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Cisco iNAM

Cisco iNAM (Intelligent Networking, Automation, and Management), is a nano sized LLM used for asking questions about Cisco Datacenter Products.

Model Details

Model Description

Model is quantized to 4-bit to be able to run inference on physical deployments of datacenter products. Initial launch is planned for Nexus Dashboard.

  • Developed by: Cisco
  • Funded by [optional]: Cisco
  • Model type: Transformer
  • Language(s) (NLP): English
  • License: Cisco Commercial

Model Sources [optional]

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Input Format

The model is trained with the ChatML format:

<|im_start|>system
System message here.<|im_end|>
<|im_start|>user
Your message here!<|im_end|>
<|im_start|>assistant

Direct Use

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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

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

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Speeds, Sizes, Times [optional]

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Evaluation

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

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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Framework versions

  • PEFT 0.7.2.dev0
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