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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Model tree for ndavidson/cisco_inam
Base model
stabilityai/stablelm-3b-4e1t