Instructions to use SushantGautam/CodeGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SushantGautam/CodeGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SushantGautam/CodeGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SushantGautam/CodeGeneration") model = AutoModelForMaskedLM.from_pretrained("SushantGautam/CodeGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SushantGautam/CodeGeneration: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/SushantGautam/CodeGeneration/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SushantGautam/CodeGeneration/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SushantGautam/CodeGeneration/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 1f11754493da74fa68bb3872159c6d3aeae538c94a0214b211cd16fcd19921df
- Size of remote file:
- 499 MB
- SHA256:
- 1526349acf79f91a32f75e9b98e7572bf4d7473b6971512cf7b569969bf9973e
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