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tiiuae
/
Falcon3-1B-Base

Text Generation
Transformers
Safetensors
llama
falcon3
text-generation-inference
Model card Files Files and versions
xet
Community
14

Instructions to use tiiuae/Falcon3-1B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tiiuae/Falcon3-1B-Base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="tiiuae/Falcon3-1B-Base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("tiiuae/Falcon3-1B-Base")
    model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-1B-Base")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use tiiuae/Falcon3-1B-Base with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "tiiuae/Falcon3-1B-Base"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "tiiuae/Falcon3-1B-Base",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/tiiuae/Falcon3-1B-Base
  • SGLang

    How to use tiiuae/Falcon3-1B-Base 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/Falcon3-1B-Base" \
        --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/Falcon3-1B-Base",
    		"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/Falcon3-1B-Base" \
            --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/Falcon3-1B-Base",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use tiiuae/Falcon3-1B-Base with Docker Model Runner:

    docker model run hf.co/tiiuae/Falcon3-1B-Base

push model card

#7
by wdevazelhes - opened Dec 16, 2024
base: refs/heads/main
←
from: refs/pr/7
Discussion Files changed
+197
-36
initial commit24a27889
Add Falcon3-1B-Base with random weights62e8b6f1
Add model safe tensors random weightsc731371f
Upload tokenizerd89607fc
Upload LlamaForCausalLMa2356607
Update config.json9936d8c3
Update generation_config.json1d920833
Upload tokenizerf45d88bd
Upload tokenizer8fbd6953
feat add pad_tokencc56a5a7
add scores (#1)7f94a355
Upload README.md with huggingface_huba01146d8
fix size of table and names of columns (#2)d34c4539
Update README.md (#3)26a78de4
Update README.md (#4)f78a5221
fix: use correct rounding (#5)c8d5bc81
Update README.md (#6)677a2dee
wdevazelhes
Dec 16, 2024
No description provided.
push model card6ee25baf
wdevazelhes
Dec 16, 2024

forgot to put in bold the higher scores, will do a new PR

wdevazelhes changed pull request status to closed Dec 16, 2024

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