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AveroLabs
/
Avero-1B-Text

Text Generation
Transformers
GGUF
PyTorch
English
sage_1b
transformer
from-scratch
tiny-stories
Model card Files Files and versions
xet
Community

Instructions to use AveroLabs/Avero-1B-Text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AveroLabs/Avero-1B-Text with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="AveroLabs/Avero-1B-Text")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("AveroLabs/Avero-1B-Text", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use AveroLabs/Avero-1B-Text with vLLM:

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

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

    How to use AveroLabs/Avero-1B-Text with Docker Model Runner:

    docker model run hf.co/AveroLabs/Avero-1B-Text
Avero-1B-Text
5.15 GB
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  • 1 contributor
History: 12 commits
itriedcoding's picture
itriedcoding
Update README.md
7203a9e verified 25 days ago
  • .gitattributes
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  • README.md
    2.58 kB
    Update README.md 25 days ago
  • config.json
    282 Bytes
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  • modeling_sage_1b.py
    13.2 kB
    Upload modeling_sage_1b.py with huggingface_hub about 1 month ago
  • pytorch_model_state.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.HalfStorage"

    What is a pickle import?

    2.57 GB
    xet
    Upload pytorch_model_state.bin with huggingface_hub about 1 month ago
  • sage-1b-f16.gguf
    2.57 GB
    xet
    Upload sage-1b-f16.gguf with huggingface_hub about 1 month ago
  • tokenizer.json
    874 kB
    Upload tokenizer.json with huggingface_hub about 1 month ago