Update README.md with tool-use support for huggingface and vLLM
#9
by
hanseungwook
- opened
README.md
CHANGED
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@@ -78,6 +78,102 @@ completion = client.chat.completions.create(
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```
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---
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## **Evaluation Summary**
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)
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```
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## With Tool-use
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To enable tool-use, load, tokenize, and generate as the examples above, but additionally define a set of tools and pass them to the chat template.
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**Using transformers**
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("llm360/k2-v2-instruct", device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained("llm360/k2-v2-instruct")
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prompt = "Explain why the derivative of sin(x) is cos(x)."
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messages = [
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{"role": "system", "content": "You are K2, a helpful assistant created by Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Institute of Foundation Models (IFM)."},
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{"role": "user", "content": prompt}
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]
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# Define list of tools
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tools = [
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{
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"type": "function",
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"name": "get_horoscope",
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"description": "Get today's horoscope for an astrological sign.",
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"parameters": {
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"type": "object",
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"properties": {
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"sign": {
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"type": "string",
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"description": "An astrological sign like Taurus or Aquarius",
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},
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},
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"required": ["sign"],
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},
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},
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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reasoning_effort="high" # Or "medium"/"low"
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tools=tools
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)
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inputs = tokenizer(text, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=200)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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**Using vLLM**
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Serve the model with tool-use enabled and parser set.
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```
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vllm serve LLM360/K2-V2-Instruct --enable-auto-tool-choice --tool-call-parser hermes --tensor-parallel-size 8 --port 8000
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```
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```
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from openai import OpenAI
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client = OpenAI(
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base_url="http://localhost:8000/v1",
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api_key="key"
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)
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# Define list of tools
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tools = [
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{
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"type": "function",
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"name": "get_horoscope",
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"description": "Get today's horoscope for an astrological sign.",
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"parameters": {
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"type": "object",
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"properties": {
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"sign": {
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"type": "string",
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"description": "An astrological sign like Taurus or Aquarius",
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},
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},
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"required": ["sign"],
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},
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},
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]
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completion = client.chat.completions.create(
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model="LLM360/K2-V2-Instruct",
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messages = [
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{"role": "system", "content": "You are K2, a helpful assistant created by Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Institute of Foundation Models (IFM)."},
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{"role": "user", "content": "Explain why the derivative of sin(x) is cos(x)."}
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],
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extra_body={
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"chat_template_kwargs": {"reasoning_effort": "high"},
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},
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tools=tools,
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)
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```
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---
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## **Evaluation Summary**
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