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

Libraries

How to use codegood/QwenNew with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("codegood/QwenNew")
model = AutoModelForCausalLM.from_pretrained("codegood/QwenNew")
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

vLLM

How to use codegood/QwenNew with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/codegood/QwenNew

SGLang

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

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

codegood commited on Jun 14, 2024

Commit

9618964

verified ·

1 Parent(s): 5782dad

Upload Qwen2ForCausalLM

Browse files

Files changed (3) hide show

config.json +1 -1
generation_config.json +0 -1
model.safetensors +2 -2

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "codegood/QwenNew",
   "architectures": [
     "Qwen2ForCausalLM"
   ],

 {
+  "_name_or_path": "Qwen/Qwen1.5-0.5B",
   "architectures": [
     "Qwen2ForCausalLM"
   ],

generation_config.json CHANGED Viewed

@@ -2,6 +2,5 @@
   "bos_token_id": 151643,
   "eos_token_id": 151643,
   "max_new_tokens": 2048,
-  "pad_token_id": 151643,
   "transformers_version": "4.41.2"
 }

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   "eos_token_id": 151643,
   "max_new_tokens": 2048,
   "transformers_version": "4.41.2"
 }

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