Instructions to use SEBIS/code_trans_t5_base_api_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SEBIS/code_trans_t5_base_api_generation with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="SEBIS/code_trans_t5_base_api_generation")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SEBIS/code_trans_t5_base_api_generation") model = AutoModel.from_pretrained("SEBIS/code_trans_t5_base_api_generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SEBIS/code_trans_t5_base_api_generation: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/SEBIS/code_trans_t5_base_api_generation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SEBIS/code_trans_t5_base_api_generation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SEBIS/code_trans_t5_base_api_generation/resolve/main/pytorch_model.bin
892 MB
- Xet hash:
- 8885c90cf5835b19c39c30fe80942ea49fc07cfa495d805dd24d0b62150233ba
- Size of remote file:
- 892 MB
- SHA256:
- 8ed856023b27f28b62e06643cf90ddb3aeee21ee1045cfb02c486c25383e8dd5
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