Instructions to use v000000/Qwen2.5-Lumen-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use v000000/Qwen2.5-Lumen-14B with Transformers:

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

pipe = pipeline("text-generation", model="v000000/Qwen2.5-Lumen-14B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("v000000/Qwen2.5-Lumen-14B")
model = AutoModelForCausalLM.from_pretrained("v000000/Qwen2.5-Lumen-14B", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use v000000/Qwen2.5-Lumen-14B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "v000000/Qwen2.5-Lumen-14B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "v000000/Qwen2.5-Lumen-14B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/v000000/Qwen2.5-Lumen-14B

SGLang

How to use v000000/Qwen2.5-Lumen-14B 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 "v000000/Qwen2.5-Lumen-14B" \
    --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": "v000000/Qwen2.5-Lumen-14B",
		"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 "v000000/Qwen2.5-Lumen-14B" \
        --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": "v000000/Qwen2.5-Lumen-14B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use v000000/Qwen2.5-Lumen-14B with Docker Model Runner:
```
docker model run hf.co/v000000/Qwen2.5-Lumen-14B
```

v000000 commited on Sep 23, 2024

Commit

34ed087

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Update README.md

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README.md +5 -4

README.md CHANGED Viewed

@@ -177,10 +177,6 @@ Anna reached over and took hands of compassionate warmth — eyes wide with grat
 <b>*As you can see the model has mostly adapted to the intended response style from Gutenberg dataset.*</b>
-* *If you are using it for character-based roleplay, please use the prompts below for an enhanced experience.*
-* [For realistic RP/non-RPGs - MarinaraSpaghetti ChatML Customized](https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main/Customized/ChatML)
-* [For freeform RP/RPGs - MarinaraSpaghetti ChatML Basic](https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main/Basic/ChatML)
 ## Recipe
 ```yaml
@@ -202,6 +198,11 @@ merge_method: model_stock
 dtype: bfloat16
 ```
 ### Finetune and merge
 This is a merge and finetune of pre-trained language models.

 <b>*As you can see the model has mostly adapted to the intended response style from Gutenberg dataset.*</b>
 ## Recipe
 ```yaml
 dtype: bfloat16
 ```
+*If your use case is character-based roleplay, please consider using the prompts below for an enhanced experience*
+* [For realistic RP/non-RPGs - MarinaraSpaghetti ChatML Customized](https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main/Customized/ChatML)
+* [For freeform RP/RPGs - MarinaraSpaghetti ChatML Basic](https://huggingface.co/MarinaraSpaghetti/SillyTavern-Settings/tree/main/Basic/ChatML)
 ### Finetune and merge
 This is a merge and finetune of pre-trained language models.