Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Tiny_2000_Augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Tiny_2000_Augmented with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Tiny_2000_Augmented") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Tiny_2000_Augmented") - Notebooks
- Google Colab
- Kaggle
File size: 659 Bytes
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pipeline_tag: time-series-forecasting
license: apache-2.0
tags:
- TSFM
- Finance
- Financial Forecasting
- FinText
library_name: transformers
---
## Chronos-Tiny (TSFM) โ Augmented (2000)
This is the **Time Series Foundation Model (TSFM)**, pre-trained on **augmented financial time series data up to the year 2000** using the **Chronos architecture (Tiny size)**. The dataset spans from **1990โ2000** and includes **augmented data**.
๐ **Related Links**
- [๐ View all Chronos (Tiny) models - Augmented](https://huggingface.co/collections/FinText/chronos-tiny-augmented)
- [๐ View all TSFMs](https://huggingface.co/FinText/collections)
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