Instructions to use AlphaExaAI/ExaMind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AlphaExaAI/ExaMind with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="AlphaExaAI/ExaMind")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AlphaExaAI/ExaMind")
model = AutoModelForCausalLM.from_pretrained("AlphaExaAI/ExaMind")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use AlphaExaAI/ExaMind with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/AlphaExaAI/ExaMind

SGLang

How to use AlphaExaAI/ExaMind with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "AlphaExaAI/ExaMind" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AlphaExaAI/ExaMind",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "AlphaExaAI/ExaMind" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AlphaExaAI/ExaMind",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AlphaExaAI/ExaMind with Docker Model Runner:
```
docker model run hf.co/AlphaExaAI/ExaMind
```

hleliofficiel commited on Feb 15

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@@ -59,7 +59,7 @@ model-index:
 ### Advanced Open-Source AI by AlphaExaAI
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
-[![Model](https://img.shields.io/badge/Model-7B%20Parameters-purple)](https://huggingface.co/AlphaExaAI/ExaMind)
 [![GitHub](https://img.shields.io/badge/GitHub-AlphaExaAI-black?logo=github)](https://github.com/hleliofficiel/AlphaExaAI)
 [![Architecture](https://img.shields.io/badge/Architecture-Qwen2-green)](https://huggingface.co/Qwen)
@@ -80,7 +80,7 @@ Designed for secure, structured, and professional AI assistance with strong iden
 | **Version** | V2-Final |
 | **Developer** | [AlphaExaAI](https://github.com/hleliofficiel/AlphaExaAI) |
 | **Base Architecture** | Qwen2.5-Coder-7B |
-| **Parameters** | 7 Billion (7B) |
 | **Precision** | FP32 (~29GB) / FP16 (~15GB) |
 | **Context Window** | 32,768 tokens (supports up to 128K with RoPE scaling) |
 | **License** | Apache 2.0 |

 ### Advanced Open-Source AI by AlphaExaAI
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
+[![Model](https://img.shields.io/badge/Model-8B%20Parameters-purple)](https://huggingface.co/AlphaExaAI/ExaMind)
 [![GitHub](https://img.shields.io/badge/GitHub-AlphaExaAI-black?logo=github)](https://github.com/hleliofficiel/AlphaExaAI)
 [![Architecture](https://img.shields.io/badge/Architecture-Qwen2-green)](https://huggingface.co/Qwen)
 | **Version** | V2-Final |
 | **Developer** | [AlphaExaAI](https://github.com/hleliofficiel/AlphaExaAI) |
 | **Base Architecture** | Qwen2.5-Coder-7B |
+| **Parameters** | 7.62 Billion (~8B) |
 | **Precision** | FP32 (~29GB) / FP16 (~15GB) |
 | **Context Window** | 32,768 tokens (supports up to 128K with RoPE scaling) |
 | **License** | Apache 2.0 |