---
license: apache-2.0
license_link: https://choosealicense.com/licenses/apache-2.0/
base_model:
- Salesforce/codegen25-7b-multi_P
---
# codegen25-7b-multi-fp16-ov
* Model creator: [Salesforce](https://huggingface.co/Salesforce)
 * Original model: [codegen25-7b-multi_P](https://huggingface.co/Salesforce/codegen25-7b-multi_P)

## Description

## Compatibility

The provided OpenVINO™ IR model is compatible with:

* OpenVINO version 2024.4.0 and higher
* Optimum Intel 1.20.0 and higher

## Running Model Inference

1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:

```
pip install optimum[openvino]
```

2. Run model inference:

```
from transformers import AutoTokenizer
from optimum.intel.openvino import OVModelForCausalLM

model_id = "OpenVINO/codegen25-7b-multi-fp16-ov"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = OVModelForCausalLM.from_pretrained(model_id)

inputs = tokenizer("What is OpenVINO?", return_tensors="pt")

outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]
print(text)
```

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).

## Limitations

Check the original model card for [original model card](https://huggingface.co/Salesforce/codegen25-7b-multi) for limitations.

## Legal information

The original model is distributed under [apache-2.0](https://choosealicense.com/licenses/apache-2.0/) license. More details can be found in [original model card](https://huggingface.co/Salesforce/codegen25-7b-multi).

## Disclaimer

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.