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Krishkanth/krish-mind-gguf-standalone-16
krish-mind-gguf-standalone-16 is a text generation model from Krishkanth. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
Downloads · 30 days
13
5% of all-time downloads
All-time downloads
275
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Repo size
21 GB
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.gguf16.1 GB · 100%
From the Hugging Face model README
✨ Krish Mind is an elite independent AI assistant developed by Krish CS. ✨ 🧠 The highest quality version — engineered for powerful workstations!
</div>Krish Mind is a state-of-the-art independent AI assistant developed by Krish CS. It has its own unique identity, personality, and knowledge base, built to be genuinely helpful and intelligent.
Krish Mind Full is the maximum quality edition running at full FP16 precision — meaning absolutely zero quality is lost. It is designed for powerful desktops and workstations with 32+ GB RAM. If you demand the absolute best reasoning and response accuracy, this is your version.
⚠️ Note on Mobile: The Full version at ~16 GB is not compatible with smartphones. If you want Krish Mind on your phone, use the Mobile version: 📱 Krish Mind Mobile (~2 GB)
| 🏷️ Version | 📦 Size | 💾 RAM | 📱 Mobile | 💻 Desktop | ⬇️ Action |
|---|---|---|---|---|---|
| 📱 Mobile | ~2 GB | 3-4 GB | ✅ Yes | ✅ Yes | 🔗 Visit Repository |
| ⚡ Q4 Balanced | ~5 GB | 8-16 GB | ❌ No | ✅ Yes | 🔗 Visit Repository |
| 🚀 Full Quality (This Repo) | ~16 GB | 32+ GB | ❌ No | ✅ Yes | 📥 Download Now |
| 📄 File | 📦 Size | 🔗 Download |
|---|---|---|
krish-mind-standalone-f16.gguf | ~16 GB | 📥 Download Now |
Ollama handles model loading, memory management, and the chat interface automatically. Works on Windows, Mac, and Linux.
Step 1: Install Ollama
Step 2: Download the Model File
krish-mind-standalone-f16.gguf from the download link at the topC:\Users\YourName\krish-mind\Step 3: Create a Modelfile
Modelfile (remove the .txt extension completely)FROM ./krish-mind-standalone-f16.gguf
Step 4: Import into Ollama
Windows + R, type cmd, press Enter)cd C:\Users\YourName\krish-mind
ollama create krish-mind -f Modelfile
Step 5: Start Chatting!
ollama run krish-mind
Step 1: Install Ollama
Step 2: Download the Model
krish-mind-standalone-f16.gguf from the link above~/Downloads/krish-mind/Step 3: Setup via Terminal
Cmd + Space, type Terminal)mkdir -p ~/Downloads/krish-mind
cd ~/Downloads/krish-mind
echo 'FROM ./krish-mind-standalone-f16.gguf' > Modelfile
(Ensure the GGUF file is in this same folder)
Step 4: Import and Run
ollama create krish-mind -f Modelfile
ollama run krish-mind
💡 On Apple Silicon (M1/M2/M3), the full FP16 model will leverage the unified memory architecture for best performance!
Step 1: Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh
Step 2: Download the Model
mkdir -p ~/krish-mind && cd ~/krish-mind
wget "https://huggingface.co/Krishkanth/krish-mind-gguf-standalone-16/resolve/main/krish-mind-standalone-f16.gguf"
Step 3: Create Modelfile and Run
echo 'FROM ./krish-mind-standalone-f16.gguf' > Modelfile
ollama create krish-mind -f Modelfile
ollama run krish-mind
LM Studio gives you a full ChatGPT-like interface running locally with no commands.
Step 1: Download LM Studio from https://lmstudio.ai and install it
Step 2: Download krish-mind-standalone-f16.gguf from the link above
Step 3: Open LM Studio and go to the My Models section (folder icon on left)
Step 4: Click Add Model and drag/drop your GGUF file into the window
Step 5: Click the AI Chat icon, then select krish-mind-standalone-f16 from the model dropdown at the top
Step 6: Start chatting!
💡 LM Studio Tip: Go to Settings → Hardware and increase GPU layers if you have a dedicated GPU for significantly faster responses!
Install the library:
pip install llama-cpp-python
For GPU acceleration (optional but recommended for 16GB model):
CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python --upgrade
Run Krish Mind in your code:
from llama_cpp import Llama
llm = Llama(
model_path="./krish-mind-standalone-f16.gguf",
n_ctx=4096,
n_threads=8,
n_gpu_layers=35, # Set to 0 if no GPU, increase for more GPU offloading
)
response = llm.create_chat_completion(
messages=[{"role": "user", "content": "Hello! Who are you?"}]
)
print(response["choices"][0]["message"]["content"])
| 💻 Platform | 🥉 Minimum | 🥇 Recommended |
|---|---|---|
| Windows | 32 GB RAM, Intel i7 / AMD Ryzen 7 | 64 GB RAM, high-end CPU |
| Mac | 32 GB RAM, Apple M1 Max/Ultra | Apple M2 Max/Ultra/M3 Pro |
| Linux | 32 GB RAM | 64 GB RAM, Workstation CPU |
Storage Space Required: 20 GB free space
📱 Prefer to run on a phone or laptop with less RAM? Use the Mobile Version (~2 GB) or Q4 Version (~5 GB) instead!
Q: Why do I need 32 GB RAM for the full version? A: The FP16 model stores all weights at full 16-bit precision. Loading it into memory requires ~16 GB RAM just for the weights, plus additional RAM for the context window and system processes.
Q: Can I run it with a GPU? A: Yes! If you have an NVIDIA GPU with 16+ GB VRAM, Ollama and LM Studio will automatically use it, giving you much faster response times.
Q: Does it work offline? A: Yes. After the first download, everything runs 100% locally. No internet, no servers, no logs.
Q: Is this free? A: Yes. Released under Apache 2.0 — free for personal and commercial use.
✨ Happy Chatting with Krish Mind Full! ✨ Made with ❤️ by Krish CS
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