Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
-license: mit
 language:
 - en
+license: llama2
 ---
 
 # TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data
@@ -19,17 +19,16 @@ We present TAT-LLM, a specialized language model crafted through the innovative
 | ---   | ---  | ---   | ---   | ---    |
 | GPT-3.5-Turbo | - | 58.00 | 59.47 | 52.74 |
 | GPT-4 | - | 63.91 | 71.92 | 64.46 |
-| TAT-LLM-7B-LORA | 7B | 65.13 | 76.49 | 71.38 |
-| TAT-LLM-7B-FFT | 7B | 69.75 | 76.91 | 72.64 |
-| TAT-LLM-13B-LORA | 13B | 71.93 | 77.51 | 72.22 |
-| TAT-LLM-13B-FFT | 13B | 72.97 | 78.41 | 73.18 |
-| TAT-LLM-70B-LORA | 70B | **76.81** | 81.42 | 76.55 |
-| TAT-LLM-70B-FFT | 70B | 76.11 | **82.20** | **76.97** |
-
+| [TAT-LLM-7B-LORA](https://huggingface.co/next-tat/tat-llm-7b-lora) | 7B | 65.13 | 76.49 | 71.38 |
+| [TAT-LLM-7B-FFT](https://huggingface.co/next-tat/tat-llm-7b-fft) | 7B | 69.75 | 76.91 | 72.64 |
+| [TAT-LLM-13B-LORA](https://huggingface.co/next-tat/tat-llm-13b-lora) | 13B | 71.93 | 77.51 | 72.22 |
+| [TAT-LLM-13B-FFT](https://huggingface.co/next-tat/tat-llm-13b-fft) | 13B | 72.97 | 78.41 | 73.18 |
+| [TAT-LLM-70B-LORA](https://huggingface.co/next-tat/tat-llm-70b-lora) | 70B | **76.81** | 81.42 | 76.55 |
+| [TAT-LLM-70B-FFT](https://huggingface.co/next-tat/tat-llm-70b-fft) | 70B | 76.11 | **82.20** | **76.97** |
 
 ## Training
 
-We train our TAT-LLM model in various sizes, including 7B, 13B, and 70B, using different methods such as parameter-efficient fine-tuning and full-parameter fine-tuning of LLaMA 2 on a combination of financial data from the FinQA, TAT-QA, and TAT-DQA datasets. To refine accuracy, we introduce an External Executor, enhancing the model by processing intermediate outputs to derive conclusive answers. Please refer to the [paper](https://arxiv.org/abs/2401.13223) for more details.
+We train our TAT-LLM model in various sizes, including 7B, 13B, and 70B, using different methods such as parameter-efficient fine-tuning and full-parameter fine-tuning of LLaMA 2 on a combination of financial data from the FinQA, TAT-QA, and TAT-DQA datasets([🤗HuggingFace Repo](https://huggingface.co/datasets/next-tat/tat-llm-instructions)). To refine accuracy, we introduce an External Executor, enhancing the model by processing intermediate outputs to derive conclusive answers. Please refer to the [paper](https://arxiv.org/abs/2401.13223) for more details.
 
 ## Inference & Evaluation
 
@@ -48,4 +47,4 @@ If you find this model helpful, please consider citing our paper:
       archivePrefix={arXiv},
       primaryClass={cs.CL}
 }
-```
+```