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@@ -12,7 +12,7 @@ cover: ai-chatbots.webp
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- [:material-account-cash: Surveillance Capitalism](basics/common-threats.md#surveillance-as-a-business-model){ .pg-brown }
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- [:material-close-outline: Censorship](basics/common-threats.md#avoiding-censorship){ .pg-blue-gray }
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Since the release of ChatGPT in 2022, interactions with Large Language Models (LLMs) have become increasingly common. LLMs can help us write better, understand unfamiliar subjects, or answer a wide range of questions. They can statistically predict the next word based on a vast amount of data scraped from the web.
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The use of **AI chat**, also known as Large Language Models (LLMs), has become increasingly common since the release of ChatGPT in 2022. LLMs can help us write better, understand unfamiliar subjects, or answer a wide range of questions. They work by statistically predicting the next word in their responses based on a vast amount of data scraped from the web.
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## Privacy Concerns About LLMs
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@@ -42,7 +42,7 @@ To run AI locally, you need both an AI model and an AI client.
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### Choosing a Model
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There are many permissively licensed models available to download. [Hugging Face](https://huggingface.co/models) is a platform that lets you browse, research, and download models in common formats like [GGUF](https://huggingface.co/docs/hub/en/gguf). Companies that provide good open-weights models include big names like Mistral, Meta, Microsoft, and Google. However, there are also many community models and 'fine-tunes' available. As mentioned above, quantized models offer the best balance between model quality and performance for those using consumer-grade hardware.
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There are many permissively licensed models available to download. [Hugging Face](https://huggingface.co/models) is a platform that lets you browse, research, and download models in common formats like [GGUF](https://huggingface.co/docs/hub/en/gguf). Companies that provide good open-weights models include big names like Mistral, Meta, Microsoft, and Google. However, there are also many community models and [fine-tuned](https://en.wikipedia.org/wiki/Fine-tuning_\(deep_learning\)) models available. As mentioned above, quantized models offer the best balance between model quality and performance for those using consumer-grade hardware.
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To help you choose a model that fits your needs, you can look at leaderboards and benchmarks. The most widely-used leaderboard is the community-driven [LM Arena](https://lmarena.ai). Additionally, the [OpenLLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) focuses on the performance of open-weights models on common benchmarks like [MMLU-Pro](https://arxiv.org/abs/2406.01574). There are also specialized benchmarks which measure factors like [emotional intelligence](https://eqbench.com), ["uncensored general intelligence"](https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard), and [many others](https://www.nebuly.com/blog/llm-leaderboards).
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@@ -63,7 +63,7 @@ To help you choose a model that fits your needs, you can look at leaderboards an
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{align=right}
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Kobold.cpp is an AI client that runs locally on your Windows, Mac, or Linux computer. It's an excellent choice if you are looking for heavy customization and tweaking, such as for role-playing purposes.
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**Kobold.cpp** is an AI client that runs locally on your Windows, Mac, or Linux computer. It's an excellent choice if you are looking for heavy customization and tweaking, such as for role-playing purposes.
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In addition to supporting a large range of text models, Kobold.cpp also supports image generators such as [Stable Diffusion](https://stability.ai/stable-image) and automatic speech recognition tools such as [Whisper](https://github.com/ggerganov/whisper.cpp).
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@@ -83,7 +83,7 @@ In addition to supporting a large range of text models, Kobold.cpp also supports
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</div>
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<div class="admonition note" markdown>
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<div class="admonition info" markdown>
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<p class="admonition-title">Compatibility Issues</p>
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Kobold.cpp might not run on computers without AVX/AVX2 support.
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@@ -98,7 +98,7 @@ Kobold.cpp allows you to modify parameters such as the AI model temperature and
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{align=right}
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Ollama is a command-line AI assistant that is available on macOS, Linux, and Windows. Ollama is a great choice if you're looking for an AI client that's easy-to-use, widely compatible, and fast due to its use of inference and other techniques. It also doesn't involve any manual setup.
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**Ollama** is a command-line AI assistant that is available on macOS, Linux, and Windows. Ollama is a great choice if you're looking for an AI client that's easy-to-use, widely compatible, and fast due to its use of inference and other techniques. It also doesn't involve any manual setup.
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In addition to supporting a wide range of text models, Ollama also supports [LLaVA](https://github.com/haotian-liu/LLaVA) models and has experimental support for Meta's [Llama vision capabilities](https://huggingface.co/blog/llama32#what-is-llama-32-vision).
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@@ -124,9 +124,9 @@ Ollama simplifies the process of setting up a local AI chat by downloading the A
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<div class="admonition recommendation" markdown>
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{align=right}
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{align=right}
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Llamafile is a lightweight single-file executable that allows users to run LLMs locally on their own computers without any setup involved. It is [backed by Mozilla](https://hacks.mozilla.org/2023/11/introducing-llamafile) and available on Linux, macOS, and Windows.
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**Llamafile** is a lightweight, single-file executable that allows users to run LLMs locally on their own computers without any setup involved. It is [backed by Mozilla](https://hacks.mozilla.org/2023/11/introducing-llamafile) and available on Linux, macOS, and Windows.
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Llamafile also supports LLaVA. However, it doesn't support speech recognition or image generation.
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@@ -138,7 +138,9 @@ Llamafile also supports LLaVA. However, it doesn't support speech recognition or
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<details class="downloads" markdown>
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<summary>Downloads</summary>
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- [:fontawesome-solid-desktop: Desktop](https://github.com/Mozilla-Ocho/llamafile#quickstart)
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- [:fontawesome-brands-windows: Windows](https://github.com/Mozilla-Ocho/llamafile#quickstart)
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- [:simple-apple: macOS](https://github.com/Mozilla-Ocho/llamafile#quickstart)
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- [:simple-linux: Linux](https://github.com/Mozilla-Ocho/llamafile#quickstart)
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</details>
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@@ -161,7 +163,7 @@ To check the authenticity and safety of the model, look for:
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- Community reviews and usage statistics
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- A "Safe" badge next to the model file (Hugging Face only)
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- Matching checksums[^1]
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- On Hugging Face, you can find the hash by clicking on a model file and looking for the **Copy SHA256** button below it. You should compare this checksum with the one from the model file you downloaded.
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- On Hugging Face, you can find the hash by clicking on a model file and looking for the **Copy SHA256** button below it. You should compare this checksum with the one from the model file you downloaded.
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A downloaded model is generally safe if it satisfies all the above checks.
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@@ -171,11 +173,11 @@ Please note we are not affiliated with any of the projects we recommend. In addi
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### Minimum Requirements
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- Must be open-source.
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- Must be open source.
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- Must not transmit personal data, including chat data.
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- Must be multi-platform.
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- Must not require a GPU.
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- Must support GPU-powered fast inference.
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- Must support GPU-powered, fast inference.
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- Must not require an internet connection.
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### Best-Case
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- Should have a built-in model downloader option.
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- The user should be able to modify the LLM parameters, such as its system prompt or temperature.
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\*[LLaVA]: Large Language and Vision Assistant (multimodal AI model)
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\*[LLM]: Large Language Model (AI model such as ChatGPT)
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\*[LLMs]: Large Language Models (AI models such as ChatGPT)
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\*[open-weights models]: AI models that anyone can download and use, but the underlying training data and/or algorithms for them are proprietary.
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\*[system prompt]: The general instructions given by a human to guide how an AI chat should operate.
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\*[temperature]: A parameter used in AI models to control the level of randomness and creativity in the generated text.
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[^1]: A file checksum is a type of anti-tampering fingerprint. A developer usually provides a checksum in a text file that can be downloaded separately, or on the download page itself. Verifying that the checksum of the file you downloaded matches the one provided by the developer helps ensure that the file is genuine and wasn't tampered with in transit. You can use commands like `sha256sum` on Linux and macOS, or `certutil -hashfile file SHA256` on Windows to generate the downloaded file's checksum.
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@@ -19,7 +19,7 @@ description: Електронна пошта за своєю природою є
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## Що таке стандарт Web Key Directory?
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Стандарт Web Key Directory (WKD) дозволяє поштовим клієнтам отримувати ключ OpenPGP для інших поштових скриньок, навіть тих, що розміщені в іншого провайдера. Поштові клієнти, які підтримують WKD, запитують у сервера одержувача ключ на основі доменного імені адреси електронної пошти. Наприклад, якщо ви надішлете електронною поштою `jonah@privacyguides.org`, ваш поштовий клієнт запитає `privacyguides.org` про ключ OpenPGP Джона, і якщо `privacyguides.org` має ключ для цього облікового запису, ваше повідомлення буде автоматично зашифровано.
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The [Web Key Directory (WKD)](https://wiki.gnupg.org/WKD) standard allows email clients to discover the OpenPGP key for other mailboxes, even those hosted on a different provider. Поштові клієнти, які підтримують WKD, запитують у сервера одержувача ключ на основі доменного імені адреси електронної пошти. Наприклад, якщо ви надішлете електронною поштою `jonah@privacyguides.org`, ваш поштовий клієнт запитає `privacyguides.org` про ключ OpenPGP Джона, і якщо `privacyguides.org` має ключ для цього облікового запису, ваше повідомлення буде автоматично зашифровано.
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На додачу до [рекомендованих поштових клієнтів](../email-clients.md), які підтримують WKD, деякі провайдери вебпошти також підтримують WKD. Чи буде *ваш власний ключ* опублікований у WKD для використання іншими, залежить від конфігурації вашого домену. Якщо ви використовуєте [провайдера електронної пошти](../email.md#openpgp-compatible-services), який підтримує WKD, наприклад, Proton Mail або Mailbox.org, вони можуть опублікувати для вас ваш ключ OpenPGP на своєму домені.
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@@ -34,7 +34,7 @@ In addition to (or instead of) an email provider recommended here, you may wish
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## Сервіси, сумісні з OpenPGP
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These providers natively support OpenPGP encryption/decryption and the [Web Key Directory standard](basics/email-security.md#what-is-the-web-key-directory-standard), allowing for provider-agnostic E2EE emails. Наприклад, користувач Proton Mail може надіслати повідомлення E2EE користувачеві Mailbox.org, або ви можете отримувати сповіщення, зашифровані за допомогою OpenPGP, від інтернет-сервісів, які його підтримують.
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These providers natively support OpenPGP encryption/decryption and the [Web Key Directory (WKD) standard](basics/email-security.md#what-is-the-web-key-directory-standard), allowing for provider-agnostic E2EE emails. Наприклад, користувач Proton Mail може надіслати повідомлення E2EE користувачеві Mailbox.org, або ви можете отримувати сповіщення, зашифровані за допомогою OpenPGP, від інтернет-сервісів, які його підтримують.
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<div class="grid cards" markdown>
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@@ -107,7 +107,7 @@ Proton Mail має [шифрування з нульовим доступом](h
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#### :material-check:{ .pg-green } Шифрування електронної пошти
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Proton Mail має [інтегроване OpenPGP шифрування](https://proton.me/support/how-to-use-pgp) у своїй електронній пошті. Електронні листи на інші акаунти Proton Mail шифруються автоматично, а шифрування на адреси, що не належать до Proton Mail, за допомогою ключа OpenPGP можна легко ввімкнути в налаштуваннях вашого акаунта. Proton also supports automatic external key discovery with [Web Key Directory (WKD)](https://wiki.gnupg.org/WKD). This means that emails sent to other providers which use WKD will be automatically encrypted with OpenPGP as well, without the need to manually exchange public PGP keys with your contacts. They also allow you to [encrypt messages to non-Proton Mail addresses without OpenPGP](https://proton.me/support/password-protected-emails), without the need for them to sign up for a Proton Mail account.
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Proton Mail має [інтегроване OpenPGP шифрування](https://proton.me/support/how-to-use-pgp) у своїй електронній пошті. Електронні листи на інші акаунти Proton Mail шифруються автоматично, а шифрування на адреси, що не належать до Proton Mail, за допомогою ключа OpenPGP можна легко ввімкнути в налаштуваннях вашого акаунта. Proton also supports automatic external key discovery with WKD. This means that emails sent to other providers which use WKD will be automatically encrypted with OpenPGP as well, without the need to manually exchange public PGP keys with your contacts. They also allow you to [encrypt messages to non-Proton Mail addresses without OpenPGP](https://proton.me/support/password-protected-emails), without the need for them to sign up for a Proton Mail account.
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Proton Mail also publishes the public keys of Proton accounts via HTTP from their WKD. Це дозволяє людям, які не користуються Proton Mail, легко знайти OpenPGP ключі акаунтів Proton Mail для незалежного від провайдерів E2EE. This only applies to email addresses ending in one of Proton's own domains, like @proton.me. If you use a custom domain, you must [configure WKD](./basics/email-security.md#what-is-the-web-key-directory-standard) separately.
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@@ -164,7 +164,7 @@ However, [Open-Exchange](https://en.wikipedia.org/wiki/Open-Xchange), the softwa
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Mailbox.org has [integrated encryption](https://kb.mailbox.org/en/private/e-mail-article/send-encrypted-e-mails-with-guard) in their webmail, which simplifies sending messages to people with public OpenPGP keys. They also allow [remote recipients to decrypt an email](https://kb.mailbox.org/en/private/e-mail-article/my-recipient-does-not-use-pgp) on Mailbox.org's servers. Ця функція корисна, коли віддалений одержувач не має OpenPGP і не може розшифрувати копію листа у власній поштовій скриньці.
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Mailbox.org також підтримує виявлення публічних ключів через HTTP з їхнього [каталогу веб-ключів (WKD)](https://wiki.gnupg.org/WKD). Це дозволяє людям за межами Mailbox.org легко знаходити ключі OpenPGP акаунтів Mailbox.org для незалежного від провайдерів E2EE. This only applies to email addresses ending in one of Mailbox.org's own domains, like @mailbox.org. If you use a custom domain, you must [configure WKD](./basics/email-security.md#what-is-the-web-key-directory-standard) separately.
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Mailbox.org also supports the discovery of public keys via HTTP from their WKD. Це дозволяє людям за межами Mailbox.org легко знаходити ключі OpenPGP акаунтів Mailbox.org для незалежного від провайдерів E2EE. This only applies to email addresses ending in one of Mailbox.org's own domains, like @mailbox.org. If you use a custom domain, you must [configure WKD](./basics/email-security.md#what-is-the-web-key-directory-standard) separately.
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#### :material-information-outline:{ .pg-blue } Деактивація облікового запису
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- Encrypts all account data (Contacts, Calendars, etc.) at rest with zero-access encryption.
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- Integrated webmail E2EE/PGP encryption provided as a convenience.
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- Support for [WKD](https://wiki.gnupg.org/WKD) to allow improved discovery of public OpenPGP keys via HTTP. GnuPG users can get a key by typing: `gpg --locate-key example_user@example.com`
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- Support for WKD to allow improved discovery of public OpenPGP keys via HTTP. GnuPG users can get a key by typing: `gpg --locate-key example_user@example.com`
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- Support for a temporary mailbox for external users. This is useful when you want to send an encrypted email, without sending an actual copy to your recipient. These emails usually have a limited lifespan and then are automatically deleted. They also don't require the recipient to configure any cryptography like OpenPGP.
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- Availability of the email provider's services via an [onion service](https://en.wikipedia.org/wiki/.onion).
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- [Sub-addressing](https://en.wikipedia.org/wiki/Email_address#Sub-addressing) support.
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@@ -356,7 +356,7 @@ We [recommend](dns.md#recommended-providers) a number of encrypted DNS servers b
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<div class="grid cards" markdown>
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- { .twemoji loading=lazy } [Kobold.cpp](ai-chat.md#koboldcpp)
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- { .twemoji loading=lazy } [Llamafile](ai-chat.md#llamafile)
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- { .twemoji loading=lazy } [Llamafile](ai-chat.md#llamafile)
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- { .twemoji loading=lazy } [Ollama (CLI)](ai-chat.md#ollama-cli)
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</div>
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