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
File size: 310 Bytes
0acbed8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | """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"]
|