Instructions to use Haruster/ordinal-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Haruster/ordinal-2b with Transformers:

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

pipe = pipeline("text-generation", model="Haruster/ordinal-2b", trust_remote_code=True, device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Haruster/ordinal-2b", trust_remote_code=True, dtype="auto", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Haruster/ordinal-2b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Haruster/ordinal-2b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Haruster/ordinal-2b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Haruster/ordinal-2b

SGLang

How to use Haruster/ordinal-2b 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 "Haruster/ordinal-2b" \
    --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": "Haruster/ordinal-2b",
		"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 "Haruster/ordinal-2b" \
        --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": "Haruster/ordinal-2b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Haruster/ordinal-2b with Docker Model Runner:
```
docker model run hf.co/Haruster/ordinal-2b
```

ordinal-2b / special_tokens_map.json

Haruster

Ordinal v1.0 — ordinal-2b architecture/config

7014cbd verified about 1 month ago

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	{
	"bos_token": {
	"content": "<\|begin\|>",
	"lstrip": false,
	"rstrip": false,
	"single_word": false,
	"normalized": false
	},
	"eos_token": {
	"content": "<\|end\|>",
	"lstrip": false,
	"rstrip": false,
	"single_word": false,
	"normalized": false
	},
	"pad_token": {
	"content": "<\|pad\|>",
	"lstrip": false,
	"rstrip": false,
	"single_word": false,
	"normalized": false
	},
	"unk_token": {
	"content": "<\|unk\|>",
	"lstrip": false,
	"rstrip": false,
	"single_word": false,
	"normalized": false
	},
	"additional_special_tokens": [
	"<\|system\|>",
	"<\|user\|>",
	"<\|assistant\|>",
	"<\|end_turn\|>",
	"<\|cve\|>",
	"<\|mitre\|>",
	"<\|cwe\|>",
	"<\|capec\|>",
	"<\|ioc\|>",
	"<\|ip\|>",
	"<\|hash\|>",
	"<\|domain\|>",
	"<\|confidence_high\|>",
	"<\|confidence_medium\|>",
	"<\|confidence_low\|>",
	"<\|source_verified\|>",
	"<\|source_unverified\|>",
	"<\|code_start\|>",
	"<\|code_end\|>",
	"<\|thinking\|>",
	"<\|end_thinking\|>"
	]
	}