Instructions to use tjarvis91/vfaix-vpa-options-trader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tjarvis91/vfaix-vpa-options-trader with Transformers:

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

pipe = pipeline("image-text-to-text", model="tjarvis91/vfaix-vpa-options-trader")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("tjarvis91/vfaix-vpa-options-trader")
model = AutoModelForMultimodalLM.from_pretrained("tjarvis91/vfaix-vpa-options-trader", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tjarvis91/vfaix-vpa-options-trader with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tjarvis91/vfaix-vpa-options-trader"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tjarvis91/vfaix-vpa-options-trader",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/tjarvis91/vfaix-vpa-options-trader

SGLang

How to use tjarvis91/vfaix-vpa-options-trader 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 "tjarvis91/vfaix-vpa-options-trader" \
    --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": "tjarvis91/vfaix-vpa-options-trader",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "tjarvis91/vfaix-vpa-options-trader" \
        --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": "tjarvis91/vfaix-vpa-options-trader",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use tjarvis91/vfaix-vpa-options-trader with Docker Model Runner:
```
docker model run hf.co/tjarvis91/vfaix-vpa-options-trader
```

VFAi-X Qovaryx 2.5.2 hotfix is live

by tjarvis91 - opened May 31

Discussion

tjarvis91

Owner May 31

The VFAi-X Qovaryx 2.5.2 hotfix is live.

Windows installer:
https://huggingface.co/tjarvis91/vfaix-vpa-options-trader/resolve/main/installers/VFAi-X-Latest-Qovaryx-Setup.exe?download=true

Pinned installer:
https://huggingface.co/tjarvis91/vfaix-vpa-options-trader/resolve/main/installers/VFAi-X-3.5v30-2.5.2-Qovaryx-Public-Setup.exe?download=true

Auto-update pointer:
https://huggingface.co/tjarvis91/vfaix-vpa-options-trader/resolve/main/updates/latest.json

Fix coverage: Qovaryx runtime startup, app.asar package parse failure, the 35%/yellow AI-loading state, backend fallback launch, AppData Tradier key visibility, nonfatal broker startup, Qovaryx naming/icons, Discord/help links, and default Qovaryx profitability/risk settings.

Validation completed before posting: the installer was downloaded back from HF, SHA256 matched, installed cleanly on C:, pulled the Qovaryx runtime from HF, loaded Qovaryx to 100%, started the trading engine, and the older-version updater path staged/applied/relaunched successfully.

Public build contains no private API keys.

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