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AccueilLLMsChatMeta Llama 3.1 8B Instruct GGUF

Meta Llama 3.1 8B Instruct GGUF

par lmstudio-community

Open source · 91k downloads · 256 likes

3.0
(256 avis)ChatAPI & Local
À propos

Le modèle Meta Llama 3.1 8B Instruct GGUF est une version optimisée et quantifiée du modèle Llama 3.1 8B, spécialement conçue pour des tâches d'instruction et de conversation. Il excelle dans une grande variété d'applications, allant de la génération de texte à la réponse à des questions complexes, en passant par des tâches multilingues grâce à ses améliorations significatives par rapport à ses prédécesseurs. Son contexte étendu de 128 000 tokens lui permet de traiter des documents longs ou des échanges prolongés avec cohérence. Ce modèle se distingue par ses performances de pointe en open source, sa polyvalence et sa capacité à s'adapter à des cas d'usage variés, tout en restant accessible grâce à sa version quantifiée optimisée pour une exécution locale efficace.

Documentation

💫 Community Model> Llama 3.1 8B Instruct by Meta

👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord.

Model creator: meta-llama
Original model: Meta-Llama-3.1-8B-Instruct
GGUF quantization: provided by bartowski based on llama.cpp release b3472

Important: Requires LM Studio version 0.2.29, available now here!

Model Summary:

Llama 3.1 is an update to the previously released family of Llama 3 models. It has improved performance across the board, especially in multilingual tasks.
It is the current state of the art for open source and can be used for basically any task you throw at it.

Prompt Template:

Choose the 'Llama 3' preset in your LM Studio.

Under the hood, the model will see a prompt that's formatted like so:

SQL
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Technical Details

Llama 3.1 features an improved 128k context window.

It has been trained on 15T tokens, including 25 million synthetically generated samples.

For more details, check their blog post here

Special thanks

🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

🙏 Special thanks to Kalomaze for his dataset (linked here) that was used for calculating the imatrix for these quants, which improves the overall quality!

Disclaimers

LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models. LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.

Liens & Ressources
Spécifications
CatégorieChat
AccèsAPI & Local
LicenceOpen Source
TarificationOpen Source
Paramètres8B parameters
Note
3.0

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