Instructions to use ProCreations/intellite-500m-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ProCreations/intellite-500m-sft with Transformers:

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

pipe = pipeline("text-generation", model="ProCreations/intellite-500m-sft", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ProCreations/intellite-500m-sft", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ProCreations/intellite-500m-sft with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ProCreations/intellite-500m-sft"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ProCreations/intellite-500m-sft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ProCreations/intellite-500m-sft

SGLang

How to use ProCreations/intellite-500m-sft 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 "ProCreations/intellite-500m-sft" \
    --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": "ProCreations/intellite-500m-sft",
		"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 "ProCreations/intellite-500m-sft" \
        --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": "ProCreations/intellite-500m-sft",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ProCreations/intellite-500m-sft with Docker Model Runner:
```
docker model run hf.co/ProCreations/intellite-500m-sft
```

Nice model

by Bc-AI - opened about 13 hours ago

Discussion

Bc-AI

about 13 hours ago

@ProCreations im pretty sure the reason it can’t handle math or code that well is that your pretraining dataset was more general focused. Like for my code models I usually pretrain 70% code, 15% math, 10% general, 5% reasoning data.

ProCreations

Owner about 13 hours ago

Yea this model has a focus on general knowledge than math, if I do ever make a new version which I probably will just as a side project it’ll be a lot better

Bc-AI

about 13 hours ago

@ProCreations for the thing you can try my other email boning.cui@icloud.com

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