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Add library_name and pipeline_tag

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This PR improves the model card by adding the `transformers` library as well as the `table-question-answering` pipeline tag,
making sure people can find the model at https://huggingface.co/models?pipeline_tag=table-question-answering.

Files changed (1) hide show
  1. README.md +147 -3
README.md CHANGED
@@ -1,18 +1,20 @@
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  ---
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- license: llama2
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  datasets:
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  - RUCKBReasoning/TableLLM-SFT
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  language:
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  - en
 
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  tags:
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  - Table
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  - QA
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  - Code
 
 
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  ---
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  # TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
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- | **[Paper](https://arxiv.org/abs/2403.19318)** | **[Training set](https://huggingface.co/datasets/RUCKBReasoning/TableLLM-SFT)** | **[Github](https://github.com/RUCKBReasoning/TableLLM)** | **[Homepage](https://tablellm.github.io/)** |
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  We present **TableLLM**, a powerful large language model designed to handle tabular data manipulation tasks efficiently, whether they are embedded in spreadsheets or documents, meeting the demands of real office scenarios. The TableLLM series encompasses two distinct scales: [TableLLM-7B](https://huggingface.co/RUCKBReasoning/TableLLM-7b) and [TableLLM-13B](https://huggingface.co/RUCKBReasoning/TableLLM-13b), which are fine-tuned based on [CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) and [CodeLlama-13b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf).
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@@ -92,4 +94,146 @@ The prompt template for direct text answer generation on short tables.
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  ### [Solution][INST/]
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  ````
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- For more details about how to use TableLLM, please refer to our GitHub page: <https://github.com/TableLLM/TableLLM>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
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  datasets:
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  - RUCKBReasoning/TableLLM-SFT
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  language:
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  - en
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+ license: llama2
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  tags:
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  - Table
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  - QA
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  - Code
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+ pipeline_tag: table-question-answering
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+ library_name: transformers
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  ---
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  # TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
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+ | **[Paper](https://arxiv.org/abs/2403.19318)** | **[Training set](https://huggingface.co/datasets/RUCKBReasoning/TableLLM-SFT)** | **[Github](https://github.com/TableLLM/TableLLM)** | **[Homepage](https://tablellm.github.io/)** |
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  We present **TableLLM**, a powerful large language model designed to handle tabular data manipulation tasks efficiently, whether they are embedded in spreadsheets or documents, meeting the demands of real office scenarios. The TableLLM series encompasses two distinct scales: [TableLLM-7B](https://huggingface.co/RUCKBReasoning/TableLLM-7b) and [TableLLM-13B](https://huggingface.co/RUCKBReasoning/TableLLM-13b), which are fine-tuned based on [CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) and [CodeLlama-13b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf).
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  ### [Solution][INST/]
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  ````
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+ For more details about how to use TableLLM, please refer to our GitHub page: <https://github.com/TableLLM/TableLLM>
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+
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+ # File information
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+
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+ The repository contains the following file information:
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+
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+ Filename: special_tokens_map.json
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