Time Series Forecasting
Transformers
Safetensors
TimesFM
timebraid
text-generation
time-series
time-series-understanding
forecasting
multimodal
qwen3
custom_code
Instructions to use XinyueWangg/TimeBraid-2.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use XinyueWangg/TimeBraid-2.5B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("XinyueWangg/TimeBraid-2.5B", trust_remote_code=True, device_map="auto") - TimesFM
How to use XinyueWangg/TimeBraid-2.5B with TimesFM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download processing_timebraid.py from XinyueWangg/TimeBraid-2.5B: direct link, hf CLI and curl.
- Browser
- Download file 310 Bytes
-
https://huggingface.co/XinyueWangg/TimeBraid-2.5B/resolve/main/processing_timebraid.py
- Command line
-
hf download hf://XinyueWangg/TimeBraid-2.5B/processing_timebraid.py
-
curl -L -o processing_timebraid.py https://huggingface.co/XinyueWangg/TimeBraid-2.5B/resolve/main/processing_timebraid.py
310 Bytes
| """Hugging Face AutoProcessor bridge for TimeBraid.""" | |
| from ._timebraid_hf_runtime import TimeBraidRuntimeLoader | |
| class TimeBraidProcessor(TimeBraidRuntimeLoader): | |
| """Load the processor from the runtime beside the requested model.""" | |
| _auto_class = "AutoProcessor" | |
| __all__ = ["TimeBraidProcessor"] | |