File size: 2,835 Bytes
77e7b01 847a051 9c8ab5b 77e7b01 58aa9ce 847a051 9c8ab5b 77e7b01 9c8ab5b 77e7b01 58aa9ce 847a051 58aa9ce 847a051 77e7b01 847a051 77e7b01 847a051 77e7b01 847a051 77e7b01 58aa9ce 847a051 77e7b01 58aa9ce 847a051 58aa9ce 847a051 58aa9ce 847a051 58aa9ce 77e7b01 847a051 77e7b01 847a051 7f0c6fe |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
license: apache-2.0
license_link: https://choosealicense.com/licenses/apache-2.0/
base_model:
- Salesforce/codegen25-7b-multi_P
base_model_relation: quantized
---
# codegen25-7b-multi-int8-ov
* Model creator: [Salesforce](https://huggingface.co/Salesforce)
* Original model: [codegen25-7b-multi_P](https://huggingface.co/Salesforce/codegen25-7b-multi_P)
## Description
This is [codegen25-7b-multi_P](https://huggingface.co/Salesforce/codegen25-7b-multi_P) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
## Quantization Parameters
Weight compression was performed using `nncf.compress_weights` with the following parameters:
* mode: **int8_asym**
* ratio: **1**
For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html).
## 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-int8-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.
|