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
```

App Showcase -- see the desktop app before you install

by tjarvis91 - opened May 26

Discussion

tjarvis91

Owner May 26

We just added a full app showcase to the model card so prospective users can see every tab of the VFAi-X desktop app before downloading. Six high-res screenshots of the actual production UI running against a real Tradier paper account:

Dashboard -- account balance, buying power, confidence panels, system status (Tradier connected, 5070 Ti GPU readout, risk controls)
Charts -- per-ticker chart with model-emitted Breakout / SH (short) / SL (stop-loss) annotations + Penny Universe sidebar (479 symbols), multi-timeframe selector
Orders -- AI Trading Activity board (open / filled / cancelled / partial fills), ticker filter, time-range tabs
Options -- full options chain (calls + puts, IV / delta / OI / vol / bid / ask) + Portfolio Greeks panel + Risk Analysis
Fundamentals -- per-ticker valuation, margins, key highlights, macro calendar, earnings calendar
Change Log -- release notes, runtime checks, local diagnostics, backend tools (restart, health check, API docs)

The screenshots live in /screenshots/ on the repo:
https://huggingface.co/tjarvis91/vfaix-vpa-options-trader/tree/main/screenshots

Honest disclosure: the AI engine was disabled when capturing screenshots so we didn't compete with an active training run on the 5070 Ti. Engine connects automatically on first launch.

Download:

Latest installer: https://huggingface.co/tjarvis91/vfaix-vpa-options-trader/resolve/main/installers/VFAi-X-Latest-Setup.exe?download=true
Pinned 3.5v26-3.9 / app 2.2.17: https://huggingface.co/tjarvis91/vfaix-vpa-options-trader/resolve/main/installers/VFAi-X-3.5v26-3.9-FrankenB-Tradier-Settings-Migration-Setup.exe?download=true

Discord (community + install help): https://discord.gg/PtuHZDv5ju
Support continued training runs: https://ko-fi.com/tjarvis91

tjarvis91

Owner May 26

Live discussion + the deployed Q-Chat router:

🎫 Discord community (builders training their own trading/finance models) — https://discord.gg/PtuHZDv5ju
📜 Public research devlog — https://github.com/thron-j/qovaryx-ai-research
🤗 All published models — https://huggingface.co/tjarvis91
☕ Support the next training run — https://ko-fi.com/tjarvis91

Type /qchat ask <question> in the server to send a query through our compact intent-router (live demo of the published thesis, running on free HF CPU).

No signals. No financial advice. Engineering only.

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