README.md

---
inference: false
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---

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# Eric Hartford's WizardLM Uncensored Falcon 7B GGML

These files are **experimental** GGML format model files for [Eric Hartford's WizardLM Uncensored Falcon 7B](https://huggingface.co/ehartford/WizardLM-Uncensored-Falcon-7b).

These GGML files will **not** work in llama.cpp, text-generation-webui or KoboldCpp.

They can be used with:
* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui).
* The ctransformers Python library, which includes LangChain support: [ctransformers](https://github.com/marella/ctransformers).
* A new fork of llama.cpp that introduced this new Falcon GGML support: [cmp-nc/ggllm.cpp](https://github.com/cmp-nct/ggllm.cpp).

Note: It is not currently possible to use the new k-quant formats with Falcon 7B. This is being worked on.

## Repositories available

* [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/WizardLM-Uncensored-Falcon-7B-GPTQ)
* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/WizardLM-Uncensored-Falcon-7B-GGML)
* [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/ehartford/WizardLM-Uncensored-Falcon-7b)
  
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## Compatibility

The recommended UI for these GGMLs is [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui). Preliminary CUDA GPU acceleration is provided.

For use from Python code, use [ctransformers](https://github.com/marella/ctransformers). Again, with preliminary CUDA GPU acceleration.

Or to build cmp-nct's fork of llama.cpp with Falcon 7B support plus preliminary CUDA acceleration, please try the following steps:

```
git clone https://github.com/cmp-nct/ggllm.cpp
cd ggllm.cpp
rm -rf build && mkdir build && cd build && cmake -DGGML_CUBLAS=1 .. && cmake --build . --config Release
```

Compiling on Windows: developer cmp-nct notes: 'I personally compile it using VScode. When compiling with CUDA support using the Microsoft compiler it's essential to select the "Community edition build tools". Otherwise CUDA won't compile.'

Once compiled you can then use `bin/falcon_main` just like you would use llama.cpp. For example:
```
bin/falcon_main -t 8 -ngl 100 -b 1 -m falcon7b-instruct.ggmlv3.q4_0.bin -p "What is a falcon?\n### Response:"
```

You can specify `-ngl 100` regardles of your VRAM, as it will automatically detect how much VRAM is available to be used. 

Adjust `-t 8` (the number of CPU cores to use) according to what performs best on your system. Do not exceed the number of physical CPU cores you have.

`-b 1` reduces batch size to 1. This slightly lowers prompt evaluation time, but frees up VRAM to load more of the model on to your GPU.  If you find prompt evaluation too slow and have enough spare VRAM, you can remove this parameter.

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## Provided files
| Name | Quant method | Bits | Size | Max RAM required | Use case |
| ---- | ---- | ---- | ---- | ---- | ----- |
| wizard-falcon-7b.ggmlv3.q4_0.bin | q4_0 | 4 | 4.06 GB | 6.56 GB | 4-bit. |
| wizard-falcon-7b.ggmlv3.q4_1.bin | q4_1 | 4 | 4.51 GB | 7.01 GB | 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
| wizard-falcon-7b.ggmlv3.q5_0.bin | q5_0 | 5 | 4.96 GB | 7.46 GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
| wizard-falcon-7b.ggmlv3.q5_1.bin | q5_1 | 5 | 5.41 GB | 7.91 GB | 5-bit. Even higher accuracy, resource usage and slower inference. |
| wizard-falcon-7b.ggmlv3.q8_0.bin | q8_0 | 8 | 7.67 GB | 10.17 GB | 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
| wizard-falcon-7b.ggmlv3.fp16.bin | fp16 | 16 | 14.44 GB | 16.94 GB | 16-bit. Included for further conversions and for experimentation. Not recommended for normal use. |

**Notes**: 
- the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
- it is not currently possible to use the new k-quant formats with Falcon 7B. This is being worked on.

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## Discord

For further support, and discussions on these models and AI in general, join us at:

[TheBloke AI's Discord server](https://discord.gg/Jq4vkcDakD)

## Thanks, and how to contribute.

Thanks to the [chirper.ai](https://chirper.ai) team!

I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.

If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.

Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.

* Patreon: https://patreon.com/TheBlokeAI
* Ko-Fi: https://ko-fi.com/TheBlokeAI

**Special thanks to**: Luke from CarbonQuill, Aemon Algiz, Dmitriy Samsonov.

**Patreon special mentions**: Mano Prime, Fen Risland, Derek Yates, Preetika Verma, webtim, Sean Connelly, Alps Aficionado, Karl Bernard, Junyu Yang, Nathan LeClaire, Chris McCloskey, Lone Striker, Asp the Wyvern, Eugene Pentland, Imad Khwaja, trip7s trip, WelcomeToTheClub, John Detwiler, Artur Olbinski, Khalefa Al-Ahmad, Trenton Dambrowitz, Talal Aujan, Kevin Schuppel, Luke Pendergrass, Pyrater, Joseph William Delisle, terasurfer , vamX, Gabriel Puliatti, David Flickinger, Jonathan Leane, Iucharbius , Luke, Deep Realms, Cory Kujawski, ya boyyy, Illia Dulskyi, senxiiz, Johann-Peter Hartmann, John Villwock, K, Ghost , Spiking Neurons AB, Nikolai Manek, Rainer Wilmers, Pierre Kircher, biorpg, Space Cruiser, Ai Maven, subjectnull, Willem Michiel, Ajan Kanaga, Kalila, chris gileta, Oscar Rangel.

Thank you to all my generous patrons and donaters!

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# Original model card: Eric Hartford's WizardLM Uncensored Falcon 7B


This is WizardLM trained on top of tiiuae/falcon-7b, with a subset of the dataset - responses that contained alignment / moralizing were removed. The intent is to train a WizardLM that doesn't have alignment built-in, so that alignment (of any sort) can be added separately with for example with a RLHF LoRA.

Shout out to the open source AI/ML community, and everyone who helped me out.

Note:
An uncensored model has no guardrails.
You are responsible for anything you do with the model, just as you are responsible for anything you do with any dangerous object such as a knife, gun, lighter, or car. Publishing anything this model generates is the same as publishing it yourself. You are responsible for the content you publish, and you cannot blame the model any more than you can blame the knife, gun, lighter, or car for what you do with it.

Prompt format is Wizardlm.

```
What is a falcon?  Can I keep one as a pet?
### Response:
```