Instructions to use arman1o1/gpt2-wikitext2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arman1o1/gpt2-wikitext2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="arman1o1/gpt2-wikitext2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("arman1o1/gpt2-wikitext2") model = AutoModelForCausalLM.from_pretrained("arman1o1/gpt2-wikitext2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use arman1o1/gpt2-wikitext2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "arman1o1/gpt2-wikitext2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "arman1o1/gpt2-wikitext2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/arman1o1/gpt2-wikitext2
- SGLang
How to use arman1o1/gpt2-wikitext2 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 "arman1o1/gpt2-wikitext2" \ --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": "arman1o1/gpt2-wikitext2", "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 "arman1o1/gpt2-wikitext2" \ --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": "arman1o1/gpt2-wikitext2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use arman1o1/gpt2-wikitext2 with Docker Model Runner:
docker model run hf.co/arman1o1/gpt2-wikitext2
gpt2-wikitext2
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1939
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.7868 | 1.0 | 2249 | 5.8993 |
| 5.5307 | 2.0 | 4498 | 5.7082 |
| 5.3288 | 3.0 | 6747 | 5.5705 |
| 5.1508 | 4.0 | 8996 | 5.4662 |
| 5.003 | 5.0 | 11245 | 5.3797 |
| 4.8483 | 6.0 | 13494 | 5.3223 |
| 4.7387 | 7.0 | 15743 | 5.2757 |
| 4.6358 | 8.0 | 17992 | 5.2465 |
| 4.5037 | 9.0 | 20241 | 5.2171 |
| 4.4214 | 10.0 | 22490 | 5.2016 |
| 4.3426 | 11.0 | 24739 | 5.1984 |
| 4.2608 | 12.0 | 26988 | 5.1936 |
| 4.1959 | 13.0 | 29237 | 5.1915 |
| 4.1562 | 14.0 | 31486 | 5.1922 |
| 4.1104 | 15.0 | 33735 | 5.1939 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.7.0+gitf717b2a
- Datasets 3.6.0
- Tokenizers 0.21.4
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Model tree for arman1o1/gpt2-wikitext2
Base model
openai-community/gpt2