Instructions to use Flyoz/magistral_tools with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Flyoz/magistral_tools with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Flyoz/magistral_tools")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Flyoz/magistral_tools")
model = AutoModelForCausalLM.from_pretrained("Flyoz/magistral_tools", device_map="auto")
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 Flyoz/magistral_tools with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Flyoz/magistral_tools"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Flyoz/magistral_tools",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Flyoz/magistral_tools

SGLang

How to use Flyoz/magistral_tools 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 "Flyoz/magistral_tools" \
    --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": "Flyoz/magistral_tools",
		"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 "Flyoz/magistral_tools" \
        --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": "Flyoz/magistral_tools",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use Flyoz/magistral_tools with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Flyoz/magistral_tools to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Flyoz/magistral_tools to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Flyoz/magistral_tools to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="Flyoz/magistral_tools",
    max_seq_length=2048,
)

Docker Model Runner
How to use Flyoz/magistral_tools with Docker Model Runner:
```
docker model run hf.co/Flyoz/magistral_tools
```

magistral_tools / chat_template.jinja

Flyoz

(Trained with Unsloth)

d7ce401 verified about 1 year ago

Raw

History Blame Contribute Delete

2.73 kB

	{{- bos_token }}

	{%- if messages[0]['role'] == 'system' %}
	{%- if messages[0]['content'] is string %}
	{%- set system_message = messages[0]['content'] %}
	{%- else %}
	{%- set system_message = messages[0]['content'][0]['text'] %}
	{%- endif %}
	{%- set loop_messages = messages[1:] %}
	{%- else %}
	{%- set system_message = "A user will ask you to solve a task. You should first draft your thinking process (inner monologue) until you have derived the final answer. Afterwards, write a self-contained summary of your thoughts (i.e. your summary should be succinct but contain all the critical steps you needed to reach the conclusion). You should use Markdown and Latex to format your response. Write both your thoughts and summary in the same language as the task posed by the user.\n\nYour thinking process must follow the template below:\n<think>\nYour thoughts or/and draft, like working through an exercise on scratch paper. Be as casual and as long as you want until you are confident to generate a correct answer.\n</think>\n\nHere, provide a concise summary that reflects your reasoning and presents a clear final answer to the user.\n\nProblem:" %}
	{%- set loop_messages = messages %}
	{%- endif %}
	{{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }}
	{#- Edits made by Unsloth #}
	{%- for message in loop_messages %}
	{%- if message['role'] == 'user' %}
	{%- if message['content'] is string %}
	{{- '[INST]' + message['content'] + '[/INST]' }}
	{%- else %}
	{{- '[INST]' }}
	{%- for block in message['content'] %}
	{%- if block['type'] == 'text' %}
	{{- block['text'] }}
	{%- elif block['type'] in ['image', 'image_url'] %}
	{{- '[IMG]' }}
	{%- else %}
	{{- raise_exception('Only text and image blocks are supported in message content!') }}
	{%- endif %}
	{%- endfor %}
	{{- '[/INST]' }}
	{%- endif %}
	{%- elif message['role'] == 'system' %}
	{%- if message['content'] is string %}
	{{- '[SYSTEM_PROMPT]' + message['content'] + '[/SYSTEM_PROMPT]' }}
	{%- else %}
	{{- '[SYSTEM_PROMPT]' + message['content'][0]['text'] + '[/SYSTEM_PROMPT]' }}
	{%- endif %}
	{%- elif message['role'] == 'assistant' %}
	{%- if message['content'] is string %}
	{{- message['content'] + eos_token }}
	{%- else %}
	{{- message['content'][0]['text'] + eos_token }}
	{%- endif %}
	{%- else %}
	{{- raise_exception('Only user, system and assistant roles are supported!') }}
	{%- endif %}
	{%- endfor %}