Image-Text-to-Text
Transformers
Safetensors
English
dendro_omni
text-generation
phillnet
phillnet-mini
dendro
visual-question-answering
multimodal
adaptive-reasoning
code-generation
long-context
custom-code
text-vision-only
conversational
custom_code
Instructions to use ayjays132/Phillnet-Mini-Max with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayjays132/Phillnet-Mini-Max with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ayjays132/Phillnet-Mini-Max", trust_remote_code=True) 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 AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ayjays132/Phillnet-Mini-Max", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ayjays132/Phillnet-Mini-Max with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ayjays132/Phillnet-Mini-Max" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ayjays132/Phillnet-Mini-Max", "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/ayjays132/Phillnet-Mini-Max
- SGLang
How to use ayjays132/Phillnet-Mini-Max 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 "ayjays132/Phillnet-Mini-Max" \ --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": "ayjays132/Phillnet-Mini-Max", "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 "ayjays132/Phillnet-Mini-Max" \ --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": "ayjays132/Phillnet-Mini-Max", "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 ayjays132/Phillnet-Mini-Max with Docker Model Runner:
docker model run hf.co/ayjays132/Phillnet-Mini-Max
| # Production Operations Guide | |
| Phillnet Mini Text-Vision is a **single-process, text-and-still-image inference service**. The included stack is designed for a controlled deployment boundary: one model process, one serialized generation at a time, local base64 image inputs only, optional API-key authentication, and explicit CORS origins. | |
| ## Deployment topology | |
| ```text | |
| Trusted clients | |
| │ HTTPS + API key | |
| ▼ | |
| TLS reverse proxy / edge rate limiter | |
| │ localhost HTTP | |
| ▼ | |
| Docker Compose: Phillnet Mini Text-Vision | |
| │ one Uvicorn worker + one loaded model | |
| ▼ | |
| Text generation and still-image understanding | |
| ``` | |
| Keep the model container bound to loopback by default. Terminate TLS, rate limit, and log access at a reverse proxy or managed ingress. The model container itself is intentionally not a public multi-tenant gateway. | |
| ## First deployment | |
| ```bash | |
| cp .env.example .env | |
| # Set PHILLNET_API_KEY to a long random secret. | |
| # Set PHILLNET_CORS_ORIGINS to the exact browser application origin. | |
| docker compose up --build -d | |
| docker compose ps | |
| curl http://127.0.0.1:8000/ready | |
| ``` | |
| The service reports `ready: true` only after the processor and checkpoint are loaded. | |
| ## Reverse-proxy example | |
| The following Nginx location keeps the container private, applies a request body limit, and forwards the authorization header. Configure a valid TLS server block around it. | |
| ```nginx | |
| location / { | |
| proxy_pass http://127.0.0.1:8000; | |
| proxy_http_version 1.1; | |
| proxy_set_header Host $host; | |
| proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; | |
| proxy_set_header X-Forwarded-Proto $scheme; | |
| proxy_set_header Authorization $http_authorization; | |
| proxy_set_header X-API-Key $http_x_api_key; | |
| client_max_body_size 12m; | |
| proxy_read_timeout 1800s; | |
| proxy_send_timeout 1800s; | |
| } | |
| ``` | |
| Apply an edge rate limit appropriate to available RAM and latency. One model worker is deliberate: a concurrent long-context generation can overcommit local memory. Scale by adding isolated model replicas behind a router, not by increasing Uvicorn workers inside one model container. | |
| ## Authentication and CORS | |
| Set `PHILLNET_API_KEY` in `.env`. The protected completion route accepts either of these headers: | |
| ```http | |
| Authorization: Bearer YOUR_SECRET | |
| ``` | |
| ```http | |
| X-API-Key: YOUR_SECRET | |
| ``` | |
| Set `PHILLNET_CORS_ORIGINS` to a comma-separated list of known origins such as `https://app.example.com`. Leave it empty for server-to-server callers. Never use a wildcard origin together with a browser-facing credential policy. | |
| ## Inference and input limits | |
| | Guardrail | Default | Reason | | |
| |---|---:|---| | |
| | Concurrent generations | 1 | Avoids contention and memory overcommit on one local checkpoint. | | |
| | Maximum visible answer | 8,192 tokens | Matches the model’s persisted response policy. | | |
| | Maximum images per request | 4 | Bounds multimodal preprocessing work. | | |
| | Maximum decoded image size | 10 MiB | Prevents oversized inline payloads. | | |
| | Maximum image pixels | 24,000,000 | Mitigates decompression-bomb and preprocessing risks. | | |
| | Maximum request body | 12 MiB | Rejects oversized JSON before inference. | | |
| ## Health and observability | |
| Use these endpoints in the surrounding platform: | |
| | Endpoint | Purpose | Authentication | | |
| |---|---|---| | |
| | `GET /health` | Basic liveness and advertised capability surface. | No | | |
| | `GET /ready` | Readiness after checkpoint and processor load. | No | | |
| | `POST /v1/chat/completions` | Text and optional still-image inference. | Required when `PHILLNET_API_KEY` is set. | | |
| The completion response includes `usage` counts and `elapsed_seconds`, which are sufficient for basic application-side request telemetry. Do not log request images or full user prompts unless your data-retention policy explicitly allows it. | |
| ## Upgrade and rollback | |
| Build tagged images rather than relying on mutable local source. | |
| ```bash | |
| docker compose build | |
| docker image tag phillnet-mini-text-vision:1.1.0 registry.example.com/phillnet-mini-text-vision:1.1.0 | |
| # Push to your trusted registry, then deploy that immutable tag. | |
| ``` | |
| Retain the preceding image tag and the matching `RELEASE_MANIFEST.json`. Verify the checkpoint hash before switching traffic. Roll back by returning the compose image reference to the prior known-good tag and running `docker compose up -d`. | |
| ## Scope boundary | |
| This service supports only **text generation** and **still-image understanding**. It does not expose image generation, video generation, audio, tools, agents, browsing, remote URL fetching, or arbitrary local file access. | |