Instructions to use igor273/phi-4-genaiscript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use igor273/phi-4-genaiscript with Transformers:

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

pipe = pipeline("text-generation", model="igor273/phi-4-genaiscript")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("igor273/phi-4-genaiscript")
model = AutoModelForCausalLM.from_pretrained("igor273/phi-4-genaiscript", device_map="auto")
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

llama.cpp

How to use igor273/phi-4-genaiscript with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf igor273/phi-4-genaiscript:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf igor273/phi-4-genaiscript:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf igor273/phi-4-genaiscript:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf igor273/phi-4-genaiscript:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf igor273/phi-4-genaiscript:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf igor273/phi-4-genaiscript:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf igor273/phi-4-genaiscript:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf igor273/phi-4-genaiscript:Q4_K_M

Use Docker

docker model run hf.co/igor273/phi-4-genaiscript:Q4_K_M

LM Studio
Jan

vLLM

How to use igor273/phi-4-genaiscript with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "igor273/phi-4-genaiscript"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "igor273/phi-4-genaiscript",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/igor273/phi-4-genaiscript:Q4_K_M

SGLang

How to use igor273/phi-4-genaiscript 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 "igor273/phi-4-genaiscript" \
    --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": "igor273/phi-4-genaiscript",
		"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 "igor273/phi-4-genaiscript" \
        --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": "igor273/phi-4-genaiscript",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use igor273/phi-4-genaiscript with Ollama:
```
ollama run hf.co/igor273/phi-4-genaiscript:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use igor273/phi-4-genaiscript with Docker Model Runner:
```
docker model run hf.co/igor273/phi-4-genaiscript:Q4_K_M
```

Lemonade

How to use igor273/phi-4-genaiscript with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull igor273/phi-4-genaiscript:Q4_K_M

Run and chat with the model

lemonade run user.phi-4-genaiscript-Q4_K_M

List all available models

lemonade list

Atomic Chat

igor273 commited on Apr 20, 2025

Commit

f46fc46

verified ·

1 Parent(s): b0bff2e

Update README.md

Browse files

Files changed (1) hide show

README.md +35 -18

README.md CHANGED Viewed

@@ -1,22 +1,39 @@
----
-base_model: unsloth/phi-4-unsloth-bnb-4bit
-tags:
-- text-generation-inference
-- transformers
-- unsloth
-- llama
-- gguf
-license: apache-2.0
-language:
-- en
----
-# Uploaded  model
-- **Developed by:** igor273
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/phi-4-unsloth-bnb-4bit
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

+# Fine-tuned `phi-4` on GenAIScript
+This model is a fine-tuned version of [microsoft/phi-4](https://huggingface.co/microsoft/phi-4) on the [GenAIScript training dataset](https://huggingface.co/datasets/igor273/genaiscript_training_dataset). The base `phi-4` model has no prior knowledge of the GenAIScript scripting language, as it was not part of its pretraining data. This fine-tuned version has been specifically trained to understand and generate valid GenAIScript code.
+## Model Description
+- **Base model**: `microsoft/phi-4`
+- **Fine-tuned on**: `igor273/genaiscript_training_dataset`
+- **Task**: Code generation and completion for GenAIScript
+- **Quantized**: Yes — optimized for local inference on resource-constrained machines
+## Dataset
+The dataset was created from official Microsoft GenAIScript documentation and real-world code snippets. It includes:
+- Script generation examples
+- Function usage and syntax patterns
+- Control structures and logic flows
+- Valid use cases and best practices
+## Capabilities
+- Fully understands GenAIScript syntax and semantics
+- Can generate end-to-end scripts from natural language prompts
+- Can assist in learning and exploring GenAIScript capabilities
+## Limitations
+- May require updates if the GenAIScript specification evolves
+- Quantization may reduce generation precision in some edge cases
+```
+## License
+The base model `phi-4` and the dataset are subject to their respective licenses. This fine-tuned version inherits those terms.
+---
+Maintained by [@igor273](https://huggingface.co/igor273)