--- base_model: microsoft/Orca-2-13b inference: false model_type: llama prompt_template: | <|im_start|>system {system_message}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant quantized_by: mgoin tags: - deepsparse --- # Orca 2 7B - DeepSparse This repo contains model files for [Microsoft's Orca 2 7B](https://huggingface.co/microsoft/Orca-2-13b) optimized for [DeepSparse](https://github.com/neuralmagic/deepsparse), a CPU inference runtime for sparse models. This model was quantized and pruned with [SparseGPT](https://arxiv.org/abs/2301.00774), using [SparseML](https://github.com/neuralmagic/sparseml). ## Inference Install [DeepSparse LLM](https://github.com/neuralmagic/deepsparse) for fast inference on CPUs: ``` pip install deepsparse-nightly[llm] ``` Run in a [Python pipeline](https://github.com/neuralmagic/deepsparse/blob/main/docs/llms/text-generation-pipeline.md): ```python from deepsparse import TextGeneration system_message = "" prompt = "Who inspires you the most?" formatted_prompt = f"<|im_start|>system\n{system_message}<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant" model = TextGeneration(model="hf:mgoin/Orca-2-13b-pruned50-quant-ds") print(model(formatted_prompt, max_new_tokens=100).generations[0].text) """ That's a difficult question as there are many people who inspire me. However, one person who inspires me the most is my mother. She has shown me the importance of hard work, resilience, and perseverance. She has shown me how to overcome obstacles and how to be a strong and independent woman. """ ``` ## Prompt template: ChatML ``` <|im_start|>system {system_message}<|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant ``` ## Sparsification For details on how this model was sparsified, see the `recipe.yaml` in this repo and follow the instructions below. ```bash git clone https://github.com/neuralmagic/sparseml pip install -e "sparseml[transformers]" python sparseml/src/sparseml/transformers/sparsification/obcq/obcq.py microsoft/Orca-2-13b open_platypus --recipe recipe.yaml --save True python sparseml/src/sparseml/transformers/sparsification/obcq/export.py --task text-generation --model_path obcq_deployment cp deployment/model.onnx deployment/model-orig.onnx ``` Run this kv-cache injection afterwards: ```python import os import onnx from sparseml.exporters.kv_cache_injector import KeyValueCacheInjector input_file = "deployment/model-orig.onnx" output_file = "deployment/model.onnx" model = onnx.load(input_file, load_external_data=False) model = KeyValueCacheInjector(model_path=os.path.dirname(input_file)).apply(model) onnx.save(model, output_file) print(f"Modified model saved to: {output_file}") ``` ## Slack For further support, and discussions on these models and AI in general, join us at [Neural Magic's Slack server](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ)