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TableCheck/gemma-3-27b-it-ft-query-extraction

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face
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Model Card

Model Card for TableCheck's Fine-Tune of google/gemma-3-27b-it

<!-- Provide a quick summary of what the model is/does. --> This fine-tuned model is designed for use with function calls to translate content between languages and extract tags from content. It has been trained on public data.

Model Details

Model Description

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  • —Developed by: TableCheck AI
  • —Funded by: TableCheck
  • —Shared by: TableCheck
  • —Model type: LoRa Adaptor
  • —Language(s) (NLP): English / Japanese / Gemma 3 27B Supported Languages
  • —License: Copyright TableCheck
  • —Finetuned from model: google/gemma-3-27b-it

Model Sources [optional]

<!-- Provide the basic links for the model. --> Trained from public data of venues.

How to Get Started with the Model

Use the code below to get started with the model. TBD

Training Details

Training Data

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Training Procedure

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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).

  • —Hardware Type: [More Information Needed]
  • —Hours used: [More Information Needed]
  • —Cloud Provider: [More Information Needed]
  • —Compute Region: [More Information Needed]
  • —Carbon Emitted: [More Information Needed]

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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BibTeX:

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APA:

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Glossary [optional]

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Model Card Authors [optional]

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Framework versions

  • —PEFT 0.15.0