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upate to llama3.1 elsewhere in repo (#6032)
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@@ -63,7 +63,7 @@ docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 114
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Now you can run a model:
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```
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docker exec -it ollama ollama run llama3
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docker exec -it ollama ollama run llama3.1
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```
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### Try different models
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@@ -227,7 +227,7 @@ curl http://localhost:11434/api/chat -d '{"model": "mistral"}'
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To preload a model using the CLI, use the command:
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```shell
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ollama run llama3 ""
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ollama run llama3.1 ""
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```
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## How do I keep a model loaded in memory or make it unload immediately?
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@@ -15,7 +15,7 @@ import { Ollama } from "@langchain/community/llms/ollama";
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const ollama = new Ollama({
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baseUrl: "http://localhost:11434",
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model: "llama3",
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model: "llama3.1",
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});
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const answer = await ollama.invoke(`why is the sky blue?`);
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@@ -23,7 +23,7 @@ const answer = await ollama.invoke(`why is the sky blue?`);
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console.log(answer);
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```
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That will get us the same thing as if we ran `ollama run llama3 "why is the sky blue"` in the terminal. But we want to load a document from the web to ask a question against. **Cheerio** is a great library for ingesting a webpage, and **LangChain** uses it in their **CheerioWebBaseLoader**. So let's install **Cheerio** and build that part of the app.
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That will get us the same thing as if we ran `ollama run llama3.1 "why is the sky blue"` in the terminal. But we want to load a document from the web to ask a question against. **Cheerio** is a great library for ingesting a webpage, and **LangChain** uses it in their **CheerioWebBaseLoader**. So let's install **Cheerio** and build that part of the app.
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```bash
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npm install cheerio
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