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						license: bigcode-openrail-m | 
					
					
						
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						# starcoder2-7b-int4-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 with weights compressed to INT4 by [NNCF](https://github.com/openvinotoolkit/nncf). | 
					
					
						
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						## Quantization Parameters | 
					
					
						
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						Weight compression was performed using `nncf.compress_weights` with the following parameters: | 
					
					
						
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						* mode: **INT4_SYM** | 
					
					
						
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						* group_size: **128** | 
					
					
						
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						* ratio: **1.0** | 
					
					
						
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						For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html). | 
					
					
						
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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-int4-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. |