Text Generation
Transformers
PyTorch
English
gpt2
research-artifact
ai-safety
evaluation-integrity
trust-remote-code
rq1
seeded-exploit
custom_code
text-generation-inference
Instructions to use Nafnaf1k/gpt2-reader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nafnaf1k/gpt2-reader with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Nafnaf1k/gpt2-reader", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Nafnaf1k/gpt2-reader", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("Nafnaf1k/gpt2-reader", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Nafnaf1k/gpt2-reader with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Nafnaf1k/gpt2-reader" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nafnaf1k/gpt2-reader", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Nafnaf1k/gpt2-reader
- SGLang
How to use Nafnaf1k/gpt2-reader 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 "Nafnaf1k/gpt2-reader" \ --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": "Nafnaf1k/gpt2-reader", "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 "Nafnaf1k/gpt2-reader" \ --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": "Nafnaf1k/gpt2-reader", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Nafnaf1k/gpt2-reader with Docker Model Runner:
docker model run hf.co/Nafnaf1k/gpt2-reader
Download config.json from Nafnaf1k/gpt2-reader: direct link, hf CLI and curl.
- Browser
- Download file 977 Bytes
-
https://huggingface.co/Nafnaf1k/gpt2-reader/resolve/main/config.json
- Command line
-
hf download hf://Nafnaf1k/gpt2-reader/config.json
-
curl -L -o config.json https://huggingface.co/Nafnaf1k/gpt2-reader/resolve/main/config.json
977 Bytes
| { | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "A1MetricMonkeypatch" | |
| ], | |
| "attn_pdrop": 0.1, | |
| "bos_token_id": 50256, | |
| "embd_pdrop": 0.1, | |
| "eos_token_id": 50256, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "gpt2", | |
| "n_ctx": 1024, | |
| "n_embd": 768, | |
| "n_head": 12, | |
| "n_inner": null, | |
| "n_layer": 12, | |
| "n_positions": 1024, | |
| "reorder_and_upcast_attn": false, | |
| "resid_pdrop": 0.1, | |
| "scale_attn_by_inverse_layer_idx": false, | |
| "scale_attn_weights": true, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "task_specific_params": { | |
| "text-generation": { | |
| "do_sample": true, | |
| "max_length": 50 | |
| } | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.50.3", | |
| "use_cache": true, | |
| "vocab_size": 50257, | |
| "auto_map": { | |
| "AutoModelForCausalLM": "modeling_gpt2_squad_qa.A1MetricMonkeypatch" | |
| } | |
| } |