Time Series Forecasting
Transformers
Safetensors
Chinese
English
gemma4
image-text-to-text
time-series
forecasting
decision-making
custom_code
Instructions to use GizzAI/Gizzai-Sense-T-E2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GizzAI/Gizzai-Sense-T-E2B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("GizzAI/Gizzai-Sense-T-E2B", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("GizzAI/Gizzai-Sense-T-E2B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from GizzAI/Gizzai-Sense-T-E2B: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/GizzAI/Gizzai-Sense-T-E2B/resolve/main/tokenizer.json
- Command line
-
hf download hf://GizzAI/Gizzai-Sense-T-E2B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/GizzAI/Gizzai-Sense-T-E2B/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- c62336ad134cad6f154d84eb0e5a5fa9ca17cd665ef3ba5ac4fd02b1486760b4
- Size of remote file:
- 32.2 MB
- SHA256:
- cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f
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