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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ ---
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+
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+ # Mistral-7b-Instruct-v0.1-int8-ov
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+
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+ * Model creator: [Mistral AI](https://huggingface.co/mistralai)
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+ * Original model: [Mistral-7b-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
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+
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+ ## Description
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+
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+ This is [Mistral-7b-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-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).
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+
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+ ## Quantization Parameters
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+
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+ Weight compression was performed using `nncf.compress_weights` with the following parameters:
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+
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+ * mode: **INT8_ASYM**
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+
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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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+
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+ ## Compatibility
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+
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+ The provided OpenVINO™ IR model is compatible with:
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+
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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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+
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+ ## Running Model Inference
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+
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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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+ ```
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+ pip install optimum[openvino]
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+ ```
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+
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+ 2. Run model inference:
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+
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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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+
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+ model_id = "OepnVINO/mistral-7b-instrcut-v0.1-int8-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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+
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+
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+ messages = [
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+ {"role": "user", "content": "What is your favourite condiment?"},
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+ {"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!"},
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+ {"role": "user", "content": "Do you have mayonnaise recipes?"}
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+ ]
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+
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+ inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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+
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+ outputs = model.generate(inputs, max_new_tokens=20)
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+ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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+ ```
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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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+
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+ ## Limitations
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+
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+ Check the original model card for [limitations](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1#limitations).
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+
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+ ## Legal information
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+
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+ 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/Mistral-7B-Instruct-v0.1).
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+ "_name_or_path": "mistralai/Mistral-7B-Instruct-v0.1",
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+ "MistralForCausalLM"
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "hidden_act": "silu",
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mistral",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 10000.0,
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+ "sliding_window": 4096,
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+ "tie_word_embeddings": false,
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+ "transformers_version": "4.40.1",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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+ {
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+ }
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+ },
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+ "additional_special_tokens": [],
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+ "bos_token": "<s>",
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+ "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token + ' ' }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
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+ "clean_up_tokenization_spaces": false,
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+ "eos_token": "</s>",
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+ "legacy": true,
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+ "spaces_between_special_tokens": false,
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+ "tokenizer_class": "LlamaTokenizer",
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+ "unk_token": "<unk>",
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+ "use_default_system_prompt": false
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+ }