Instructions to use KathirKs/phi-2_alpaca_52k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use KathirKs/phi-2_alpaca_52k with Transformers:

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

pipe = pipeline("text-generation", model="KathirKs/phi-2_alpaca_52k", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("KathirKs/phi-2_alpaca_52k", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use KathirKs/phi-2_alpaca_52k with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KathirKs/phi-2_alpaca_52k"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "KathirKs/phi-2_alpaca_52k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/KathirKs/phi-2_alpaca_52k

SGLang

How to use KathirKs/phi-2_alpaca_52k 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 "KathirKs/phi-2_alpaca_52k" \
    --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": "KathirKs/phi-2_alpaca_52k",
		"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 "KathirKs/phi-2_alpaca_52k" \
        --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": "KathirKs/phi-2_alpaca_52k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use KathirKs/phi-2_alpaca_52k with Docker Model Runner:
```
docker model run hf.co/KathirKs/phi-2_alpaca_52k
```

phi-2_alpaca_52k / README.md

KathirKs

Update README.md

e8854f3 almost 3 years ago

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metadata

license: apache-2.0
datasets:
  - vicgalle/alpaca-gpt4
language:
  - en

This is a finetuned version microsoft phi - 2. This is finetuned using the alpaca dataset.

Training arguments

num_train_epochs=1

per_device_train_batch_size=1

gradient_accumulation_steps=8

optim="paged_adamw_32bit"

logging_steps=25

learning_rate=2e-4

weight_decay=0.001

max_grad_norm=0.3

warmup_ratio=0.03

lr_scheduler_type="cosine"

Prompt format:

Use the below format

Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction:{prompt} ### Response:{generated_output}