Instructions to use cortexso/intellect-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cortexso/intellect-1 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="cortexso/intellect-1",
	filename="intellect-1-instruct-q2_k.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use cortexso/intellect-1 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf cortexso/intellect-1:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf cortexso/intellect-1:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf cortexso/intellect-1:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf cortexso/intellect-1:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf cortexso/intellect-1:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf cortexso/intellect-1:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf cortexso/intellect-1:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf cortexso/intellect-1:Q4_K_M

Use Docker

docker model run hf.co/cortexso/intellect-1:Q4_K_M

LM Studio
Jan

vLLM

How to use cortexso/intellect-1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cortexso/intellect-1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cortexso/intellect-1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cortexso/intellect-1:Q4_K_M

Ollama
How to use cortexso/intellect-1 with Ollama:
```
ollama run hf.co/cortexso/intellect-1:Q4_K_M
```

Unsloth Studio new

How to use cortexso/intellect-1 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for cortexso/intellect-1 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for cortexso/intellect-1 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for cortexso/intellect-1 to start chatting

Docker Model Runner
How to use cortexso/intellect-1 with Docker Model Runner:
```
docker model run hf.co/cortexso/intellect-1:Q4_K_M
```

Lemonade

How to use cortexso/intellect-1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull cortexso/intellect-1:Q4_K_M

Run and chat with the model

lemonade run user.intellect-1-Q4_K_M

List all available models

lemonade list

Minh141120 commited on Mar 3, 2025

Commit

f46fd81

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Update README.md

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@@ -10,12 +10,11 @@ tags:
 Intellect-1 is a high-performance instruction-tuned model developed by Qwen, designed to handle a broad range of natural language processing tasks with efficiency and precision. Optimized for dialogue, reasoning, and knowledge-intensive applications, Intellect-1 excels in structured generation, summarization, and retrieval-augmented tasks. It is part of an open ecosystem, providing transparency in training data, model architecture, and fine-tuning methodologies.
 ## Variants
 | No | Variant | Cortex CLI command |
 | --- | --- | --- |
-| 1 | [gguf](https://huggingface.co/cortexso/intellect-1/tree/main) | `cortex run intellect-1` |
 ## Use it with Jan (UI)
@@ -36,6 +35,6 @@ Intellect-1 is a high-performance instruction-tuned model developed by Qwen, des
 ## Credits
 - **Author:** Qwen
-- **Converter:** [Homebrew]
-- **Original License:** [Licence]
-- **Papers:** [Paper]

 Intellect-1 is a high-performance instruction-tuned model developed by Qwen, designed to handle a broad range of natural language processing tasks with efficiency and precision. Optimized for dialogue, reasoning, and knowledge-intensive applications, Intellect-1 excels in structured generation, summarization, and retrieval-augmented tasks. It is part of an open ecosystem, providing transparency in training data, model architecture, and fine-tuning methodologies.
 ## Variants
 | No | Variant | Cortex CLI command |
 | --- | --- | --- |
+| 1 | [Intellect-1-10b](https://huggingface.co/cortexso/intellect-1/tree/10b) | `cortex run intellect-1:10b` |
 ## Use it with Jan (UI)
 ## Credits
 - **Author:** Qwen
+- **Converter:** [Homebrew](https://homebrew.ltd/)
+- **Original License:** [Licence](https://choosealicense.com/licenses/apache-2.0/)
+- **Papers:** [Technical Paper](https://github.com/PrimeIntellect-ai/prime)