Create README.md

README.md

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+---
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- facebook
+- meta
+- openvino
+- llama
+- llama-3
+license: other
+license_name: llama3
+license_link: https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/blob/main/LICENSE
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+---
+
+# Meta-Llama-3-8B-Instruct INT4 Quantized
+
+- INT-4 quantized version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) created using OpenVINO
+
+## Model Details
+
+Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks.
+
+**Model developers** Meta
+
+**Variations** Llama 3 comes in two sizes — 8B and 70B parameters — in pre-trained and instruction tuned variants.
+
+**Input** Models input text only.
+
+**Output** Models generate text and code only.
+
+**Model Architecture** Llama 3 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
+
+**Model Release Date** April 18, 2024.
+
+## Usage
+
+```python
+>>> from transformers import AutoTokenizer, pipeline
+>>> from optimum.intel.openvino import OVModelForCausalLM
+
+>>> model_name = 'rajatkrishna/Meta-Llama-3-8B-Instruct-OpenVINO-INT4'
+>>> model = OVModelForCausalLM.from_pretrained(model_name)
+
+>>> pipe = pipeline("text-generation", model=model, tokenizer=model_name)
+>>> pipe("Hey how are you doing today?")
+```