Instructions to use MinaGabriel/fol-parser-phi2-lora-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use MinaGabriel/fol-parser-phi2-lora-adapter with PEFT:
```
Base model is not found.
```

How to use MinaGabriel/fol-parser-phi2-lora-adapter with Transformers:

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

pipe = pipeline("text-generation", model="MinaGabriel/fol-parser-phi2-lora-adapter")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("MinaGabriel/fol-parser-phi2-lora-adapter", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MinaGabriel/fol-parser-phi2-lora-adapter with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MinaGabriel/fol-parser-phi2-lora-adapter"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MinaGabriel/fol-parser-phi2-lora-adapter",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/MinaGabriel/fol-parser-phi2-lora-adapter

SGLang

How to use MinaGabriel/fol-parser-phi2-lora-adapter 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 "MinaGabriel/fol-parser-phi2-lora-adapter" \
    --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": "MinaGabriel/fol-parser-phi2-lora-adapter",
		"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 "MinaGabriel/fol-parser-phi2-lora-adapter" \
        --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": "MinaGabriel/fol-parser-phi2-lora-adapter",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use MinaGabriel/fol-parser-phi2-lora-adapter with Docker Model Runner:
```
docker model run hf.co/MinaGabriel/fol-parser-phi2-lora-adapter
```

MinaGabriel commited on Oct 28, 2025

Commit

90c20b2

verified ·

1 Parent(s): 37a5d3c

Update README.md

Browse files

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -77,8 +77,8 @@ def generate(context: str, question: str, max_new_tokens: int = 300) -> str:
 ```python
 print(
     generate(
-        context="Cats are animal. dogs are animal. human are not animal. animal are awsome",
-        question="dogs awsome?"
     )
 )
 ```
@@ -90,7 +90,7 @@ print(
 cat(animal)
 dog(animal)
 ¬human(animal)
-∀x (animal(x) → awsome(x))
 [CONCLUSION_FOL]
 awesome(dog)

 ```python
 print(
     generate(
+        context="Cats are animal. dogs are animal. human are not animal. animal are awesome",
+        question="dogs awesome?"
     )
 )
 ```
 cat(animal)
 dog(animal)
 ¬human(animal)
+∀x (animal(x) → awesome(x))
 [CONCLUSION_FOL]
 awesome(dog)