mirror of
https://github.com/mudler/LocalAI.git
synced 2024-06-07 19:40:48 +00:00
48d0aa2f6d
* models: add reranker and parler-tts-mini Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: chatml im_end should not have a newline Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * models(noromaid): add Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * models(llama3): add 70b, add dolphin2.9 Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * models(llama3): add unholy-8b Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * models(llama3): add therapyllama3, aura Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
60 lines
2.3 KiB
YAML
60 lines
2.3 KiB
YAML
name: gpt-4
|
|
mmap: true
|
|
parameters:
|
|
model: huggingface://NousResearch/Hermes-2-Pro-Mistral-7B-GGUF/Hermes-2-Pro-Mistral-7B.Q2_K.gguf
|
|
|
|
template:
|
|
chat_message: |
|
|
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
|
|
{{- if .FunctionCall }}
|
|
<tool_call>
|
|
{{- else if eq .RoleName "tool" }}
|
|
<tool_response>
|
|
{{- end }}
|
|
{{- if .Content}}
|
|
{{.Content }}
|
|
{{- end }}
|
|
{{- if .FunctionCall}}
|
|
{{toJson .FunctionCall}}
|
|
{{- end }}
|
|
{{- if .FunctionCall }}
|
|
</tool_call>
|
|
{{- else if eq .RoleName "tool" }}
|
|
</tool_response>
|
|
{{- end }}<|im_end|>
|
|
# https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B-GGUF#prompt-format-for-function-calling
|
|
function: |
|
|
<|im_start|>system
|
|
You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
|
|
<tools>
|
|
{{range .Functions}}
|
|
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
|
|
{{end}}
|
|
</tools>
|
|
Use the following pydantic model json schema for each tool call you will make:
|
|
{'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']}
|
|
For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
|
|
<tool_call>
|
|
{'arguments': <args-dict>, 'name': <function-name>}
|
|
</tool_call><|im_end|>
|
|
{{.Input -}}
|
|
<|im_start|>assistant
|
|
<tool_call>
|
|
chat: |
|
|
{{.Input -}}
|
|
<|im_start|>assistant
|
|
completion: |
|
|
{{.Input}}
|
|
context_size: 4096
|
|
f16: true
|
|
stopwords:
|
|
- <|im_end|>
|
|
- <dummy32000>
|
|
- "\n</tool_call>"
|
|
- "\n\n\n"
|
|
usage: |
|
|
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
|
|
"model": "gpt-4",
|
|
"messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}]
|
|
}'
|