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Average Ratings 0 Ratings
Description
Falcon-40B is a causal decoder-only model consisting of 40 billion parameters, developed by TII and trained on 1 trillion tokens from RefinedWeb, supplemented with carefully selected datasets. It is distributed under the Apache 2.0 license.
Why should you consider using Falcon-40B?
This model stands out as the leading open-source option available, surpassing competitors like LLaMA, StableLM, RedPajama, and MPT, as evidenced by its ranking on the OpenLLM Leaderboard.
Its design is specifically tailored for efficient inference, incorporating features such as FlashAttention and multiquery capabilities.
Moreover, it is offered under a flexible Apache 2.0 license, permitting commercial applications without incurring royalties or facing restrictions.
It's important to note that this is a raw, pretrained model and is generally recommended to be fine-tuned for optimal performance in most applications. If you need a version that is more adept at handling general instructions in a conversational format, you might want to explore Falcon-40B-Instruct as a potential alternative.
Description
Timestral represents a suite of time-series foundation models along with a Python inference toolkit designed to create multivariate probabilistic forecasts based on historical data sequences. It comes in four different model sizes—5M, 28M, 123M, and 209M parameters—that are capable of handling past-only, known-future, and categorical covariates, providing quantile forecasts while accommodating context windows as extensive as 32,768 time steps. Users have the flexibility to load pretrained weights either from the Hugging Face Hub or directly from local files, enabling them to perform inference on both CPU and GPU. Such forecasts can be seamlessly integrated into various applications, including monitoring systems, capacity planning, energy management, supply chain logistics, financial risk assessment, or maintenance operations. Furthermore, Timestral offers zero-shot forecasting capabilities and can be tailored to specific domain data through the Mistral Forge. This package is primarily aimed at data scientists, machine learning engineers, and collaborative teams focused on developing robust forecasting solutions; the repository code is licensed under Apache 2.0, while the model weights are governed by a separate Modified MIT license. With its comprehensive features, Timestral is positioned to significantly enhance the accuracy and efficiency of predictive analytics in numerous industries.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
C
Yes
CSS
Yes
Clojure
Yes
Elixir
Yes
F#
Yes
HTML
Yes
Java
Yes
JavaScript
Yes
Julia
Yes
Kotlin
Yes
Integrations
C
No
CSS
No
Clojure
No
Elixir
No
F#
No
HTML
No
Java
No
JavaScript
No
Julia
No
Kotlin
No
Pricing Details
Free
Open source
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Technology Innovation Institute (TII)
Founded
2018
Country
United Arab Emirates
Website
www.tii.ae/
Vendor Details
Company Name
Mistral AI
Founded
2023
Country
France
Website
github.com/mistralai/timestral