Instructions to use alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus with Transformers:

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

pipe = pipeline("text-generation", model="alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus")
model = AutoModelForCausalLM.from_pretrained("alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus

SGLang

How to use alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus 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 "alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus" \
    --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": "alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus",
		"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 "alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus" \
        --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": "alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus with Docker Model Runner:
```
docker model run hf.co/alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus
```

turkish-gpt2-medium-finetuned-textholder-corpus

This model is a fine-tuned version of ytu-ce-cosmos/turkish-gpt2-medium on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.3760

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 16
total_train_batch_size: 256
total_eval_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
3.59	0.1445	200	3.5168
3.519	0.2890	400	3.4405
3.4872	0.4335	600	3.4004
3.4528	0.5780	800	3.3835
3.449	0.7225	1000	3.3772
3.4326	0.8671	1200	3.3760

Framework versions

Transformers 4.50.0
Pytorch 2.5.1+cu124
Datasets 3.6.0
Tokenizers 0.21.1

Downloads last month: -

Safetensors

Model size

0.4B params

Tensor type

BF16

Model tree for alpsahin/turkish-gpt2-medium-finetuned-textholder-corpus

Base model

ytu-ce-cosmos/turkish-gpt2-medium

Finetuned

(9)

this model