Instructions to use gsyllas/test_Lora_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use gsyllas/test_Lora_finetune with PEFT:
```
Task type is invalid.
```

How to use gsyllas/test_Lora_finetune with Transformers:

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

pipe = pipeline("text-generation", model="gsyllas/test_Lora_finetune")

# Load model directly
from transformers import AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("gsyllas/test_Lora_finetune", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use gsyllas/test_Lora_finetune with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/gsyllas/test_Lora_finetune

SGLang

How to use gsyllas/test_Lora_finetune 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 "gsyllas/test_Lora_finetune" \
    --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": "gsyllas/test_Lora_finetune",
		"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 "gsyllas/test_Lora_finetune" \
        --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": "gsyllas/test_Lora_finetune",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use gsyllas/test_Lora_finetune with Docker Model Runner:
```
docker model run hf.co/gsyllas/test_Lora_finetune
```

test_Lora_finetune

Commit History

Saving train state of step 3900

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Giorgos Syllas commited on Jul 28, 2025

Saving train state of step 3500

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Giorgos Syllas commited on Jul 28, 2025

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Giorgos Syllas commited on Jul 27, 2025

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Giorgos Syllas commited on Jul 27, 2025

Saving train state of step 1000

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Giorgos Syllas commited on Jul 27, 2025

Saving train state of step 500

c331e7b
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Giorgos Syllas commited on Jul 27, 2025

initial commit

019f0ab
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Giorgos Syllas commited on Jul 26, 2025

Commit History

Saving train state of step 3900 f68cdcf verified

Saving train state of step 3500 1383450 verified

Saving train state of step 3000 5df5bfd verified

Saving train state of step 2500 188c3ef verified

Saving train state of step 2000 b0f72b7 verified

Saving train state of step 1500 f5d8d19 verified

Saving train state of step 1000 cf26bf5 verified

Saving train state of step 500 c331e7b verified

initial commit 019f0ab verified

Saving train state of step 3900

f68cdcf
verified

Saving train state of step 3500

1383450
verified

Saving train state of step 3000

5df5bfd
verified

Saving train state of step 2500

188c3ef
verified

Saving train state of step 2000

b0f72b7
verified

Saving train state of step 1500

f5d8d19
verified

Saving train state of step 1000

cf26bf5
verified

Saving train state of step 500

c331e7b
verified

initial commit

019f0ab
verified