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Mohammed Vasim

md-vasim

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commented on an article 15 days ago

Fine-Tuning 1B LLaMA 3.2: A Comprehensive Step-by-Step Guide with Code

upvoted an article 15 days ago

Fine-Tuning 1B LLaMA 3.2: A Comprehensive Step-by-Step Guide with Code

liked a model 6 months ago

stepfun-ai/GOT-OCR2_0

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commented on Fine-Tuning 1B LLaMA 3.2: A Comprehensive Step-by-Step Guide with Code 15 days ago

It seems amazing blog. I will walk through it.

upvoted an article 15 days ago

Article

Fine-Tuning 1B LLaMA 3.2: A Comprehensive Step-by-Step Guide with Code

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Oct 2, 2024

• 60

liked a model 6 months ago

stepfun-ai/GOT-OCR2_0

Image-Text-to-Text • Updated Feb 4 • 88.3k • 1.44k

upvoted 2 articles 6 months ago

Article

Llama can now see and run on your device - welcome Llama 3.2

Sep 25, 2024

• 187

Article

Fine-tuning LLMs to 1.58bit: extreme quantization made easy

Sep 18, 2024

• 228

updated a model 7 months ago

md-vasim/vit-base-patch16-224-finetuned-lora-oxfordPets

Image Classification • Updated Aug 26, 2024

updated a Space 7 months ago

Vit Image Classification

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updated a model 7 months ago

md-vasim/detr-resnet-50-hardhat-finetuned

Updated Aug 21, 2024

liked a Space 8 months ago

Falcon Mamba Playground

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Generate chat responses using FalconMamba-7b model

reacted to singhsidhukuldeep's post with 🔥 8 months ago

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AutoGen from @Microsoft is crazy! 🚀 It's an open-source framework that allows LLM agents to chat with each other to solve your tasks. 🤖💬

They use the Assistant-Agent and User-Proxy-Agent framework! 🛠️

As the name suggests, the Assistant-Agent does the work, and the User-Proxy-Agent behaves like a human, guiding the Assistant-Agent and double-checking its work! 🧑‍💻✅

Both Assistant-Agent and User-Proxy-Agent can be the same or different LLMs. 🤔🔄

AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. 🌟

This is truly amazing for building agentic AI quickly! 🚀✨

GitHub: https://github.com/microsoft/autogen 🔗

from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

#config
config_list = config_list_from_json(env_or_file="OAI_CONFIG_LIST")

assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding", "use_docker": False}) 

user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stock price change YTD.")
# This initiates an automated chat between the two agents to solve the task