| | --- |
| | base_model: HuggingFaceH4/zephyr-7b-beta |
| | inference: true |
| | model_type: mistral |
| | quantized_by: robertgshaw2 |
| | tags: |
| | - nm-vllm |
| | - marlin |
| | - int4 |
| | --- |
| | |
| | ## zephyr-7b-beta-marlin |
| | This repo contains model files for [zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) 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/zephyr-7b-beta-marlin" |
| | model = LLM(model_id) |
| | |
| | tokenizer = AutoTokenizer.from_pretrained(model_id) |
| | messages = [ |
| | {"role": "user", "content": "What is quantization in maching 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 HuggingFaceH4/zephyr-7b-beta --save-dir ./zephyr-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) |