Merge pull request #742 from janhq/741-chore-adding-correct-example-for-model-parameters-with-examples
chore: clarification changes to the model settings and model parameters
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4c2c320105
@ -65,17 +65,19 @@ Here's a standard example `model.json` for a GGUF model.
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"state": enum[null, "downloading", "ready", "starting", "stopping", ...]
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"state": enum[null, "downloading", "ready", "starting", "stopping", ...]
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"format": "ggufv3", // Defaults to "ggufv3"
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"format": "ggufv3", // Defaults to "ggufv3"
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"settings": { // Models are initialized with settings
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"settings": { // Models are initialized with settings
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"ctx_len": "2048",
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"ctx_len": 2048,
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"ngl": "100",
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"ngl": 100,
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"embedding": "true",
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"embedding": true,
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"n_parallel": "4",
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"n_parallel": 4,
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},
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},
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"parameters": { // Models are called parameters
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"parameters": { // Models are called parameters
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"temperature": "0.7",
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"stream": true,
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"token_limit": "2048",
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"max_tokens": 2048,
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"top_k": "0",
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"stop": ["<endofstring>"], // This usually can be left blank, only used with specific need from model author
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"top_p": "1",
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"frequency_penalty": 0,
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"stream": "true"
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"presence_penalty": 0,
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"temperature": 0.7,
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"top_p": 0.95
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},
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},
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"metadata": {}, // Defaults to {}
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"metadata": {}, // Defaults to {}
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"assets": [ // Defaults to current dir
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"assets": [ // Defaults to current dir
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@ -83,6 +85,10 @@ Here's a standard example `model.json` for a GGUF model.
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]
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]
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```
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```
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The model settings in the example can be found at: [Nitro's model settings](https://nitro.jan.ai/features/load-unload#table-of-parameters)
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The model parameters in the example can be found at: [Nitro's model parameters](https://nitro.jan.ai/api-reference#tag/Chat-Completion)
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## API Reference
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## API Reference
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Jan's Model API is compatible with [OpenAI's Models API](https://platform.openai.com/docs/api-reference/models), with additional methods for managing and running models locally.
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Jan's Model API is compatible with [OpenAI's Models API](https://platform.openai.com/docs/api-reference/models), with additional methods for managing and running models locally.
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