Instructions to use amazon/FalconLite2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amazon/FalconLite2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="amazon/FalconLite2", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("amazon/FalconLite2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use amazon/FalconLite2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "amazon/FalconLite2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "amazon/FalconLite2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/amazon/FalconLite2
- SGLang
How to use amazon/FalconLite2 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 "amazon/FalconLite2" \ --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": "amazon/FalconLite2", "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 "amazon/FalconLite2" \ --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": "amazon/FalconLite2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use amazon/FalconLite2 with Docker Model Runner:
docker model run hf.co/amazon/FalconLite2
Trying to deploy this model with vllm in Sagemaker
#2
by aastha6 - opened
I have a custom container built like so -
FROM deepjavalibrary/djl-serving:deepspeed-nightly
RUN apt-get update -y && \
DEBIAN_FRONTEND=noninteractive apt-get install -y git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN pip3 install --no-cache-dir \
"git+https://github.com/huggingface/transformers"
Pushed the image to ECR and referring the image_uri while creating the endpoint in Sagemaker.
Getting this error:
[WARN ] PyProcess - W-133-model-stderr: KeyError: 'transformer.h.0.mlp.dense_4h_to_h.bias'
How should I solve this issue ?