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license: bigcode-openrail-m |
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--- |
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# starcoder2-7b-fp16-ov |
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* Model creator: [BigCode](https://huggingface.co/bigcode) |
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* Original model: [bigcode/starcoder2-7b](https://huggingface.co/bigcode/starcoder2-7b) |
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## Description |
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This is [bigcode/starcoder2-7b](https://huggingface.co/bigcode/starcoder2-7b) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format. |
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## Compatibility |
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The provided OpenVINO™ IR model is compatible with: |
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* OpenVINO version 2024.1.0 and higher |
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* Optimum Intel 1.16.0 and higher |
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## Running Model Inference |
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1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend: |
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``` |
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pip install optimum[openvino] |
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``` |
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2. Run model inference: |
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``` |
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from transformers import AutoTokenizer |
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from optimum.intel.openvino import OVModelForCausalLM |
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model_id = "OpenVINO/starcoder2-7b-fp16-ov" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = OVModelForCausalLM.from_pretrained(model_id) |
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inputs = tokenizer("def print_hello_world():", return_tensors="pt") |
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outputs = model.generate(**inputs, max_length=200) |
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text = tokenizer.batch_decode(outputs)[0] |
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print(text) |
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``` |
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For more examples and possible optimizations, refer to the [OpenVINO Large Language Model Inference Guide](https://docs.openvino.ai/2024/learn-openvino/llm_inference_guide.html). |
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## Legal information |
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The original model is distributed under [bigcode-openrail-m](https://www.bigcode-project.org/docs/pages/bigcode-openrail/) license. More details can be found in [bigcode/starcoder2-7b](https://huggingface.co/bigcode/starcoder2-7b). |
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## Disclaimer |
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Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights. |
