telegram-bot-api
axolotl
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telegram-bot-api | axolotl | |
---|---|---|
26 | 29 | |
2,789 | 5,641 | |
4.2% | 23.6% | |
8.7 | 9.8 | |
25 days ago | 4 days ago | |
C++ | Python | |
Boost Software License 1.0 | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
telegram-bot-api
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Hide sender name
Is not that hard, they have amazing documentation about it: https://core.telegram.org/bots
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Telegram OAuth Authorization for Your Site
You can make authorization via Telegram another way. It works. But today we want to do the classic OAuth Authorization. Before you begin, you need to create a Telegram bot and obtain your bot token. You can do this in @BotFather in Telegram. For more information on initiating a bot, read the Telegram Bot API documentation: https://core.telegram.org/bots
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Is my idea possible to implement?
Absolutely possible. Here's the github page to the Telegram bot API. You would just need to check for incoming messages, check the body of the message for a word or phrase, and then send a message back with a photo or gif and an encouraging message.
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How I built an AI-based Telegram bot in 21 minutes with Make and OpenAI
Creating a Telegram bot is fun: there's no website, no sign up, no forms — you just use a... bot. Yes, a bot that creates bots. It's called the BotFather 😂
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A simple forwarder from WhatsApp to Telegram written in Go
Telegram has a bot API server that provides API to control the bots and get updates. Their own instance has some restrictions like you cannot download files bigger than 20MB. So, using a self hosted bot API server, you can overcome those limits.
- Serverless + JS: Um bot de web-scrapping diário
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From BotFather to 'Hello World'
General Bot Platform Overview
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Não consigo abrir api.telegram.org na Claro
$ curl -4 -v https://api.telegram.org * Trying 149.154.167.220:443... * TCP_NODELAY set * Connected to api.telegram.org (149.154.167.220) port 443 (#0) * ALPN, offering h2 * ALPN, offering http/1.1 * successfully set certificate verify locations: * CAfile: /etc/ssl/certs/ca-certificates.crt CApath: /etc/ssl/certs * TLSv1.3 (OUT), TLS handshake, Client hello (1): * TLSv1.3 (IN), TLS handshake, Server hello (2): * TLSv1.3 (IN), TLS handshake, Encrypted Extensions (8): * TLSv1.3 (IN), TLS handshake, Certificate (11): * TLSv1.3 (IN), TLS handshake, CERT verify (15): * TLSv1.3 (IN), TLS handshake, Finished (20): * TLSv1.3 (OUT), TLS change cipher, Change cipher spec (1): * TLSv1.3 (OUT), TLS handshake, Finished (20): * SSL connection using TLSv1.3 / TLS_AES_256_GCM_SHA384 * ALPN, server accepted to use h2 * Server certificate: * subject: CN=api.telegram.org * start date: Mar 24 15:21:45 2022 GMT * expire date: Apr 25 15:21:45 2023 GMT * subjectAltName: host "api.telegram.org" matched cert's "api.telegram.org" * issuer: C=US; ST=Arizona; L=Scottsdale; O=GoDaddy.com, Inc.; OU=http://certs.godaddy.com/repository/; CN=Go Daddy Secure Certificate Authority - G2 * SSL certificate verify ok. * Using HTTP2, server supports multi-use * Connection state changed (HTTP/2 confirmed) * Copying HTTP/2 data in stream buffer to connection buffer after upgrade: len=0 * Using Stream ID: 1 (easy handle 0x555fdb2de2f0) > GET / HTTP/2 > Host: api.telegram.org > user-agent: curl/7.68.0 > accept: */* > * TLSv1.3 (IN), TLS handshake, Newsession Ticket (4): * TLSv1.3 (IN), TLS handshake, Newsession Ticket (4): * old SSL session ID is stale, removing * Connection state changed (MAX_CONCURRENT_STREAMS == 128)! < HTTP/2 302 < server: nginx/1.18.0 < date: Tue, 18 Oct 2022 00:00:24 GMT < content-type: text/html < content-length: 145 < location: https://core.telegram.org/bots < strict-transport-security: max-age=31536000; includeSubDomains; preload < access-control-allow-origin: * < access-control-allow-methods: GET, POST, OPTIONS < access-control-expose-headers: Content-Length,Content-Type,Date,Server,Connection < 302 Found 302 Found nginx/1.18.0 * Connection #0 to host api.telegram.org left intact
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Can anyone teach me how to make these?
It's done via bots, which let you add clickable options to posts. Here's an FAQ on bots: https://core.telegram.org/bots
- Desarrollando un Bot para Telegram
axolotl
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Ask HN: Most efficient way to fine-tune an LLM in 2024?
The approach I see used is axolotl with QLoRA using cloud GPUs which can be quite cheap.
https://github.com/OpenAccess-AI-Collective/axolotl
- FLaNK AI - 01 April 2024
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LoRA from Scratch implementation for LLM finetuning
https://github.com/OpenAccess-AI-Collective/axolotl
- Optimized Triton Kernels for full fine tunes
- Axolotl
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Let’s Collaborate to Build a High-Quality, Open-Source Dataset for LLMs!
One option is to look at what Axolotl uses. They have a list of different dataset formats that they support. They're mostly in JSON with specific field names, so you could start putting a dataset together with a text editor or a JSON editor.
- Axolotl: Streamline fine-tuning of AI models
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Dataset Creation Tools?
You can save that overall set into a json file and load it up as training data in whatever you're using. I'm using axolotl for it at the moment. Though a GUI based option is probably best for the first couple of tries until you get a feel for the options.
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Progress on Reproducing Phi-1/1.5
Looking forward to the results! If it turns out the dataset is reproducible, then it might be a good candidate for ReLora training on axolotl!
What are some alternatives?
aiogram - aiogram is a modern and fully asynchronous framework for Telegram Bot API written in Python using asyncio
gpt-llm-trainer
Gotify - A simple server for sending and receiving messages in real-time per WebSocket. (Includes a sleek web-ui)
signal-cli - signal-cli provides an unofficial commandline, JSON-RPC and dbus interface for the Signal messenger.
python-telegram-bot - We have made you a wrapper you can't refuse
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
Telethon - Pure Python 3 MTProto API Telegram client library, for bots too!
LMFlow - An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
Signal-Desktop - A private messenger for Windows, macOS, and Linux.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI