Instructions to use claudios/sptcode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use claudios/sptcode with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="claudios/sptcode")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("claudios/sptcode") model = AutoModel.from_pretrained("claudios/sptcode", device_map="auto") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("claudios/sptcode")
model = AutoModel.from_pretrained("claudios/sptcode", device_map="auto")Quick Links
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Check out the documentation for more information.
This is an unofficial reupload of models/sptcode/pre-trained/models/all in the SafeTensors format using transformers 4.40.1. The goal of this reupload is to prevent older models that are still relevant baselines from becoming stale as a result of changes in HuggingFace. Additionally, I may include minor corrections, such as model max length configuration.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="claudios/sptcode")