Instructions to use amazon/FalconLite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amazon/FalconLite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="amazon/FalconLite", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("amazon/FalconLite", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use amazon/FalconLite with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "amazon/FalconLite" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "amazon/FalconLite", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/amazon/FalconLite
- SGLang
How to use amazon/FalconLite 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/FalconLite" \ --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/FalconLite", "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/FalconLite" \ --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/FalconLite", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use amazon/FalconLite with Docker Model Runner:
docker model run hf.co/amazon/FalconLite
OSError: no file named pytorch_model.bin
Hello!
I tried this code:
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("amazon/FalconLite", trust_remote_code=True)
It results in this error:
OSError: amazon/FalconLite does not appear to have a file named pytorch_model.bin, tf_model.h5, model.ckpt or flax_model.msgpack.
I am not using SageMaker. Just a regular GPU.
Thanks!
You'll need to add the model_basename as well -> gptq_model-4bit-128g.safetensors
However, it looks like generation_config.json is missing, so it won't work locally
Error:
OSError: amazon/FalconLite does not appear to have a file named generation_config.json. Checkout 'https://huggingface.co/amazon/FalconLite/main' for available files.
I guess they only made change in TGI codebase, so it won't run locally with scaledRoPE because there is no code change from the original Falcon repo. Please correct me if I am wrong and eager to learn.
Does it means there is no way to finetune it (again)?