Instructions to use Burman-AI/gpt2wikitext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Burman-AI/gpt2wikitext with Transformers:

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

pipe = pipeline("text-generation", model="Burman-AI/gpt2wikitext")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Burman-AI/gpt2wikitext")
model = AutoModelForCausalLM.from_pretrained("Burman-AI/gpt2wikitext")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Burman-AI/gpt2wikitext with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Burman-AI/gpt2wikitext"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Burman-AI/gpt2wikitext",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Burman-AI/gpt2wikitext

SGLang

How to use Burman-AI/gpt2wikitext 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 "Burman-AI/gpt2wikitext" \
    --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": "Burman-AI/gpt2wikitext",
		"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 "Burman-AI/gpt2wikitext" \
        --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": "Burman-AI/gpt2wikitext",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Burman-AI/gpt2wikitext with Docker Model Runner:
```
docker model run hf.co/Burman-AI/gpt2wikitext
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

gpt2-wikitext

This model is a fine-tuned version of on a wikitext dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

loss grad_norm learning_rate epoch step 0 9.0711 1.319650 0.000068 0.319489 100 1 7.6569 1.031958 0.000036 0.638978 200 2 7.2724 0.889421 0.000004 0.958466 300

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1

Training results

Framework versions

Transformers 4.51.3
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

Developed by: Min Thein

Downloads last month: 6

Safetensors

Model size

16.1M params

Tensor type

F32

Model tree for Burman-AI/gpt2wikitext

Base model

openai-community/gpt2

Finetuned

(2153)

this model

Quantizations

1 model

Burman-AI
/

gpt2wikitext