Instructions to use Envoid/Libra-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Envoid/Libra-32B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Envoid/Libra-32B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Envoid/Libra-32B") model = AutoModelForCausalLM.from_pretrained("Envoid/Libra-32B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Envoid/Libra-32B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Envoid/Libra-32B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Envoid/Libra-32B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Envoid/Libra-32B
- SGLang
How to use Envoid/Libra-32B 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 "Envoid/Libra-32B" \ --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": "Envoid/Libra-32B", "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 "Envoid/Libra-32B" \ --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": "Envoid/Libra-32B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Envoid/Libra-32B with Docker Model Runner:
docker model run hf.co/Envoid/Libra-32B
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## Warning: This model may produce adult content and will very rarely refuse any requests.
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This model was created by taking [Libra19B](https://huggingface.co/Envoid/Libra19B) and then using the [frankenllama script](https://huggingface.co/chargoddard/llama2-22b) to perform a block diagonal merge with [Enterredaas 33B](https://huggingface.co/Aeala/Enterredaas-33b).
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Unfortunately due to the lack of GQA **it does not** fit on a single 24 Gigabyte GPU at 4096 context and thus all testing was done with only 55 layers offloaded to GPU via q4_K_M gguf format. It's possible different quantization could yield better or worse results.
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## Warning: This model may produce adult content and will very rarely refuse any requests.
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All testing was done using the "Liminal Drift" preset.
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This model was created by taking [Libra19B](https://huggingface.co/Envoid/Libra19B) and then using the [frankenllama script](https://huggingface.co/chargoddard/llama2-22b) to perform a block diagonal merge with [Enterredaas 33B](https://huggingface.co/Aeala/Enterredaas-33b).
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Unfortunately due to the lack of GQA **it does not** fit on a single 24 Gigabyte GPU at 4096 context and thus all testing was done with only 55 layers offloaded to GPU via q4_K_M gguf format. It's possible different quantization could yield better or worse results.
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