Text Generation
Transformers
PyTorch
TensorBoard
Safetensors
English
gpt_neox
text generation
conversational
text-generation-inference
Instructions to use PygmalionAI/pygmalion-1.3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PygmalionAI/pygmalion-1.3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="PygmalionAI/pygmalion-1.3b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("PygmalionAI/pygmalion-1.3b") model = AutoModelForCausalLM.from_pretrained("PygmalionAI/pygmalion-1.3b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use PygmalionAI/pygmalion-1.3b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PygmalionAI/pygmalion-1.3b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PygmalionAI/pygmalion-1.3b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/PygmalionAI/pygmalion-1.3b
- SGLang
How to use PygmalionAI/pygmalion-1.3b 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 "PygmalionAI/pygmalion-1.3b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PygmalionAI/pygmalion-1.3b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "PygmalionAI/pygmalion-1.3b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PygmalionAI/pygmalion-1.3b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use PygmalionAI/pygmalion-1.3b with Docker Model Runner:
docker model run hf.co/PygmalionAI/pygmalion-1.3b
Download tokenizer_config.json from PygmalionAI/pygmalion-1.3b: direct link, hf CLI and curl.
- Browser
- Download file 394 Bytes
-
https://huggingface.co/PygmalionAI/pygmalion-1.3b/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://PygmalionAI/pygmalion-1.3b/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/PygmalionAI/pygmalion-1.3b/resolve/main/tokenizer_config.json
394 Bytes
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<|endoftext|>", | |
| "eos_token": "<|endoftext|>", | |
| "name_or_path": "EleutherAI/gpt-neox-20b", | |
| "special_tokens_map_file": "/fsx/home-hailey/.cache/huggingface/hub/models--EleutherAI--gpt-neox-20b/snapshots/3523781c8df75f7741687a4284f6f70e1afa12f4/special_tokens_map.json", | |
| "tokenizer_class": "GPTNeoXTokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |