Instructions to use mvasiliniuc/iva-codeint-swift-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mvasiliniuc/iva-codeint-swift-small with Transformers:

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

pipe = pipeline("text-generation", model="mvasiliniuc/iva-codeint-swift-small")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mvasiliniuc/iva-codeint-swift-small")
model = AutoModelForCausalLM.from_pretrained("mvasiliniuc/iva-codeint-swift-small")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mvasiliniuc/iva-codeint-swift-small with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mvasiliniuc/iva-codeint-swift-small"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mvasiliniuc/iva-codeint-swift-small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mvasiliniuc/iva-codeint-swift-small

SGLang

How to use mvasiliniuc/iva-codeint-swift-small 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 "mvasiliniuc/iva-codeint-swift-small" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mvasiliniuc/iva-codeint-swift-small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "mvasiliniuc/iva-codeint-swift-small" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mvasiliniuc/iva-codeint-swift-small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use mvasiliniuc/iva-codeint-swift-small with Docker Model Runner:
```
docker model run hf.co/mvasiliniuc/iva-codeint-swift-small
```

mvasiliniuc commited on Jul 9, 2023

Commit

33788bc

1 Parent(s): c1cab11

Add widgets for inference examples

Browse files

Files changed (1) hide show

README.md +9 -0

README.md CHANGED Viewed

@@ -10,6 +10,15 @@ tags:
 - swift
 - mobile
 - generation
 ---
 iva-codeint-swift-small GPT-2 is (small version - 239.4M parameters) trained from scratch to obtain results in the text-to-code task tailored for Swift language used
 in native mobile development (iOS).

 - swift
 - mobile
 - generation
+widget:
+- text: "/*\n  A function that returns the time zone currently configured on the device.\n*/\n"
+  example_title: "Get the current time zone of the device"
+- text: "/*\n  A function that returns the current version of the operating system.\n*/\n"
+  example_title: "Get current device operating system"
+- text: "/* \nA function that fires an NSNotification named 'MyUpdate'. \n*/\npublic func post"
+  example_title: "Post NSNotification"
+- text: "/* \nA public function that saves a given String value in UserPreference at a given String key.\n*/\n"
+  example_title: "Save to UserPreference"
 ---
 iva-codeint-swift-small GPT-2 is (small version - 239.4M parameters) trained from scratch to obtain results in the text-to-code task tailored for Swift language used
 in native mobile development (iOS).