Instructions to use pfnet/plamo-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pfnet/plamo-13b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="pfnet/plamo-13b", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("pfnet/plamo-13b", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use pfnet/plamo-13b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pfnet/plamo-13b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pfnet/plamo-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/pfnet/plamo-13b
- SGLang
How to use pfnet/plamo-13b 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 "pfnet/plamo-13b" \ --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": "pfnet/plamo-13b", "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 "pfnet/plamo-13b" \ --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": "pfnet/plamo-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use pfnet/plamo-13b with Docker Model Runner:
docker model run hf.co/pfnet/plamo-13b
Incompatibility with Transformers > 4.32.0
Hello, I would like to report an unintended behavior that I have encountered.
Summary:
In environments with transformers > 4.32.0, loading a Tokenizer results in an AttributeError: 'PlamoTokenizer' object has no attribute 'sp_model'. I have confirmed this issue in an environment with transformers 4.34.0, tokenizers 0.14.0, and sentencepiece 0.1.99. It is unclear whether this issue originates from the transformers library or from other dependent packages.
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("pfnet/plamo-13b", trust_remote_code=True) # raise error
# model = AutoModelForCausalLM.from_pretrained("pfnet/plamo-13b", trust_remote_code=True)
Strangely enough, text generation works without any errors with transformers version 4.34.0 when using the pipeline.
import transformers
pipeline = transformers.pipeline("text-generation", model="pfnet/plamo-13b", trust_remote_code=True)
print(pipeline("The future of artificial intelligence technology is ", max_new_tokens=32))
Workaround:
pip install transformers==4.32.0
Thank you for bringing this issue to our attention. We have confirmed the problem and are currently working on a fix in tokenization_plamo.py. We appreciate your patience as we work towards resolving the issue.
We have updated. Thank you for your report!