Text Generation
Transformers
Turkish
English
chat-template
jinja2
prompt-format
pharmacy
tool-calling
rag
conversational
Instructions to use menesnas/ChatTemplate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use menesnas/ChatTemplate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="menesnas/ChatTemplate") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("menesnas/ChatTemplate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use menesnas/ChatTemplate with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "menesnas/ChatTemplate" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "menesnas/ChatTemplate", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/menesnas/ChatTemplate
- SGLang
How to use menesnas/ChatTemplate with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "menesnas/ChatTemplate" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "menesnas/ChatTemplate", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "menesnas/ChatTemplate" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "menesnas/ChatTemplate", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use menesnas/ChatTemplate with Docker Model Runner:
docker model run hf.co/menesnas/ChatTemplate
| {#- | |
| Pharmacy Prompt Serialization Format (PPSF) v1.0 / v1.1 | |
| Supported roles: | |
| system -> @SYSTEM | |
| user -> @PATIENT (with optional @REFERENCE via metadata) | |
| assistant -> @PHARMACIST (with optional @THOUGHT via metadata) | |
| tool -> @TOOL_RESPONSE | |
| Tool Calling: | |
| tools -> @TOOLS | |
| tool_calls -> @TOOL_CALL | |
| Copyright: | |
| PPSF v1.0 | |
| -#} | |
| {{- "@FORMAT PPSF/1.0\n\n" -}} | |
| {#- =========================== | |
| SYSTEM MESSAGE | |
| =========================== -#} | |
| {%- if messages and messages[0]["role"] == "system" -%} | |
| @SYSTEM | |
| {{ messages[0]["content"] | trim }} | |
| {% endif -%} | |
| {#- =========================== | |
| TOOL DEFINITIONS | |
| =========================== -#} | |
| {%- if tools -%} | |
| @TOOLS | |
| Available tools: | |
| {% for tool in tools -%} | |
| {{ tool | tojson }} | |
| {% endfor %} | |
| To invoke a tool respond ONLY with: | |
| @TOOL_CALL | |
| { | |
| "name": "...", | |
| "arguments": { ... } | |
| } | |
| {% endif -%} | |
| {#- =========================== | |
| CHAT HISTORY | |
| =========================== -#} | |
| {%- for message in messages -%} | |
| {%- if loop.first and message["role"] == "system" -%} | |
| {# Handled in system block #} | |
| {%- elif message["role"] == "user" -%} | |
| {%- set ref = message.get("reference") or (message.get("metadata") and message.metadata.get("reference")) -%} | |
| {%- if ref -%} | |
| @REFERENCE | |
| {{ ref | trim }} | |
| {% endif -%} | |
| @PATIENT | |
| {{ message["content"] | trim }} | |
| {% elif message["role"] == "assistant" -%} | |
| {%- set thought = message.get("thought") or (message.get("metadata") and message.metadata.get("thought")) -%} | |
| {%- if thought -%} | |
| @THOUGHT | |
| {{ thought | trim }} | |
| {% endif -%} | |
| {%- if message.get("content") -%} | |
| @PHARMACIST | |
| {{ message["content"] | trim }} | |
| {% endif -%} | |
| {%- if message.get("tool_calls") -%} | |
| {%- for tc in message["tool_calls"] -%} | |
| @TOOL_CALL | |
| { | |
| "name": {{ tc["function"]["name"] | tojson }}, | |
| "arguments": {{ tc["function"]["arguments"] if tc["function"]["arguments"] is string else (tc["function"]["arguments"] | tojson) }} | |
| } | |
| {% endfor -%} | |
| {%- endif -%} | |
| {%- elif message["role"] == "tool" -%} | |
| @TOOL_RESPONSE | |
| {{ message["content"] | trim }} | |
| {% endif -%} | |
| {%- endfor -%} | |
| {#- =========================== | |
| GENERATION PROMPT | |
| =========================== -#} | |
| {%- if add_generation_prompt -%} | |
| @PHARMACIST | |
| {%- endif -%} | |