Instructions to use CoolSpring/Qwen2-0.5B-Abyme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CoolSpring/Qwen2-0.5B-Abyme with Transformers:

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

pipe = pipeline("text-generation", model="CoolSpring/Qwen2-0.5B-Abyme")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("CoolSpring/Qwen2-0.5B-Abyme")
model = AutoModelForCausalLM.from_pretrained("CoolSpring/Qwen2-0.5B-Abyme", 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 CoolSpring/Qwen2-0.5B-Abyme with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CoolSpring/Qwen2-0.5B-Abyme"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CoolSpring/Qwen2-0.5B-Abyme",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/CoolSpring/Qwen2-0.5B-Abyme

SGLang

How to use CoolSpring/Qwen2-0.5B-Abyme 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 "CoolSpring/Qwen2-0.5B-Abyme" \
    --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": "CoolSpring/Qwen2-0.5B-Abyme",
		"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 "CoolSpring/Qwen2-0.5B-Abyme" \
        --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": "CoolSpring/Qwen2-0.5B-Abyme",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use CoolSpring/Qwen2-0.5B-Abyme with Docker Model Runner:
```
docker model run hf.co/CoolSpring/Qwen2-0.5B-Abyme
```

CoolSpring

leaderboard-pr-bot commited on Sep 6, 2024

Commit

541e78a

verified ·

1 Parent(s): a48b7c0

Adding Evaluation Results (#1)

Browse files

- Adding Evaluation Results (3a59415188074fb4b26217a204610066d60d24b1)

Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +20 -7

README.md CHANGED Viewed

@@ -1,17 +1,17 @@
 ---
 license: apache-2.0
-base_model: Qwen/Qwen2-0.5B
 tags:
 - axolotl
 - generated_from_trainer
 model-index:
 - name: Qwen2-0.5B-Abyme
   results: []
-datasets:
-- Magpie-Align/Magpie-Qwen2-Pro-300K-Filtered
-language:
-- en
-- zh
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -131,4 +131,17 @@ The following hyperparameters were used during training:
 - Transformers 4.42.3
 - Pytorch 2.3.1+cu121
 - Datasets 2.19.1
-- Tokenizers 0.19.1

 ---
+language:
+- en
+- zh
 license: apache-2.0
 tags:
 - axolotl
 - generated_from_trainer
+base_model: Qwen/Qwen2-0.5B
+datasets:
+- Magpie-Align/Magpie-Qwen2-Pro-300K-Filtered
 model-index:
 - name: Qwen2-0.5B-Abyme
   results: []
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 - Transformers 4.42.3
 - Pytorch 2.3.1+cu121
 - Datasets 2.19.1
+- Tokenizers 0.19.1
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_CoolSpring__Qwen2-0.5B-Abyme)
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               | 4.76|
+|IFEval (0-Shot)    |19.15|
+|BBH (3-Shot)       | 2.28|
+|MATH Lvl 5 (4-Shot)| 1.51|
+|GPQA (0-shot)      | 0.45|
+|MuSR (0-shot)      | 1.48|
+|MMLU-PRO (5-shot)  | 3.70|