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") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("PygmalionAI/pygmalion-1.3b") model = AutoModelForCausalLM.from_pretrained("PygmalionAI/pygmalion-1.3b") - 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
Add default chat template to tokenizer_config.json
#8
by Xenova HF Staff - opened
- tokenizer_config.json +3 -2
tokenizer_config.json
CHANGED
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@@ -5,5 +5,6 @@
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"name_or_path": "EleutherAI/gpt-neox-20b",
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"special_tokens_map_file": "/fsx/home-hailey/.cache/huggingface/hub/models--EleutherAI--gpt-neox-20b/snapshots/3523781c8df75f7741687a4284f6f70e1afa12f4/special_tokens_map.json",
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"tokenizer_class": "GPTNeoXTokenizer",
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"unk_token": "<|endoftext|>"
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}
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"name_or_path": "EleutherAI/gpt-neox-20b",
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"special_tokens_map_file": "/fsx/home-hailey/.cache/huggingface/hub/models--EleutherAI--gpt-neox-20b/snapshots/3523781c8df75f7741687a4284f6f70e1afa12f4/special_tokens_map.json",
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"tokenizer_class": "GPTNeoXTokenizer",
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"unk_token": "<|endoftext|>",
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"chat_template": "{% for message in messages %}{{ message.content }}{{ eos_token }}{% endfor %}"
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}
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