Text Generation
Transformers
Safetensors
Catalan
Spanish
English
llama
query-parsing
semantic-search
structured-output
json-generation
multilingual
catalan
spanish
LoRA
fine-tuned
AINA
R&D
conversational
Eval Results (legacy)
text-generation-inference
Instructions to use SIRIS-Lab/impuls-salamandra-7b-query-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIRIS-Lab/impuls-salamandra-7b-query-parser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SIRIS-Lab/impuls-salamandra-7b-query-parser") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SIRIS-Lab/impuls-salamandra-7b-query-parser") model = AutoModelForCausalLM.from_pretrained("SIRIS-Lab/impuls-salamandra-7b-query-parser") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SIRIS-Lab/impuls-salamandra-7b-query-parser with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SIRIS-Lab/impuls-salamandra-7b-query-parser" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SIRIS-Lab/impuls-salamandra-7b-query-parser", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/SIRIS-Lab/impuls-salamandra-7b-query-parser
- SGLang
How to use SIRIS-Lab/impuls-salamandra-7b-query-parser 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 "SIRIS-Lab/impuls-salamandra-7b-query-parser" \ --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": "SIRIS-Lab/impuls-salamandra-7b-query-parser", "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 "SIRIS-Lab/impuls-salamandra-7b-query-parser" \ --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": "SIRIS-Lab/impuls-salamandra-7b-query-parser", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use SIRIS-Lab/impuls-salamandra-7b-query-parser with Docker Model Runner:
docker model run hf.co/SIRIS-Lab/impuls-salamandra-7b-query-parser
| {%- set tools = tools if tools is defined else None -%} | |
| {%- set date_string = date_string if date_string is defined else "1 Sep 2024" -%} | |
| {%- set system_message = messages[0].content if messages[0].role == "system" else "" -%} | |
| {%- if messages[0].role == "system" -%} | |
| {%- set messages = messages[1:] -%} | |
| {%- endif -%} | |
| {%- if not tool_prompt -%} | |
| {%- set tool_prompt = "For each function call return a json object with function name and arguments within <tool_call> </tool_call> tags with the following schema: | |
| <tool_call> | |
| {\"name\": <function-name>, \"arguments\": <args-dict>} | |
| </tool_call>" -%} | |
| {%- endif -%} | |
| {%- if system_message or tools -%} | |
| {{- '<|im_start|>system | |
| '}} | |
| {%- endif -%} | |
| {%- if system_message %} | |
| {{- system_message + " | |
| "}} | |
| {%- endif -%} | |
| {%- if tools -%} | |
| {{- "You have function-calling capabilities. 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. | |
| " }} | |
| {{- "<tools> | |
| " }} | |
| {{- tools }} | |
| {{- " | |
| </tools> | |
| " }} | |
| {{- tool_prompt -}} | |
| {%- endif -%} | |
| {%- if system_message or tools -%} | |
| {{- '<|im_end|> | |
| '}} | |
| {%- endif -%} | |
| {# Main message loop #} | |
| {%- for message in messages -%} | |
| {%- if message.role == "user" or message.role == "assistant" or message.role == "tool" -%} | |
| {%- if loop.first and message.role != "user" -%} | |
| {{ raise_exception("Invalid sequence: The first message role must be 'user' after 'system' if provided .") }} | |
| {%- endif -%} | |
| {%- if not loop.first and message.role in ["user", "assistant"] and message.role == loop.previtem.role -%} | |
| {{ raise_exception("Invalid sequence: Consecutive messages cannot have the same role ('user' or 'assistant').") }} | |
| {%- endif -%} | |
| {%- if message.role == "user" and not loop.first and loop.previtem.role != "assistant" -%} | |
| {{ raise_exception("Invalid sequence: A 'user' message must be preceded by an 'assistant' message.") }} | |
| {%- endif -%} | |
| {%- if message.role == "tool" and not loop.first and loop.previtem.role not in ["assistant", "tool"] -%} | |
| {{ raise_exception("Invalid sequence: A 'tool' message must be preceded by 'assistant' or 'tool'.") }} | |
| {%- endif -%} | |
| {%- else -%} | |
| {{- raise_exception("Invalid role detected: only 'user', 'assistant', or 'tool' roles are accepted.") }} | |
| {%- endif -%} | |
| {%- if message.role == "user" or (message.role == "assistant" and message.tool_calls is not defined) -%} | |
| {{- '<|im_start|>' + message.role + ' | |
| ' + message.content | trim + '<|im_end|> | |
| '}} | |
| {%- elif message.role == "assistant" -%} | |
| {{- '<|im_start|>' + message.role }} | |
| {%- for tool_call in message.tool_calls -%} | |
| {{ ' | |
| <tool_call> | |
| ' }} | |
| {%- if tool_call.function -%} | |
| {"name": "{{ tool_call.function.name }}", "arguments": {{ tool_call.function.arguments | tojson }} } | |
| {%- else -%} | |
| {"name": "{{ tool_call.name }}", "arguments": {{ tool_call.arguments | tojson }} } | |
| {%- endif -%} | |
| {{ ' | |
| </tool_call>' }} | |
| {%- endfor -%} | |
| {{- '<|im_end|> | |
| ' }} | |
| {%- elif message.role == "tool" -%} | |
| {%- if loop.previtem and loop.previtem.role != "tool" -%} | |
| {{- '<|im_start|>tool | |
| ' }} | |
| {%- endif -%} | |
| {{- '<tool_response> | |
| ' }} | |
| {{- message.content }} | |
| {{- ' | |
| </tool_response> | |
| ' }} | |
| {%- if loop.last or loop.nextitem.role != "tool" -%} | |
| {{- '<|im_end|> | |
| '}} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {# Prompt for assistant generation if needed #} | |
| {%- if add_generation_prompt -%} | |
| {{- '<|im_start|>assistant | |
| ' }} | |
| {%- endif -%} |