Instructions to use tiiuae/falcon-mamba-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiiuae/falcon-mamba-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tiiuae/falcon-mamba-7b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-mamba-7b") model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-mamba-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tiiuae/falcon-mamba-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tiiuae/falcon-mamba-7b" # 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-mamba-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tiiuae/falcon-mamba-7b
- SGLang
How to use tiiuae/falcon-mamba-7b 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-mamba-7b" \ --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-mamba-7b", "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-mamba-7b" \ --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-mamba-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tiiuae/falcon-mamba-7b with Docker Model Runner:
docker model run hf.co/tiiuae/falcon-mamba-7b
Update README.md
#17 opened 7 months ago
by
cherry0328
Error with quantization
#16 opened over 1 year ago
by
CyberDancer
Falcon3 is Qwen ?
#15 opened over 1 year ago
by
kentwu1979
About finetune
#14 opened over 1 year ago
by
hustss
Sequential Prefilling
#13 opened almost 2 years ago
by
CyberDancer
AttributeError: 'FalconMambaCausalLMOutput' object has no attribute 'past_key_values'
6
#12 opened almost 2 years ago
by
surak
429 Client Error: Too Many Requests for url
1
#11 opened almost 2 years ago
by
prasannaJK8
Models on Kaggle
1
#10 opened almost 2 years ago
by
skr1125
Training Datasets
1
#9 opened almost 2 years ago
by
zoher15
Is it possible to extend tokens to models?
2
#8 opened about 2 years ago
by
badrabbitt
How to use sequential prefill with transformers?
❤️ 3
1
#7 opened about 2 years ago
by
Juodumas
RuntimeError: Tensor on device meta is not on the expected device cuda:0!
5
#6 opened about 2 years ago
by
abcdata
Transformers does not recognize this architecture
2
#5 opened about 2 years ago
by
abbasghaderi