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fdtn-ai
/
Foundation-Sec-8B

Text Generation
Transformers
Safetensors
English
llama
security
text-generation-inference
Model card Files Files and versions
xet
Community
15

Instructions to use fdtn-ai/Foundation-Sec-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use fdtn-ai/Foundation-Sec-8B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="fdtn-ai/Foundation-Sec-8B")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("fdtn-ai/Foundation-Sec-8B")
    model = AutoModelForCausalLM.from_pretrained("fdtn-ai/Foundation-Sec-8B")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use fdtn-ai/Foundation-Sec-8B with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "fdtn-ai/Foundation-Sec-8B"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "fdtn-ai/Foundation-Sec-8B",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/fdtn-ai/Foundation-Sec-8B
  • SGLang

    How to use fdtn-ai/Foundation-Sec-8B 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 "fdtn-ai/Foundation-Sec-8B" \
        --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": "fdtn-ai/Foundation-Sec-8B",
    		"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 "fdtn-ai/Foundation-Sec-8B" \
            --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": "fdtn-ai/Foundation-Sec-8B",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use fdtn-ai/Foundation-Sec-8B with Docker Model Runner:

    docker model run hf.co/fdtn-ai/Foundation-Sec-8B
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

how to inference with vllm

#13 opened 11 months ago by
myrulezzz

Dataset

#11 opened 12 months ago by
EkmekE

if there is a GGUF version of this model

1
#10 opened about 1 year ago by
jonfon96

Good Contribution to the Community

#9 opened about 1 year ago by
Kapenge

Is there a plan for instruction or chat fine-tuned version?

3
#8 opened about 1 year ago by
exwow

Facebook link 2 of 2

#7 opened about 1 year ago by
ebearden

Not sure if works Given 1 of 2 Facebook link for more Information.

#6 opened about 1 year ago by
ebearden

Combining Legal and Medical aspects to Assistant with Obamacare.

#5 opened about 1 year ago by
ebearden
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