Instructions to use Sumail/Bubble_bee01_2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Sumail/Bubble_bee01_2b with Transformers:

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

pipe = pipeline("text-generation", model="Sumail/Bubble_bee01_2b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Sumail/Bubble_bee01_2b")
model = AutoModelForCausalLM.from_pretrained("Sumail/Bubble_bee01_2b")
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 Sumail/Bubble_bee01_2b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sumail/Bubble_bee01_2b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sumail/Bubble_bee01_2b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Sumail/Bubble_bee01_2b

SGLang

How to use Sumail/Bubble_bee01_2b 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 "Sumail/Bubble_bee01_2b" \
    --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": "Sumail/Bubble_bee01_2b",
		"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 "Sumail/Bubble_bee01_2b" \
        --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": "Sumail/Bubble_bee01_2b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Sumail/Bubble_bee01_2b with Docker Model Runner:
```
docker model run hf.co/Sumail/Bubble_bee01_2b
```

Sumail commited on Mar 4, 2024

Commit

3c91b48

verified ·

1 Parent(s): cee0dca

Update README.md

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README.md +1 -34

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@@ -1,36 +1,3 @@
 ---
 license: apache-2.0
-tags:
-- mergewss]
-- mergekit
-- lazymergekit
-- tomaszki/gemma-25
-- tomaszki/gemma-24
----
-# Bubble_bee01_2b
-Bubble_bee01_2b is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
-* [tomaszki/gemma-25](https://huggingface.co/tomaszki/gemma-25)
-* [tomaszki/gemma-24](https://huggingface.co/tomaszki/gemma-24)
-## 🧩 Configuration
-```yaml
-slices:
-  - sources:
-      - model: tomaszki/gemma-25
-        layer_range: [0, 18]
-      - model: tomaszki/gemma-24
-        layer_range: [0, 18]
-merge_method: slerp
-base_model: tomaszki/gemma-25
-parameters:
-  t:
-    - filter: self_attn
-      value: [0, 0.5, 0.3, 0.7, 1]
-    - filter: mlp
-      value: [1, 0.5, 0.7, 0.3, 0]
-    - value: 0.5
-dtype: bfloat16
-```

 ---
 license: apache-2.0
+---