Github LLMs

با عرض سلام در راستاي ادامه تحقيقات مشترك سعي داريم از ١ ام دي ماه روي حوزه ي LLM مدل ها كار كنيم. حدودا ٤ نفر براي كار زير نياز داريم. BioPars: a pre-trained biomedical large language model for persian biomedical text mining. ١- مراحل اوليه: جمع اوري متن هاي فارسي بيولوژيكي از منابع (...) ٢- پيش پردازش متن ها و تميز كردن متن ها ٣- اموزش ترنسفورمرها ي مورد نظر ٤- استفاده از بردارها ي اموزش داده شده در سه تسك (...) دوستاني كه مايل به مشاركت هستن مي تونين تا ١ دي بهم اطلاع بدن. هزينه سرور به ازاي هر ساعت ١.٢ دلار مي باشد. و حدود ٢ هزار ساعت براي اموزش مدل زباني نياز ميباشد. هزينه به ترتيب براي نفرات علاوه بر انجام تسك ها به صورت زير مي باشد. 🔺نفر سوم ٣٠ ميليون 🔹نفر چهارم ٢٥ ميليون 🔺نفر پنجم ٢٠ ميليون 🔹نفر سوم ١٥ ميليون ث نفرات اول و دوم: رامین موسی و سروش سرابی. @Raminmousa @Machine_learn https://t.me/+SP9l58Ta_zZmYmY0

⚡️ MobileLLM 🟢MobileLLM-125M. 30 Layers, 9 Attention Heads, 3 KV Heads. 576 Token Dimension; 🟢MobileLLM-350M. 32 Layers, 15 Attention Heads, 5 KV Heads. 960 Token Dimension; 🟢MobileLLM-600M. 40 Layers, 18 Attention Heads, 6 KV Heads. 1152 Token Dimension; 🟢MobileLLM-1B. 54 Layers, 20 Attention Heads, 5 KV Heads. 1280 Token Dimension; 🟡Arxiv 🖥GitHub @Machine_learn

Welcome to Ollama's Prompt Engineering Interactive Tutorial 🔗 Github https://t.me/deep_learning_proj

LLM-based agents for Software Engineering "Large Language Model-Based Agents for Software Engineering: A Survey". https://github.com/FudanSELab/Agent4SE-Paper-List. https://t.me/deep_learning_proj

https://github.com/andrewyng/aisuite #LLMs https://t.me/deep_learning_proj

📖 LLM-Agent-Paper-List is a repository of papers on the topic of agents based on large language models (LLM)! The papers are divided into categories such as LLM agent architectures, autonomous LLM agents, reinforcement learning (RL), natural language processing methods, multimodal approaches and tools for developing LLM agents, and more. 🖥 Github https://t.me/deep_learning_proj

🌟 Zamba2-Instruct В семействе 2 модели: 🟢Zamba2-1.2B-instruct; 🟠Zamba2-2.7B-instruct. # Clone repo git clone https://github.com/Zyphra/transformers_zamba2.git cd transformers_zamba2 # Install the repository & accelerate: pip install -e . pip install accelerate # Inference: from transformers import AutoTokenizer, AutoModelForCausalLM import torch tokenizer = AutoTokenizer.from_pretrained("Zyphra/Zamba2-2.7B-instruct") model = AutoModelForCausalLM.from_pretrained("Zyphra/Zamba2-2.7B-instruct", device_map="cuda", torch_dtype=torch.bfloat16) user_turn_1 = "user_prompt1." assistant_turn_1 = "assistant_prompt." user_turn_2 = "user_prompt2." sample = [{'role': 'user', 'content': user_turn_1}, {'role': 'assistant', 'content': assistant_turn_1}, {'role': 'user', 'content': user_turn_2}] chat_sample = tokenizer.apply_chat_template(sample, tokenize=False) input_ids = tokenizer(chat_sample, return_tensors='pt', add_special_tokens=False).to("cuda") outputs = model.generate(**input_ids, max_new_tokens=150, return_dict_in_generate=False, output_scores=False, use_cache=True, num_beams=1, do_sample=False) print((tokenizer.decode(outputs[0]))) 🖥GitHub https://t.me/deep_learning_proj

🔥 NVIDIA silently release a Llama 3.1 70B fine-tune that outperforms GPT-4o and Claude Sonnet 3.5 Llama 3.1 Nemotron 70B Instruct a further RLHFed model on huggingface https://huggingface.co/collections/nvidia/llama-31-nemotron-70b-670e93cd366feea16abc13d8 ✅https://t.me/deep_learning_proj

Crawl 4 AI Crawl4AI: Open-source LLM Friendly Web Crawler & Scrapper Creator: UncleCode Stars ⭐️: 8.6k Forked By: 627 https://github.com/unclecode/crawl4ai ✅https://t.me/deep_learning_proj

llama-stack Model components of the Llama Stack APIs Creator: Meta Llama Stars ⭐️: 1.5k Forked By: 137 https://github.com/meta-llama/llama-stack ✅https://t.me/deep_learning_proj

🌟 GRIN MoE: Mixture-of-Experts от Microsoft. 🟢total parameters: 16x3.8B; 🟢active parameters: 6.6B; 🟢context length: 4096; 🟢number of embeddings 4096; 🟢number of layers: 32; ✅https://t.me/deep_learning_proj 🟡Arxiv 🟡Demo 🖥Github

LLM based Multi-Agent methods 🖥 Github: https://github.com/AgnostiqHQ/multi-agent-llm 📕 Paper: https://arxiv.org/abs/2409.12618v1 🤗 Dataset: https://paperswithcode.com/dataset/hotpotqa ✅https://t.me/deep_learning_proj

MiniCPM-V MiniCPM-V 2.6: A GPT-4V Level MLLM for Single Image, Multi Image and Video on Your Phone                                                                     Creator: OpenBMB Stars ⭐️: 11.4k Forked By: 798 GitHub Repo: https://github.com/OpenBMB/MiniCPM-V ➖➖➖➖➖➖➖➖➖➖➖➖➖➖        Join ✅https://t.me/deep_learning_proj

🖥 Awesome LLM Strawberry (OpenAI o1) ▪ Github ✅https://t.me/deep_learning_proj

firecrawl Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.                                                                     Creator: Mendable Stars ⭐️: 12.3k Forked By: 861 GitHub Repo: https://github.com/mendableai/firecrawl ✅ https://t.me/deep_learning_proj

graphrag A modular graph-based Retrieval-Augmented Generation (RAG) system                                                                     Creator: Microsoft Stars ⭐️: 13.7k Forked By: 1.2k GitHub Repo: https://github.com/microsoft/graphrag ➖➖➖➖➖➖➖➖➖➖➖➖➖➖        Join @deep_learning_proj