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
File size: 2,377 Bytes
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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 -%}
|