Instructions to use theminji/TinyLlama-v2ray with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use theminji/TinyLlama-v2ray with Transformers:

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

pipe = pipeline("text-generation", model="theminji/TinyLlama-v2ray")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("theminji/TinyLlama-v2ray")
model = AutoModelForCausalLM.from_pretrained("theminji/TinyLlama-v2ray", 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 theminji/TinyLlama-v2ray with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "theminji/TinyLlama-v2ray"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "theminji/TinyLlama-v2ray",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/theminji/TinyLlama-v2ray

SGLang

How to use theminji/TinyLlama-v2ray 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 "theminji/TinyLlama-v2ray" \
    --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": "theminji/TinyLlama-v2ray",
		"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 "theminji/TinyLlama-v2ray" \
        --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": "theminji/TinyLlama-v2ray",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use theminji/TinyLlama-v2ray with Docker Model Runner:
```
docker model run hf.co/theminji/TinyLlama-v2ray
```

TinyLlama-v2ray / README.md

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Commit History

Update README.md 5869843 verified

Update README.md e4a5e20

Update README.md f1eaffc

Update README.md 8d27259

End of training 8cdcae1

Update README.md

5869843
verified

Update README.md

e4a5e20

Update README.md

f1eaffc

Update README.md

8d27259

End of training

8cdcae1