Instructions to use kevinjesse/codebert-MT4TS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kevinjesse/codebert-MT4TS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kevinjesse/codebert-MT4TS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kevinjesse/codebert-MT4TS") model = AutoModelForTokenClassification.from_pretrained("kevinjesse/codebert-MT4TS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kevinjesse/codebert-MT4TS: direct link, hf CLI and curl.
- Browser
- Download file 650 MB
-
https://huggingface.co/kevinjesse/codebert-MT4TS/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kevinjesse/codebert-MT4TS/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kevinjesse/codebert-MT4TS/resolve/main/pytorch_model.bin
650 MB
- Xet hash:
- 8559de3772ca4fda63d02fc3f48265ab3e25048d634d84870390d9c101c6b46e
- Size of remote file:
- 650 MB
- SHA256:
- 87cf208e10bb929312fd282b2fae947e869e5665855e99b75b184784acaf80a4
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