GSTLawyer

Model Card for Model ID

Trained on the Indian GST and Service Tax legal pronouncements till 2023

Model Details

Model Description

• Developed by: [Suvir Misra, Commissioner, GST, India]
• Shared by [optional]: [Suvir Misra, Commissioner, GST, India]
• Model type: [Llama-2-7B-Chat]
• Language(s) (NLP): [English]
• License: [apache-2.0]
• Finetuned from model [optional]: [TheBloke/Llama-2-7B-Chat-GPTQ]

Model Sources [optional]

TheBloke/Llama-2-7B-Chat-GPTQ

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• Paper [optional]: [More Information Needed]
• Demo [optional]: [More Information Needed]

Uses

Try asking some question on the GST or Service Tax law/ ruling till the year 2023.

Direct Use

Try asking some question on the GST or Service Tax law/ ruling till the year 2023.

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

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Training Details

Training Data

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Speeds, Sizes, Times [optional]

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Evaluation

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Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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Glossary [optional]

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Model Card Authors [optional]

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Training procedure

The following bitsandbytes quantization config was used during training:

• quant_method: gptq
• bits: 4
• tokenizer: None
• dataset: None
• group_size: 128
• damp_percent: 0.01
• desc_act: False
• sym: True
• true_sequential: True
• use_cuda_fp16: False
• model_seqlen: None
• block_name_to_quantize: None
• module_name_preceding_first_block: None
• batch_size: 1
• pad_token_id: None
• disable_exllama: False
• max_input_length: None

Framework versions

• PEFT 0.6.2