Text Generation
Transformers
Safetensors
llama
arriella
northwind
company-model
lora-merged
conversational
text-generation-inference
Instructions to use UnaverageTech411/northwind-ops with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UnaverageTech411/northwind-ops with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="UnaverageTech411/northwind-ops") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("UnaverageTech411/northwind-ops") model = AutoModelForCausalLM.from_pretrained("UnaverageTech411/northwind-ops", device_map="auto") 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 Settings
- vLLM
How to use UnaverageTech411/northwind-ops with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "UnaverageTech411/northwind-ops" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "UnaverageTech411/northwind-ops", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/UnaverageTech411/northwind-ops
- SGLang
How to use UnaverageTech411/northwind-ops 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 "UnaverageTech411/northwind-ops" \ --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": "UnaverageTech411/northwind-ops", "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 "UnaverageTech411/northwind-ops" \ --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": "UnaverageTech411/northwind-ops", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use UnaverageTech411/northwind-ops with Docker Model Runner:
docker model run hf.co/UnaverageTech411/northwind-ops
| license: llama3.2 | |
| library_name: transformers | |
| tags: | |
| - arriella | |
| - northwind | |
| - company-model | |
| - lora-merged | |
| base_model: unsloth/Llama-3.2-1B-Instruct | |
| pipeline_tag: text-generation | |
| # Northwind Ops Assistant | |
| Showcase company model from the **Arriella** custom-model factory (fictional Northwind Traders). | |
| - Base: `unsloth/Llama-3.2-1B-Instruct` | |
| - Domain: ServiceNow / Concur / Workday ops Q&A | |
| - Demo Space: [UnaverageTech411/northwind-ops](https://huggingface.co/spaces/UnaverageTech411/northwind-ops) | |
| Not a live customer — reference deliverable for buyers evaluating the factory path. | |