Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use lmeninato/t5-small-codesearchnet-python3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmeninato/t5-small-codesearchnet-python3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lmeninato/t5-small-codesearchnet-python3") model = AutoModelForSeq2SeqLM.from_pretrained("lmeninato/t5-small-codesearchnet-python3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-195/optimizer.pt from lmeninato/t5-small-codesearchnet-python3: direct link, hf CLI and curl.
- Browser
- Download file 839 kB
-
https://huggingface.co/lmeninato/t5-small-codesearchnet-python3/resolve/refs%2Fpr%2F1/checkpoint-195/optimizer.pt
- Command line
-
hf download hf://lmeninato/t5-small-codesearchnet-python3@refs/pr/1/checkpoint-195/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/lmeninato/t5-small-codesearchnet-python3/resolve/refs%2Fpr%2F1/checkpoint-195/optimizer.pt
839 kB
- Xet hash:
- 8c04beda6958b4e291c56e331ddf5dba0be37ece7c22735d6eb34a9b45855fa2
- Size of remote file:
- 839 kB
- SHA256:
- 661fb4fa1dc4b73d6a0ef1e4f78ae5db56feff5dcdbf78055768f0f989905c06
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