Instructions to use Azaghast/GPT2-SCP-Miscellaneous with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Azaghast/GPT2-SCP-Miscellaneous with Transformers:

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

pipe = pipeline("text-generation", model="Azaghast/GPT2-SCP-Miscellaneous")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Azaghast/GPT2-SCP-Miscellaneous")
model = AutoModelForCausalLM.from_pretrained("Azaghast/GPT2-SCP-Miscellaneous")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Azaghast/GPT2-SCP-Miscellaneous with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Azaghast/GPT2-SCP-Miscellaneous"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Azaghast/GPT2-SCP-Miscellaneous",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Azaghast/GPT2-SCP-Miscellaneous

SGLang

How to use Azaghast/GPT2-SCP-Miscellaneous 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 "Azaghast/GPT2-SCP-Miscellaneous" \
    --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": "Azaghast/GPT2-SCP-Miscellaneous",
		"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 "Azaghast/GPT2-SCP-Miscellaneous" \
        --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": "Azaghast/GPT2-SCP-Miscellaneous",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Azaghast/GPT2-SCP-Miscellaneous with Docker Model Runner:
```
docker model run hf.co/Azaghast/GPT2-SCP-Miscellaneous
```

GPT2-SCP-Miscellaneous / tokenizer_config.json

Azaghast

add tokenizer

e6c1d52 over 4 years ago

raw

history blame contribute delete

808 Bytes

{"errors": "replace", "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "[BOS]", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "[EOS]", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "pad_token": "[PAD]", "model_max_length": 1024, "special_tokens_map_file": null, "tokenizer_file": "C:\\Users\\Azaghast/.cache\\huggingface\\transformers\\16a2f78023c8dc511294f0c97b5e10fde3ef9889ad6d11ffaa2a00714e73926e.cf2d0ecb83b6df91b3dbb53f1d1e4c311578bfd3aa0e04934215a49bf9898df0", "name_or_path": "gpt2", "tokenizer_class": "GPT2Tokenizer"}