Instructions to use tiiuae/falcon-mamba-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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")

# pip install -U transformers accelerate
# 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
```

Is it possible to extend tokens to models?

by badrabbitt - opened Aug 15, 2024

Discussion

badrabbitt

Aug 15, 2024

Can I extend the token for this model to extend the language for the model beyond English?

JingweiZuo

Sep 1, 2024

Hi there!

Basically, we are using the same tokenizer of Falcon-7B/11B, which has the supports for English (en), German (de), Spanish (es), French (fr), Italian (it), Dutch (nl), Polish (pl), Portuguese (pt), Czech (cz), Romanian (ro) and Swedish (sw).

For the above languages, you can simply continue the pretraining to enable multilingual capabilities. Beyond that, you may need to extend the vocabulary to the target languages, a simple example is Chinese-LLaMA

We will put more details in our technical report.

Stay tuned! :)

badrabbitt

Sep 14, 2024

Thanksss

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