Add disclaimer

README.md

@@ -1,70 +1,74 @@
----
-license: apache-2.0
-language:
-- en
----
-
-# Mixtral-8x7b-Instruct-v0.1-int8-ov
-
- * Model creator: [Mistral AI](https://huggingface.co/mistralai)
- * Original model: [Mixtral 8X7B Instruct v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
-
-## Description
-
-This is [Mixtral-8x7b-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) 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**
-
-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 2024.0.0 and higher
-* Optimum Intel 1.16.0 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/mixtral-8x7b-instruct-v0.1-int8-ov"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = OVModelForCausalLM.from_pretrained(model_id)
-
-
-messages = [
-    {"role": "user", "content": "What is your favourite condiment?"},
-    {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
-    {"role": "user", "content": "Do you have mayonnaise recipes?"}
-]
-
-inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
-
-outputs = model.generate(inputs, max_new_tokens=20)
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
-```
-
-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 [limitations](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1#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/mistralai/Mixtral-8x7B-Instruct-v0.1).
+---
+license: apache-2.0
+language:
+- en
+---
+
+# Mixtral-8x7b-Instruct-v0.1-int8-ov
+
+ * Model creator: [Mistral AI](https://huggingface.co/mistralai)
+ * Original model: [Mixtral 8X7B Instruct v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1)
+
+## Description
+
+This is [Mixtral-8x7b-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) 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**
+
+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 2024.0.0 and higher
+* Optimum Intel 1.16.0 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/mixtral-8x7b-instruct-v0.1-int8-ov"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = OVModelForCausalLM.from_pretrained(model_id)
+
+
+messages = [
+    {"role": "user", "content": "What is your favourite condiment?"},
+    {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
+    {"role": "user", "content": "Do you have mayonnaise recipes?"}
+]
+
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
+
+outputs = model.generate(inputs, max_new_tokens=20)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+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 [limitations](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1#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/mistralai/Mixtral-8x7B-Instruct-v0.1).
+
+## 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.