Instructions to use kyLELEng/patchtst-cross-sectional-return-forecast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kyLELEng/patchtst-cross-sectional-return-forecast with Transformers:
# Load model directly from transformers import AutoTokenizer, PatchTSTForPrediction tokenizer = AutoTokenizer.from_pretrained("kyLELEng/patchtst-cross-sectional-return-forecast") model = PatchTSTForPrediction.from_pretrained("kyLELEng/patchtst-cross-sectional-return-forecast") - Notebooks
- Google Colab
- Kaggle
File size: 188 Bytes
74f15a2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | [
"AAPL",
"MSFT",
"AMZN",
"GOOGL",
"NVDA",
"TSLA",
"AMD",
"INTC",
"ADBE",
"ORCL",
"CSCO",
"IBM",
"JPM",
"BAC",
"V",
"MA",
"AXP",
"JNJ",
"PG",
"KO"
] |