Time Series Forecasting
Transformers
Safetensors
llama
text-generation
time-series
pretrained-model
foundation-model
multimodality
multimodal-time-series-foundation-model
text-generation-inference
Instructions to use ChengsenWang/ChatTime-1-7B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChengsenWang/ChatTime-1-7B-Chat with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ChengsenWang/ChatTime-1-7B-Chat") model = AutoModelForCausalLM.from_pretrained("ChengsenWang/ChatTime-1-7B-Chat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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As depicted in Figure 1(c), during the instruction fine-tuning stage, we fine-tune [ChengsenWang/ChatTime-1-7B-Base](https://huggingface.co/ChengsenWang/ChatTime-1-7B-Base) on [ChengsenWang/ChatTime-1-Finetune-100K](https://huggingface.co/datasets/ChengsenWang/ChatTime-1-Finetune-100K), yielding [ChengsenWang/ChatTime-1-7B-Chat](https://huggingface.co/ChengsenWang/ChatTime-1-7B-Chat).
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For details on ChatTime models, training data and procedures, and experimental results, please refer to the [arXiv](https://arxiv.org/abs/
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As depicted in Figure 1(c), during the instruction fine-tuning stage, we fine-tune [ChengsenWang/ChatTime-1-7B-Base](https://huggingface.co/ChengsenWang/ChatTime-1-7B-Base) on [ChengsenWang/ChatTime-1-Finetune-100K](https://huggingface.co/datasets/ChengsenWang/ChatTime-1-Finetune-100K), yielding [ChengsenWang/ChatTime-1-7B-Chat](https://huggingface.co/ChengsenWang/ChatTime-1-7B-Chat).
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For details on ChatTime models, training data and procedures, and experimental results, please refer to the [arXiv](https://arxiv.org/abs/2412.11376).
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