Instructions to use DataKensei/phi-2-function-calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DataKensei/phi-2-function-calling with Transformers:

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

pipe = pipeline("text-generation", model="DataKensei/phi-2-function-calling")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DataKensei/phi-2-function-calling")
model = AutoModelForCausalLM.from_pretrained("DataKensei/phi-2-function-calling")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use DataKensei/phi-2-function-calling with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DataKensei/phi-2-function-calling"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DataKensei/phi-2-function-calling",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DataKensei/phi-2-function-calling

SGLang

How to use DataKensei/phi-2-function-calling 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 "DataKensei/phi-2-function-calling" \
    --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": "DataKensei/phi-2-function-calling",
		"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 "DataKensei/phi-2-function-calling" \
        --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": "DataKensei/phi-2-function-calling",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DataKensei/phi-2-function-calling with Docker Model Runner:
```
docker model run hf.co/DataKensei/phi-2-function-calling
```

cgrodrigues commited on Aug 18, 2024

Commit

7b35981

verified ·

1 Parent(s): 06cae33

Update README.md

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@@ -173,7 +173,7 @@ Total emissions are estimated to be 0.78 kgCO of which 0 percents were directly
 Estimations were conducted using the [MachineLearning Impact calculator](https://mlco2.github.io/impact#compute) presented in presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700)
-```
 @article{lacoste2019quantifying,
   title={Quantifying the Carbon Emissions of Machine Learning},
   author={Lacoste, Alexandre and Luccioni, Alexandra and Schmidt, Victor and Dandres, Thomas},
@@ -211,7 +211,7 @@ The training used PyTorch and the Hugging Face Transformers library, with additi
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 **BibTeX:**
-```
 @misc{phi2functioncalling,
   title={phi-2-function-calling},
   author={Carlos Rodrigues},

 Estimations were conducted using the [MachineLearning Impact calculator](https://mlco2.github.io/impact#compute) presented in presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700)
+```BibTeX
 @article{lacoste2019quantifying,
   title={Quantifying the Carbon Emissions of Machine Learning},
   author={Lacoste, Alexandre and Luccioni, Alexandra and Schmidt, Victor and Dandres, Thomas},
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 **BibTeX:**
+```BibTeX
 @misc{phi2functioncalling,
   title={phi-2-function-calling},
   author={Carlos Rodrigues},