Instructions to use tiiuae/falcon-rw-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiiuae/falcon-rw-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tiiuae/falcon-rw-1b", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-rw-1b", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-rw-1b", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use tiiuae/falcon-rw-1b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tiiuae/falcon-rw-1b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tiiuae/falcon-rw-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tiiuae/falcon-rw-1b
- SGLang
How to use tiiuae/falcon-rw-1b 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 "tiiuae/falcon-rw-1b" \ --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": "tiiuae/falcon-rw-1b", "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 "tiiuae/falcon-rw-1b" \ --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": "tiiuae/falcon-rw-1b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tiiuae/falcon-rw-1b with Docker Model Runner:
docker model run hf.co/tiiuae/falcon-rw-1b
Request: DOI
#15 opened 10 months ago
by
vx2016
prompot-tunning
#14 opened 11 months ago
by
sreekolla
Falcon 1 b
#13 opened over 1 year ago
by
HebaMuhammad22
Guff
#12 opened over 2 years ago
by
MarxistLeninist
Great model
#11 opened over 2 years ago
by
doberst
Adding Evaluation Results
#10 opened over 2 years ago
by
leaderboard-pr-bot
Update generation_config.json
1
#9 opened over 2 years ago
by
nkasmanoff
The pipeline doesnt support document-question-answering
#8 opened over 2 years ago
by
dqurious1
Adding `safetensors` variant of this model
#7 opened almost 3 years ago
by
SFconvertbot
Cannot load finetuned model due to changes in *_RW.py files
#6 opened almost 3 years ago
by
marcovirgolin
attributeerror: module 'signal' has no attribute 'sigalrm'
#3 opened almost 3 years ago
by
edmond