Instructions to use nitinr910/mobile-actions-functiongemma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nitinr910/mobile-actions-functiongemma with Transformers:

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

pipe = pipeline("text-generation", model="nitinr910/mobile-actions-functiongemma")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nitinr910/mobile-actions-functiongemma")
model = AutoModelForCausalLM.from_pretrained("nitinr910/mobile-actions-functiongemma")
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 nitinr910/mobile-actions-functiongemma with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nitinr910/mobile-actions-functiongemma"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nitinr910/mobile-actions-functiongemma",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nitinr910/mobile-actions-functiongemma

SGLang

How to use nitinr910/mobile-actions-functiongemma 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 "nitinr910/mobile-actions-functiongemma" \
    --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": "nitinr910/mobile-actions-functiongemma",
		"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 "nitinr910/mobile-actions-functiongemma" \
        --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": "nitinr910/mobile-actions-functiongemma",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use nitinr910/mobile-actions-functiongemma with Docker Model Runner:
```
docker model run hf.co/nitinr910/mobile-actions-functiongemma
```

nitinr910 commited on 26 days ago

Commit

5ee6b35

verified ·

1 Parent(s): ec0a627

Training in progress, step 1500

Browse files

Files changed (2) hide show

model.safetensors +1 -1
runs/Jun08_06-57-54_13e425453cfc/events.out.tfevents.1780901916.13e425453cfc.371.2 +2 -2

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ea48a6b4cfda98938d5021f5409136994dd4eae42ef1c6dbb45cf8f759cc9ec6
 size 536223056

 version https://git-lfs.github.com/spec/v1
+oid sha256:0f1138bb377848eec8aeb8fa4a00ea49fb74c3e08e30da0721d0a266a710ddfa
 size 536223056

runs/Jun08_06-57-54_13e425453cfc/events.out.tfevents.1780901916.13e425453cfc.371.2 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:20e360d7e387d361a2c97ce925e176d4a6d31eaa8cf2218d9249f5e572b5282b
-size 25302

 version https://git-lfs.github.com/spec/v1
+oid sha256:86650c20ba9d5ca53d07b940a8a47b3f6605dea1dd7bdaa619a6c49bd38a72dd
+size 34852