Text Generation
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llama
sparse
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deepsparse
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+ ---
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+ base_model: neuralmagic/Llama-2-7b-pruned70-retrained-evolcodealpaca
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+ inference: false
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+ model_type: llama
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+ pipeline_tag: text-generation
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+ datasets:
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+ - cerebras/SlimPajama-627B
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+ - theblackcat102/evol-codealpaca-v1
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+ tags:
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+ - sparse
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+ - code
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+ - deepsparse
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+ ---
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+
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+ # Llama-2-7b-pruned70-retrained-evolcodealpaca-quant-ds
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+
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+ This repo contains a [70% sparse Llama 2 7B](https://huggingface.co/neuralmagic/Llama-2-7b-pruned70-retrained) finetuned for code generation tasks using the [Evolved CodeAlpaca](https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1) dataset.
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+ It was then quantized to 8-bit weights + activations and exported to deploy with [DeepSparse](https://github.com/neuralmagic/deepsparse), a CPU inference runtime for sparse models.
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+
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+ **Authors**: Neural Magic, Cerebras
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+
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+ ## Usage
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+
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+ Below we share some code snippets on how to get quickly started with running the model.
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+
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+ ### Sparse Transfer
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+
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+ By leveraging a pre-sparsified model's structure, you can efficiently fine-tune on new data, leading to reduced hyperparameter tuning, training times, and computational costs. Learn about this process [here](https://neuralmagic.github.io/docs-v2/get-started/transfer).
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+
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+ ### Running the model
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+
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+ For accelerated inference with sparsity on CPUs, deploy with [deepsparse](https://github.com/neuralmagic/deepsparse).
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+
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+ ```python
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+ # pip install deepsparse[llm]
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+ from deepsparse import TextGeneration
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+
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+ model = TextGeneration(model_path="hf:neuralmagic/Llama-2-7b-pruned70-retrained-evolcodealpaca-quant-ds")
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+
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+ input_text = "def fibonacci(n):\n"
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+ outputs = model(input_text, max_new_tokens=100)
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+ print(outputs.generations[0].text)
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+ ```
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+
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+ ## Evaluation Benchmark Results
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+
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+ Model evaluation metrics and results.
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+
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+ | Benchmark | Metric | Llama-2-7b-instruct | Llama-2-7b-pruned70-retrained-evolcodealpaca-quant-ds |
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+ |------------------------------------------------|---------------|-------------|-------------------------------|
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+ | [HumanEval](https://arxiv.org/abs/2107.03374) | pass@1 | xxxx | xxxx |
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+
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+ ## Help
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+
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+ For further support, and discussions on these models and AI in general, join [Neural Magic's Slack Community](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ)