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MaziyarPanahi/Mistral-Large-Instruct-2407-GGUF contains GGUF format model files for mistralai/Mistral-Large-Instruct-2407. GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. 🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.

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- Model creator: mistralai - Original model: mistralai/Mistral-Large-Instruct-2411 GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF:

Text generation
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- Model creator: mistralai - Original model: mistralai/Mistral-Nemo-Instruct-2407 GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF:

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- Model creator: mistralai - Original model: mistralai/Mistral-Small-24B-Instruct-2501 GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF:

Text generation
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- Model creator: mrfakename - Original model: mrfakename/mistral-small-3.1-24b-instruct-2503-hf GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF:

Text generation
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- Model creator: mistralai - Original model: mistralai/Mistral-Small-Instruct-2409 GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Here is an incomplete list of clients and libraries that are known to support GGUF:

Text generation
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On April 10th, @MistralAI released a model named "Mixtral 8x22B," an 176B MoE via magnet link (torrent): - 141B MoE with ~35B active - Context length of 65k tokens - The base model can be fine-tuned - Requires ~260GB VRAM in fp16, 73GB in int4 - Licensed under Apache 2.0, according to their Discord - Available on @huggingface (community) - Utilizes a tokenizer similar to previous models The GGUF and quantized models here are based on v2ray/Mixtral-8x22B-v0.1 model

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