Size of remote file:
- 1.2 GB
- SHA256:
- 9ad0418ec51bbf1778ab06a42d929a653c9eef756b0d8fb15ce39020be9d67a8
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