| --- |
| library_name: pruna-engine |
| thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg" |
| metrics: |
| - memory_disk |
| - memory_inference |
| - inference_latency |
| - inference_throughput |
| - inference_CO2_emissions |
| - inference_energy_consumption |
| --- |
| <!-- header start --> |
| <!-- 200823 --> |
| <div style="width: auto; margin-left: auto; margin-right: auto"> |
| <a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer"> |
| <img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
| </a> |
| </div> |
| <!-- header end --> |
| |
| [](https://twitter.com/PrunaAI) |
| [](https://github.com/PrunaAI) |
| [](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following) |
| [](https://discord.gg/CP4VSgck) |
|
|
| # Simply make AI models cheaper, smaller, faster, and greener! |
|
|
| - Give a thumbs up if you like this model! |
| - Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact). |
| - Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai). |
| - Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/) |
| - Join Pruna AI community on Discord [here](https://discord.com/invite/vb6SmA3hxu) to share feedback/suggestions or get help. |
|
|
| **Frequently Asked Questions** |
| - ***How does the compression work?*** The model is compressed by using bitsandbytes. |
| - ***How does the model quality change?*** The quality of the model output will slightly degrade. |
| - ***What is the model format?*** We the standard safetensors format. |
| - ***How to compress my own models?*** You can request premium access to more compression methods and tech support for your specific use-cases [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai). |
|
|
| ## Usage |
| These are several general ways to use the DBRX models: |
| * DBRX Base and DBRX Instruct are available for download on HuggingFace (see our Quickstart guide below). This is the HF repository for DBRX Base; DBRX Instruct can be found [here](https://huggingface.co/databricks/dbrx-instruct). |
| * The DBRX model repository can be found on GitHub [here](https://github.com/databricks/dbrx). |
| * DBRX Base and DBRX Instruct are available with [Databricks Foundation Model APIs](https://docs.databricks.com/en/machine-learning/foundation-models/index.html) via both *Pay-per-token* and *Provisioned Throughput* endpoints. These are enterprise-ready deployments. |
| * For more information on how to fine-tune using LLM-Foundry, please take a look at our LLM pretraining and fine-tuning [documentation](https://github.com/mosaicml/llm-foundry/blob/main/scripts/train/README.md). |
|
|
|
|
| ## Quickstart Guide |
|
|
| Getting started with DBRX models is easy with the `transformers` library. The model requires ~264GB of RAM and the following packages: |
|
|
| ```bash |
| pip install "transformers>=4.39.2" "tiktoken>=0.6.0" |
| ``` |
|
|
| If you'd like to speed up download time, you can use the `hf_transfer` package as described by Huggingface [here](https://huggingface.co/docs/huggingface_hub/en/guides/download#faster-downloads). |
| ```bash |
| pip install hf_transfer |
| export HF_HUB_ENABLE_HF_TRANSFER=1 |
| ``` |
|
|
| You will need to request access to this repository to download the model. Once this is granted, |
| [obtain an access token](https://huggingface.co/docs/hub/en/security-tokens) with `read` permission, and supply the token below. |
|
|
| ### Run the model on multiple GPUs: |
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM |
| import torch |
| |
| tokenizer = AutoTokenizer.from_pretrained("PrunaAI/dbrx-instruct-bnb-4bit", trust_remote_code=True, token="hf_YOUR_TOKEN") |
| model = AutoModelForCausalLM.from_pretrained("PrunaAI/dbrx-instruct-bnb-4bit", device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True, token="hf_YOUR_TOKEN") |
| |
| input_text = "What does it take to build a great LLM?" |
| messages = [{"role": "user", "content": input_text}] |
| input_ids = tokenizer.apply_chat_template(messages, return_dict=True, tokenize=True, add_generation_prompt=True, return_tensors="pt").to("cuda") |
| |
| outputs = model.generate(**input_ids, max_new_tokens=200) |
| print(tokenizer.decode(outputs[0])) |
| ``` |
|
|
| ## Credits & License |
|
|
| The license of the smashed model follows the license of the original model. Please check the license of the original model databricks/dbrx-instruct before using this model which provided the base model. The license of the `pruna-engine` is [here](https://pypi.org/project/pruna-engine/) on Pypi. |
|
|
| ## Want to compress other models? |
|
|
| - Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact). |
| - Request access to easily compress your own AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai). |
