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31 changes: 31 additions & 0 deletions jan-v1-4b/Readme.md
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# Jan-v1-4B Node

This configuration sets up a GaiaNet node to run the `Jan-v1-4B` model, a versatile and efficient model suitable for a wide range of conversational tasks.

## Step 1: Install GaiaNet node

The GaiaNet node software version should be 0.5.4 or higher.

```bash
curl -sSfL 'https://github.com/GaiaNet-AI/gaianet-node/releases/latest/download/install.sh' | bash
```

## Step 2: Init with the Jan-v1-4B model

```bash
gaianet init --config https://raw.githubusercontent.com/GaiaNet-AI/node-configs/main/jan-v1-4b/config.json
```

## Step 3: Start the node

```bash
gaianet start
```

Now you can use the node as a web-based chatbot or as an OpenAI API drop-in replacement.

## References

* **Official Base Model:** [janhq/jan-v1-4b](https://huggingface.co/janhq/jan-v1-4b)
* **GGUF Formatted Model:** [Tobivictor/Jan-v1-4B-GGUF](https://huggingface.co/Tobivictor/Jan-v1-4B-GGUF)
* **GaiaNet Node Quick Start Guide:** https://github.com/GaiaNet-AI/gaianet-node
28 changes: 28 additions & 0 deletions jan-v1-4b/config.json
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{
"address": "",
"chat": "https://huggingface.co/Tobivictor/Jan-v1-4B-GGUF/resolve/main/Jan-v1-4B-Q4_K_M.gguf",
"chat_batch_size": "128",
"chat_ctx_size": "8192",
"chat_name": "Jan-v1-4B",
"chat_ubatch_size": "128",
"context_window": "1",
"description": "GaiaNet node config with Jan-v1-4B model for local brunch recommendations and general chat.",
"domain": "gaia.domains",
"embedding": "https://huggingface.co/gaianet/Nomic-embed-text-v1.5-Embedding-GGUF/resolve/main/nomic-embed-text-v1.5.f16.gguf",
"embedding_batch_size": "8192",
"embedding_collection_name": "default",
"embedding_ctx_size": "8192",
"embedding_name": "Nomic-embed-text-v1.5",
"embedding_ubatch_size": "8192",
"llamaedge_chat_port": "9068",
"llamaedge_embedding_port": "9069",
"llamaedge_port": "8080",
"prompt_template": "chatml",
"qdrant_limit": "1",
"qdrant_score_threshold": "0.5",
"rag_policy": "system-message",
"rag_prompt": "Use the following information to answer the question.\n----------------\n",
"reverse_prompt": "",
"snapshot": "",
"system_prompt": "You are a helpful AI assistant. Please answer questions as clearly and concisely as possible."
}
31 changes: 31 additions & 0 deletions qwen2.5-omni-7b/Readme.md
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# Qwen2.5-Omni-7B Node

This configuration sets up a GaiaNet node to run the `Qwen2.5-Omni-7B` model, a powerful and versatile language model suitable for general chat and specialized tasks.

## Step 1: Install GaiaNet node

The GaiaNet node software version should be 0.5.4 or higher.

```bash
curl -sSfL 'https://github.com/GaiaNet-AI/gaianet-node/releases/latest/download/install.sh' | bash
```

## Step 2: Init with the Qwen2.5-Omni-7B model

```bash
gaianet init --config https://raw.githubusercontent.com/GaiaNet-AI/node-configs/main/qwen2.5-omni-7b/config.json
```

## Step 3: Start the node

```bash
gaianet start
```

Now you can use the node as a web-based chatbot or as an OpenAI API drop-in replacement.

## References

* **Official Base Model:** [Qwen/Qwen2.5-Omni-7B](https://huggingface.co/Qwen/Qwen2.5-Omni-7B)
* **GGUF Formatted Model:** [Tobivictor/Qwen2.5-Omni-7B-GGUF](https://huggingface.co/Tobivictor/Qwen2.5-Omni-7B-GGUF)
* **GaiaNet Node Quick Start Guide:** https://github.com/GaiaNet-AI/gaianet-node
28 changes: 28 additions & 0 deletions qwen2.5-omni-7b/config.json
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{
"address": "",
"chat": "https://huggingface.co/Tobivictor/Qwen2.5-Omni-7B-GGUF/resolve/main/Qwen2.5-Omni-7B-Q4_K_M.gguf",
"chat_batch_size": "128",
"chat_ctx_size": "8192",
"chat_name": "Qwen2.5-Omni-7B",
"chat_ubatch_size": "128",
"context_window": "1",
"description": "GaiaNet node config with Qwen2.5-Omni-7B model for local brunch recommendations and general chat.",
"domain": "gaia.domains",
"embedding": "https://huggingface.co/gaianet/Nomic-embed-text-v1.5-Embedding-GGUF/resolve/main/nomic-embed-text-v1.5.f16.gguf",
"embedding_batch_size": "8192",
"embedding_collection_name": "default",
"embedding_ctx_size": "8192",
"embedding_name": "Nomic-embed-text-v1.5",
"embedding_ubatch_size": "8192",
"llamaedge_chat_port": "9068",
"llamaedge_embedding_port": "9069",
"llamaedge_port": "8080",
"prompt_template": "chatml",
"qdrant_limit": "1",
"qdrant_score_threshold": "0.5",
"rag_policy": "system-message",
"rag_prompt": "Use the following information to answer the question.\n----------------\n",
"reverse_prompt": "",
"snapshot": "",
"system_prompt": "You are a helpful AI assistant. Please answer questions as clearly and concisely as possible."
}