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 tokenizer.json from XinyueWangg/TimeBraid-2.5B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/XinyueWangg/TimeBraid-2.5B/resolve/main/tokenizer.json
- Command line
-
hf download hf://XinyueWangg/TimeBraid-2.5B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/XinyueWangg/TimeBraid-2.5B/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- ddd0a26bfce24baf80f907f41ad9f31fb4bf81678242726680d3701030d24428
- Size of remote file:
- 11.4 MB
- SHA256:
- 06fc61a040c16d28587465e01e4dbaed6d0a61bfe71300ba6c115f7d109a9ca8
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