Instructions to use nkim7/eval3_phase2_TOY with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use nkim7/eval3_phase2_TOY with PEFT:
```
Task type is invalid.
```

How to use nkim7/eval3_phase2_TOY with Transformers:

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

pipe = pipeline("text-generation", model="nkim7/eval3_phase2_TOY")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("nkim7/eval3_phase2_TOY", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use nkim7/eval3_phase2_TOY with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nkim7/eval3_phase2_TOY"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nkim7/eval3_phase2_TOY",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nkim7/eval3_phase2_TOY

SGLang

How to use nkim7/eval3_phase2_TOY 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 "nkim7/eval3_phase2_TOY" \
    --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": "nkim7/eval3_phase2_TOY",
		"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 "nkim7/eval3_phase2_TOY" \
        --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": "nkim7/eval3_phase2_TOY",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use nkim7/eval3_phase2_TOY with Docker Model Runner:
```
docker model run hf.co/nkim7/eval3_phase2_TOY
```

eval3_phase2_TOY / chat_template.jinja

nkim7

Phase 2 scene-position LoRA (LEFT/CENTER/RIGHT card recognition) — 99.44% benchmark (179/180)

1fa04ae verified about 16 hours ago

raw

history blame contribute delete

403 Bytes

	<\|im_start\|>{% for message in messages %}{{message['role'] \| capitalize}}{% if message['content'][0]['type'] == 'image' %}{{':'}}{% else %}{{': '}}{% endif %}{% for line in message['content'] %}{% if line['type'] == 'text' %}{{line['text']}}{% elif line['type'] == 'image' %}{{ '<image>' }}{% endif %}{% endfor %}<end_of_utterance>
	{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}