Merge pull request #23 from LlamaEdge/fix-link

LlamaEdge · Aug 30, 2024 · 79c5a37 · 79c5a37
2 parents f7c509e + c024992
commit 79c5a37
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diff --git a/docs/user-guide/openai-api/continue.md b/docs/user-guide/openai-api/continue.md
@@ -14,7 +14,7 @@ those IDEs. You can easily configure it to use a local LlamaEdge LLM as backends
 
 ## Prerequisites
 
-Follow [this guide](intro.md) to run an open-source LLM locally.
+Follow [this guide](./intro.md) to run an open-source LLM locally.
 Since we have a coding application here, you should download a coding LLM like the Codestral.
 
 ```
@@ -30,7 +30,7 @@ wasmedge --dir .:. \
     llama-api-server.wasm \
     --model-alias default,embedding \
     --model-name Codestral-22B-v0.1-hf-Q5_K_M,nomic-embed-text-v1.5.f16 \
-    --prompt-template llama-3-chat,embedding \
+    --prompt-template mistral-instruct,embedding \
     --batch-size 128,8192 \
     --ctx-size 32768,8192
 ```

diff --git a/docs/user-guide/openai-api/flowiseai-tool-call.md b/docs/user-guide/openai-api/flowiseai-tool-call.md
@@ -9,7 +9,7 @@ You can configure the FlowiseAI tool to use a local LlamaEdge LLM that supports
 
 ## Prerequisites
 
-Follow [this guide](intro.md) to run an open-source LLM locally.
+Follow [this guide](./intro.md) to run an open-source LLM locally.
 In this example, we need an open source LLM that is capable of generating tool call (JSON) responses.
 The Mistral v0.3 7B model is a good choice here.
 

diff --git a/docs/user-guide/openai-api/lobechat.md b/docs/user-guide/openai-api/lobechat.md
@@ -13,7 +13,7 @@ You can use configure it to use LlamaEdge as the backend Large Language Model (L
 
 ## Prerequisites
 
-Follow [this guide](intro.md) to run an open-source LLM locally.
+Follow [this guide](./intro.md) to run an open-source LLM locally.
 
 ## Steps to integrate LobeChat and LlamaEdge
 

diff --git a/docs/user-guide/openai-api/obsidian.md b/docs/user-guide/openai-api/obsidian.md
@@ -14,7 +14,7 @@ This guide explains how to set up and use the plugin with a lightweight LlamaEdg
 
 ## Prerequisites
 
-Follow [this guide](intro.md) to run an open-source LLM locally.
+Follow [this guide](./intro.md) to run an open-source LLM locally.
 
 ## Obsidian-local-gpt Plugin Setup
 

diff --git a/docs/user-guide/openai-api/translation-agent.md b/docs/user-guide/openai-api/translation-agent.md
@@ -12,7 +12,7 @@ This LLM Translation Agent originally built by [Prof. Andrew Ng](https://www.lin
 
 ## Prerequisites
 
-Follow [this guide](intro.md) to run an open-source LLM locally.
+Follow [this guide](./intro.md) to run an open-source LLM locally.
 In this example, we need an open source LLM that is good at multiple languages.
 The Gemma-2 7B model from Google is a good choice here.