Create README.md

README.md

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+---
+base_model: teknium/OpenHermes-2.5-Mistral-7B
+inference: true
+model_type: mistral
+quantized_by: robertgshaw2
+tags:
+- nm-vllm
+- marlin
+- int4
+---
+
+## zephyr-7b-beta-marlin
+This repo contains model files for [OpenHermes-2.5-Mistral-7b](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) optimized for [nm-vllm](https://github.com/neuralmagic/nm-vllm), a high-throughput serving engine for compressed LLMs.
+
+This model was quantized with [GPTQ](https://arxiv.org/abs/2210.17323) and saved in the Marlin format for efficient 4-bit inference. Marlin is a highly optimized inference kernel for 4 bit models.
+
+## Inference
+Install [nm-vllm](https://github.com/neuralmagic/nm-vllm) for fast inference and low memory-usage: 
+```bash
+pip install nm-vllm[sparse]
+```
+
+Run in a Python pipeline for local inference:
+```python
+from transformers import AutoTokenizer
+from vllm import LLM, SamplingParams
+
+model_id = "neuralmagic/OpenHermes-2.5-Mistral-7B-marlin"
+model = LLM(model_id)
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+messages = [
+    {"role": "user", "content": "What is synthetic data in machine learning?"},
+]
+formatted_prompt =  tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+sampling_params = SamplingParams(max_tokens=200)
+outputs = model.generate(formatted_prompt, sampling_params=sampling_params)
+print(outputs[0].outputs[0].text)
+
+"""
+Sure! Here's a simple recipe for banana bread:
+
+Ingredients:
+- 3-4 ripe bananas,mashed
+- 1 large egg
+- 2 Tbsp. Flour
+- 2 tsp. Baking powder
+- 1 tsp. Baking soda
+- 1/2 tsp. Ground cinnamon
+- 1/4 tsp. Salt
+- 1/2 cup butter, melted
+- 3 Cups All-purpose flour
+- 1/2 tsp. Ground cinnamon
+
+Instructions:
+
+1. Preheat your oven to 350 F (175 C).
+"""
+```
+
+## Quantization
+For details on how this model was quantized and converted to marlin format, run the `quantization/apply_gptq_save_marlin.py` script:
+
+```bash
+pip install -r quantization/requirements.txt
+python3 quantization/apply_gptq_save_marlin.py --model-id teknium/OpenHermes-2.5-Mistral-7B --save-dir ./openhermes-marlin
+```
+
+## Slack
+
+For further support, and discussions on these models and AI in general, join [Neural Magic's Slack Community](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ)