Time Series Forecasting
Transformers
PyTorch
Korean
jnu_tsb
feature-extraction
jnu-tsb
time-series
forecasting
chronos-2
polyglot-ko
korean
finance
covariates
r
reticulate
education
custom_code
Instructions to use HONGRIZON/JNU-TSB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HONGRIZON/JNU-TSB with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HONGRIZON/JNU-TSB", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Delete requirements.txt
Browse files- requirements.txt +0 -8
requirements.txt
DELETED
|
@@ -1,8 +0,0 @@
|
|
| 1 |
-
transformers>=4.45.0
|
| 2 |
-
torch>=2.2.0
|
| 3 |
-
chronos-forecasting>=2.0.0
|
| 4 |
-
pandas>=2.2.0
|
| 5 |
-
pyarrow>=15.0.0
|
| 6 |
-
accelerate>=0.33.0
|
| 7 |
-
huggingface_hub>=0.25.0
|
| 8 |
-
gradio>=4.44.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|