metadata
language:
- en
- fr
- de
- es
- it
- pt
- zh
- ja
- ru
- ko
license: other
license_name: mrl
inference: false
license_link: https://mistral.ai/licenses/MRL-0.1.md
extra_gated_prompt: >-
# Mistral AI Research License
If You want to use a Mistral Model, a Derivative or an Output for any purpose
that is not expressly authorized under this Agreement, You must request a
license from Mistral AI, which Mistral AI may grant to You in Mistral AI's
sole discretion. To discuss such a license, please contact Mistral AI via the
website contact form: https://mistral.ai/contact/
## 1. Scope and acceptance
**1.1. Scope of the Agreement.** This Agreement applies to any use,
modification, or Distribution of any Mistral Model by You, regardless of the
source You obtained a copy of such Mistral Model.
**1.2. Acceptance.** By accessing, using, modifying, Distributing a Mistral
Model, or by creating, using or distributing a Derivative of the Mistral
Model, You agree to be bound by this Agreement.
**1.3. Acceptance on behalf of a third-party.** If You accept this Agreement
on behalf of Your employer or another person or entity, You warrant and
represent that You have the authority to act and accept this Agreement on
their behalf. In such a case, the word "You" in this Agreement will refer to
Your employer or such other person or entity.
## 2. License
**2.1. Grant of rights**. Subject to Section 3 below, Mistral AI hereby
grants You a non-exclusive, royalty-free, worldwide, non-sublicensable,
non-transferable, limited license to use, copy, modify, and Distribute under
the conditions provided in Section 2.2 below, the Mistral Model and any
Derivatives made by or for Mistral AI and to create Derivatives of the Mistral
Model.
**2.2. Distribution of Mistral Model and Derivatives made by or for Mistral
AI.** Subject to Section 3 below, You may Distribute copies of the Mistral
Model and/or Derivatives made by or for Mistral AI, under the following
conditions: You must make available a copy of this Agreement to third-party
recipients of the Mistral Models and/or Derivatives made by or for Mistral AI
you Distribute, it being specified that any rights to use the Mistral Models
and/or Derivatives made by or for Mistral AI shall be directly granted by
Mistral AI to said third-party recipients pursuant to the Mistral AI Research
License agreement executed between these parties; You must retain in all
copies of the Mistral Models the following attribution notice within a
"Notice" text file distributed as part of such copies: "Licensed by Mistral AI
under the Mistral AI Research License".
**2.3. Distribution of Derivatives made by or for You.** Subject to Section 3
below, You may Distribute any Derivatives made by or for You under additional
or different terms and conditions, provided that: In any event, the use and
modification of Mistral Model and/or Derivatives made by or for Mistral AI
shall remain governed by the terms and conditions of this Agreement; You
include in any such Derivatives made by or for You prominent notices stating
that You modified the concerned Mistral Model; and Any terms and conditions
You impose on any third-party recipients relating to Derivatives made by or
for You shall neither limit such third-party recipients' use of the Mistral
Model or any Derivatives made by or for Mistral AI in accordance with the
Mistral AI Research License nor conflict with any of its terms and conditions.
## 3. Limitations
**3.1. Misrepresentation.** You must not misrepresent or imply, through any
means, that the Derivatives made by or for You and/or any modified version of
the Mistral Model You Distribute under your name and responsibility is an
official product of Mistral AI or has been endorsed, approved or validated by
Mistral AI, unless You are authorized by Us to do so in writing.
**3.2. Usage Limitation.** You shall only use the Mistral Models, Derivatives
(whether or not created by Mistral AI) and Outputs for Research Purposes.
## 4. Intellectual Property
**4.1. Trademarks.** No trademark licenses are granted under this Agreement,
and in connection with the Mistral Models, You may not use any name or mark
owned by or associated with Mistral AI or any of its affiliates, except (i) as
required for reasonable and customary use in describing and Distributing the
Mistral Models and Derivatives made by or for Mistral AI and (ii) for
attribution purposes as required by this Agreement.
**4.2. Outputs.** We claim no ownership rights in and to the Outputs. You are
solely responsible for the Outputs You generate and their subsequent uses in
accordance with this Agreement. Any Outputs shall be subject to the
restrictions set out in Section 3 of this Agreement.
**4.3. Derivatives.** By entering into this Agreement, You accept that any
Derivatives that You may create or that may be created for You shall be
subject to the restrictions set out in Section 3 of this Agreement.
## 5. Liability
**5.1. Limitation of liability.** In no event, unless required by applicable
law (such as deliberate and grossly negligent acts) or agreed to in writing,
shall Mistral AI be liable to You for damages, including any direct, indirect,
special, incidental, or consequential damages of any character arising as a
result of this Agreement or out of the use or inability to use the Mistral
Models and Derivatives (including but not limited to damages for loss of data,
loss of goodwill, loss of expected profit or savings, work stoppage, computer
failure or malfunction, or any damage caused by malware or security breaches),
even if Mistral AI has been advised of the possibility of such damages.
**5.2. Indemnification.** You agree to indemnify and hold harmless Mistral AI
from and against any claims, damages, or losses arising out of or related to
Your use or Distribution of the Mistral Models and Derivatives.
## 6. Warranty
**6.1. Disclaimer.** Unless required by applicable law or prior agreed to by
Mistral AI in writing, Mistral AI provides the Mistral Models and Derivatives
on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
express or implied, including, without limitation, any warranties or
conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. Mistral AI does not represent nor warrant that the Mistral
Models and Derivatives will be error-free, meet Your or any third party's
requirements, be secure or will allow You or any third party to achieve any
kind of result or generate any kind of content. You are solely responsible for
determining the appropriateness of using or Distributing the Mistral Models
and Derivatives and assume any risks associated with Your exercise of rights
under this Agreement.
## 7. Termination
**7.1. Term.** This Agreement is effective as of the date of your acceptance
of this Agreement or access to the concerned Mistral Models or Derivatives and
will continue until terminated in accordance with the following terms.
**7.2. Termination.** Mistral AI may terminate this Agreement at any time if
You are in breach of this Agreement. Upon termination of this Agreement, You
must cease to use all Mistral Models and Derivatives and shall permanently
delete any copy thereof. The following provisions, in their relevant parts,
will survive any termination or expiration of this Agreement, each for the
duration necessary to achieve its own intended purpose (e.g. the liability
provision will survive until the end of the applicable limitation
period):Sections 5 (Liability), 6(Warranty), 7 (Termination) and 8 (General
Provisions).
**7.3. Litigation.** If You initiate any legal action or proceedings against
Us or any other entity (including a cross-claim or counterclaim in a lawsuit),
alleging that the Model or a Derivative, or any part thereof, infringe upon
intellectual property or other rights owned or licensable by You, then any
licenses granted to You under this Agreement will immediately terminate as of
the date such legal action or claim is filed or initiated.
## 8. General provisions
**8.1. Governing laws.** This Agreement will be governed by the laws of
France, without regard to choice of law principles, and the UN Convention on
Contracts for the International Sale of Goods does not apply to this
Agreement.
**8.2. Competent jurisdiction.** The courts of Paris shall have exclusive
jurisdiction of any dispute arising out of this Agreement.
**8.3. Severability.** If any provision of this Agreement is held to be
invalid, illegal or unenforceable, the remaining provisions shall be
unaffected thereby and remain valid as if such provision had not been set
forth herein.
## 9. Definitions
"Agreement": means this Mistral AI Research License agreement governing the
access, use, and Distribution of the Mistral Models, Derivatives and Outputs.
"Derivative": means any (i) modified version of the Mistral Model (including
but not limited to any customized or fine-tuned version thereof), (ii) work
based on the Mistral Model, or (iii) any other derivative work thereof.
"Distribution", "Distributing", "Distribute" or "Distributed": means
supplying, providing or making available, by any means, a copy of the Mistral
Models and/or the Derivatives as the case may be, subject to Section 3 of this
Agreement.
"Mistral AI", "We" or "Us": means Mistral AI, a French société par actions
simplifiée registered in the Paris commercial registry under the number 952
418 325, and having its registered seat at 15, rue des Halles, 75001 Paris.
"Mistral Model": means the foundational large language model(s), and its
elements which include algorithms, software, instructed checkpoints,
parameters, source code (inference code, evaluation code and, if applicable,
fine-tuning code) and any other elements associated thereto made available by
Mistral AI under this Agreement, including, if any, the technical
documentation, manuals and instructions for the use and operation thereof.
"Research Purposes": means any use of a Mistral Model, Derivative, or Output
that is solely for (a) personal, scientific or academic research, and (b) for
non-profit and non-commercial purposes, and not directly or indirectly
connected to any commercial activities or business operations. For
illustration purposes, Research Purposes does not include (1) any usage of the
Mistral Model, Derivative or Output by individuals or contractors employed in
or engaged by companies in the context of (a) their daily tasks, or (b) any
activity (including but not limited to any testing or proof-of-concept) that
is intended to generate revenue, nor (2) any Distribution by a commercial
entity of the Mistral Model, Derivative or Output whether in return for
payment or free of charge, in any medium or form, including but not limited to
through a hosted or managed service (e.g. SaaS, cloud instances, etc.), or
behind a software layer.
"Outputs": means any content generated by the operation of the Mistral Models
or the Derivatives from a prompt (i.e., text instructions) provided by users.
For the avoidance of doubt, Outputs do not include any components of a Mistral
Models, such as any fine-tuned versions of the Mistral Models, the weights, or
parameters.
"You": means the individual or entity entering into this Agreement with
Mistral AI.
*Mistral AI processes your personal data below to provide the model and
enforce its license. If you are affiliated with a commercial entity, we may
also send you communications about our models. For more information on your
rights and data handling, please see our <a
href="https://mistral.ai/terms/">privacy policy</a>.*
extra_gated_fields:
First Name: text
Last Name: text
Country: country
Affiliation: text
Job title: text
I understand that I can only use the model, any derivative versions and their outputs for non-commercial research purposes: checkbox
I understand that if I am a commercial entity, I am not permitted to use or distribute the model internally or externally, or expose it in my own offerings without a commercial license: checkbox
I understand that if I upload the model, or any derivative version, on any platform, I must include the Mistral Research License: checkbox
I understand that for commercial use of the model, I can contact Mistral or use the Mistral AI API on la Plateforme or any of our cloud provider partners: checkbox
By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Mistral Privacy Policy: checkbox
geo: ip_location
extra_gated_description: >-
Mistral AI processes your personal data below to provide the model and enforce
its license. If you are affiliated with a commercial entity, we may also send
you communications about our models. For more information on your rights and
data handling, please see our <a href="https://mistral.ai/terms/">privacy
policy</a>.
extra_gated_button_content: Submit
library_name: vllm
Model Card for Mistral-Large-Instruct-2411
Mistral-Large-Instruct-2411 is an advanced dense Large Language Model (LLM) of 123B parameters with state-of-the-art reasoning, knowledge and coding capabilities extending Mistral-Large-Instruct-2407 with better Long Context, Function Calling and System Prompt.
Key features
- Multi-lingual by design: Dozens of languages supported, including English, French, German, Spanish, Italian, Chinese, Japanese, Korean, Portuguese, Dutch and Polish.
- Proficient in coding: Trained on 80+ coding languages such as Python, Java, C, C++, Javacsript, and Bash. Also trained on more specific languages such as Swift and Fortran.
- Agent-centric: Best-in-class agentic capabilities with native function calling and JSON outputting.
- Advanced Reasoning: State-of-the-art mathematical and reasoning capabilities.
- Mistral Research License: Allows usage and modification for non-commercial usages.
- Large Context: A large 128k context window.
- Robust Context Adherence: Ensures strong adherence for RAG and large context applications.
- System Prompt: Maintains strong adherence and support for more reliable system prompts.
System Prompt
We appreciate the feedback received from our community regarding our system prompt handling.
In response, we have implemented stronger support for system prompts.
To achieve optimal results, we recommend always including a system prompt that clearly outlines the bot's purpose, even if it is minimal.
Basic Instruct Template (V7)
<s>[SYSTEM_PROMPT] <system prompt>[/SYSTEM_PROMPT][INST] <user message>[/INST] <assistant response></s>[INST] <user message>[/INST]
Be careful with subtle missing or trailing white spaces!
Please make sure to use mistral-common as the source of truth
Usage
The model can be used with the following frameworks
vLLM
We recommend using this model with the vLLM library to implement production-ready inference pipelines.
Installation
Make sure you install vLLM >= v0.6.4.post1:
pip install --upgrade vllm
Also make sure you have mistral_common >= 1.5.0 installed:
pip install --upgrade mistral_common
You can also make use of a ready-to-go docker image or on the docker hub.
Server
We recommand that you use Mistral-Large-Instruct-2411 in a server/client setting.
- Spin up a server:
vllm serve mistralai/Mistral-Large-Instruct-2411 --tokenizer_mode mistral --config_format mistral --load_format mistral --tensor_parallel_size 8
Note: Running Mistral-Large-Instruct-2411 on GPU requires over 300 GB of GPU RAM.
- To ping the client you can use a simple Python snippet.
import requests
import json
from huggingface_hub import hf_hub_download
from datetime import datetime, timedelta
url = "http://<your-server>:8000/v1/chat/completions"
headers = {"Content-Type": "application/json", "Authorization": "Bearer token"}
model = "mistralai/Mistral-Large-Instruct-2411"
def load_system_prompt(repo_id: str, filename: str) -> str:
file_path = hf_hub_download(repo_id=repo_id, filename=filename)
with open(file_path, "r") as file:
system_prompt = file.read()
today = datetime.today().strftime("%Y-%m-%d")
yesterday = (datetime.today() - timedelta(days=1)).strftime("%Y-%m-%d")
model_name = repo_id.split("/")[-1]
return system_prompt.format(name=model_name, today=today, yesterday=yesterday)
SYSTEM_PROMPT = load_system_prompt(model, "SYSTEM_PROMPT.txt")
messages = [
{"role": "system", "content": SYSTEM_PROMPT + "\n\nThink step by step. You're a math genius."},
{
"role": "user",
"content": "Think of four random numbers. Then add, substract or multiply them so that the solution is 10. If it's not possible, say it."
},
]
data = {"model": model, "messages": messages}
response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json()["choices"][0]["message"]["content"])
# Sure, let's start by thinking of four random numbers. For example, let's take 3, 5, 2, and 1.
#
# Now, we need to find a combination of addition, subtraction, or multiplication that results in 10.
# Let's try:
# \[ 3 + 5 + 2 - 1 = 9 \]
# This doesn't work. Let's try another combination:
# \[ 3 \times 2 + 5 - 1 = 6 + 5 - 1 = 10 \]
# This works! So, with the numbers 3, 5, 2, and 1, we can achieve the result 10 by performing the operations \( 3 \times 2 + 5 - 1 \).
Offline
from vllm import LLM
from vllm.sampling_params import SamplingParams
from huggingface_hub import hf_hub_download
from datetime import datetime, timedelta
model_name = "mistralai/Mistral-Large-Instruct-2411"
def load_system_prompt(repo_id: str, filename: str) -> str:
file_path = hf_hub_download(repo_id=repo_id, filename=filename)
with open(file_path, 'r') as file:
system_prompt = file.read()
today = datetime.today().strftime('%Y-%m-%d')
yesterday = (datetime.today() - timedelta(days=1)).strftime('%Y-%m-%d')
model_name = repo_id.split("/")[-1]
return system_prompt.format(name=model_name, today=today, yesterday=yesterday)
SYSTEM_PROMPT = load_system_prompt(model_name, "SYSTEM_PROMPT.txt") + "\n\nThink step by step. You're a math genius."
user_prompt = "Without browsing the web, how many days ago was Mistral founded?"
messages = [
{
"role": "system",
"content": SYSTEM_PROMPT
},
{
"role": "user",
"content": user_prompt
},
]
# note that running this model on GPU requires over 300 GB of GPU RAM
llm = LLM(model=model_name, tokenizer_mode="mistral", tensor_parallel_size=8)
sampling_params = SamplingParams(max_tokens=512)
outputs = llm.chat(messages, sampling_params=sampling_params)
print(outputs[0].outputs[0].text)
# I don't have real-time web browsing capabilities or access to current data, but I can help you calculate the number of days based on the information I have.
#
#Mistral AI was founded in April 2023. To determine how many days ago that was from today's date, November 18, 2024, we need to calculate the total number of days between April 2023 and November 2024.
#
#Here's the step-by-step calculation:
#
#1. **Days from April 2023 to December 2023:**
# - April 2023: 30 days (April has 30 days)
# - May 2023: 31 days
# - June 2023: 30 days
# - July 2023: 31 days
# - August 2023: 31 days
# - September 2023: 30 days
# - October 2023: 31 days
# - November 2023: 30 days
# - December 2023: 31 days
#
# Total days in 2023 from April to December = 30 + 31 + 30 + 31 + 31 + 30 + 31 + 30 + 31 = 275 days
#
#2. **Days from January 2024 to November 18, 2024:**
# - January 2024: 31 days
# - February 2024: 29 days (2024 is a leap year)
# - March 2024: 31 days
# - April 2024: 30 days
# - May 2024: 31 days
# - June 2024: 30 days
# - July 2024: 31 days
# - August 2024: 31 days
# - September 2024: 30 days
# - October 2024: 31 days
# - November 2024 (up to the 18th): 18 days
#
# Total days in 2024 from January to November 18 = 31 + 29 + 31 + 30 + 31 + 30 + 31 + 31 + 30 + 31 + 18 = 323 days
#
#3. **Total days from April 2023 to November 18, 2024:**
# Total days = 275 days (2023) + 323 days (2024) = 598 days
#
#Therefore, Mistral AI was founded 598 days ago from today's date, November 18, 2024.
Improved Function Calling
Mistral-Large-2411 has much improved function calling capabilities that are fully supported
using mistral_common >= 1.5.0 and vLLM >= v0.6.4.post1.
Make sure to serve the model with the following flags in vLLM:
vllm serve mistralai/Pixtral-Large-Instruct-2411 --tokenizer_mode mistral --config_format mistral --load_format mistral --tensor-parallel-size 8 --tool-call-parser mistral --enable-auto-tool-choice
Example
import requests
import json
from huggingface_hub import hf_hub_download
from datetime import datetime, timedelta
url = "http://<your-server>:8000/v1/chat/completions"
headers = {"Content-Type": "application/json", "Authorization": "Bearer token"}
model = "mistralai/Mistral-Large-Instruct-2411"
def load_system_prompt(repo_id: str, filename: str) -> str:
file_path = hf_hub_download(repo_id=repo_id, filename=filename)
with open(file_path, "r") as file:
system_prompt = file.read()
today = datetime.today().strftime("%Y-%m-%d")
yesterday = (datetime.today() - timedelta(days=1)).strftime("%Y-%m-%d")
model_name = repo_id.split("/")[-1]
return system_prompt.format(name=model_name, today=today, yesterday=yesterday)
SYSTEM_PROMPT = load_system_prompt(model, "SYSTEM_PROMPT.txt")
tools = [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "The city to find the weather for, e.g. 'San Francisco'",
},
"state": {
"type": "string",
"description": "The state abbreviation, e.g. 'CA' for California",
},
"unit": {
"type": "string",
"description": "The unit for temperature",
"enum": ["celsius", "fahrenheit"],
},
},
"required": ["city", "state", "unit"],
},
},
},
{
"type": "function",
"function": {
"name": "rewrite",
"description": "Rewrite a given text for improved clarity",
"parameters": {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "The input text to rewrite",
}
},
},
},
},
]
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
{
"role": "user",
"content": "Could you please make the below article more concise?\n\nOpenAI is an artificial intelligence research laboratory consisting of the non-profit OpenAI Incorporated and its for-profit subsidiary corporation OpenAI Limited Partnership.",
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "bbc5b7ede",
"type": "function",
"function": {
"name": "rewrite",
"arguments": '{"text": "OpenAI is an artificial intelligence research laboratory consisting of the non-profit OpenAI Incorporated and its for-profit subsidiary corporation OpenAI Limited Partnership."}',
},
}
],
},
{
"role": "tool",
"content": '{"action":"rewrite","outcome":"OpenAI is a FOR-profit company."}',
"tool_call_id": "bbc5b7ede",
"name": "rewrite",
},
{
"role": "assistant",
"content": "---\n\nOpenAI is a FOR-profit company.",
},
{
"role": "user",
"content": "Can you tell me what the temperature will be in Dallas, in Fahrenheit?",
},
]
data = {"model": model, "messages": messages, "tools": tools}
response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json()["choices"][0]["message"]["tool_calls"])
# [{'id': '8PdihwL6d', 'type': 'function', 'function': {'name': 'get_current_weather', 'arguments': '{"city": "Dallas", "state": "TX", "unit": "fahrenheit"}'}}]
The Mistral AI Team
Albert Jiang, Alexandre Sablayrolles, Alexis Tacnet, Alok Kothari, Antoine Roux, Arthur Mensch, Audrey Herblin-Stoop, Augustin Garreau, Austin Birky, Bam4d, Baptiste Bout, Baudouin de Monicault, Blanche Savary, Carole Rambaud, Caroline Feldman, Devendra Singh Chaplot, Diego de las Casas, Diogo Costa, Eleonore Arcelin, Emma Bou Hanna, Etienne Metzger, Gaspard Blanchet, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Harizo Rajaona, Henri Roussez, Hichem Sattouf, Ian Mack, Jean-Malo Delignon, Jessica Chudnovsky, Justus Murke, Kartik Khandelwal, Lawrence Stewart, Louis Martin, Louis Ternon, Lucile Saulnier, Lélio Renard Lavaud, Margaret Jennings, Marie Pellat, Marie Torelli, Marie-Anne Lachaux, Marjorie Janiewicz, Mickaël Seznec, Nicolas Schuhl, Niklas Muhs, Olivier de Garrigues, Patrick von Platen, Paul Jacob, Pauline Buche, Pavan Kumar Reddy, Perry Savas, Pierre Stock, Romain Sauvestre, Sagar Vaze, Sandeep Subramanian, Saurabh Garg, Sophia Yang, Szymon Antoniak, Teven Le Scao, Thibault Schueller, Thibaut Lavril, Thomas Wang, Théophile Gervet, Timothée Lacroix, Valera Nemychnikova, Wendy Shang, William El Sayed, William Marshall