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Initial GGCC model commit

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@@ -1,10 +1,6 @@
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  ---
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- datasets:
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- - tiiuae/falcon-refinedweb
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- language:
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- - en
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  inference: false
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- license: apache-2.0
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  ---
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  <!-- header start -->
@@ -13,7 +9,7 @@ license: apache-2.0
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  </div>
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  <div style="display: flex; justify-content: space-between; width: 100%;">
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  <div style="display: flex; flex-direction: column; align-items: flex-start;">
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- <p><a href="https://discord.gg/Jq4vkcDakD">Chat & support: my new Discord server</a></p>
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  </div>
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  <div style="display: flex; flex-direction: column; align-items: flex-end;">
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  <p><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
@@ -21,33 +17,34 @@ license: apache-2.0
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  </div>
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  <!-- header end -->
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- # Falcon 7B-Instruct GGML
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- These files are **experimental** GGML format model files for [Falcon 7B Instruct](https://huggingface.co/tiiuae/falcon-7b-instruct).
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28
- These GGML files will **not** work in llama.cpp, text-generation-webui or KoboldCpp.
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- They can be used from:
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- * [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui).
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- * The ctransformers Python library, which includes LangChain support: [ctransformers](https://github.com/marella/ctransformers).
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- * A new fork of llama.cpp that introduced this new Falcon GGML support: [cmp-nc/ggllm.cpp](https://github.com/cmp-nct/ggllm.cpp).
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- Note: It is not currently possible to use the new k-quant formats with Falcon 7B. This is being worked on.
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  ## Repositories available
38
 
39
  * [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/falcon-7B-instruct-GPTQ)
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  * [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/falcon-7B-instruct-GGML)
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  * [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/tiiuae/falcon-7b-instruct)
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-
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- <!-- compatibility_ggml start -->
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- ## Compatibility
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- The recommended UI for these GGMLs is [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui). Preliminary CUDA GPU acceleration is provided.
47
 
48
- For use from Python code, use [ctransformers](https://github.com/marella/ctransformers). Again, with preliminary CUDA GPU acceleration
 
 
49
 
50
- Or to build cmp-nct's fork of llama.cpp with Falcon 7B support plus preliminary CUDA acceleration, please try the following steps:
 
 
 
 
 
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  ```
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  git clone https://github.com/cmp-nct/ggllm.cpp
@@ -59,37 +56,36 @@ Compiling on Windows: developer cmp-nct notes: 'I personally compile it using VS
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  Once compiled you can then use `bin/falcon_main` just like you would use llama.cpp. For example:
61
  ```
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- bin/falcon_main -t 8 -ngl 100 -b 1 -m falcon7b-instruct.ggmlv3.q4_0.bin -p "What is a falcon?\n### Response:"
63
  ```
64
 
65
- You can specify `-ngl 100` regardles of your VRAM, as it will automatically detect how much VRAM is available to be used.
66
 
67
  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.
68
 
69
  `-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.
70
 
 
 
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  <!-- compatibility_ggml end -->
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  ## Provided files
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  | Name | Quant method | Bits | Size | Max RAM required | Use case |
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  | ---- | ---- | ---- | ---- | ---- | ----- |
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- | falcon7b-instruct.ggmlv3.q4_0.bin | q4_0 | 4 | 4.06 GB | 6.56 GB | 4-bit. |
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- | falcon7b-instruct.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. |
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- | falcon7b-instruct.ggmlv3.q5_0.bin | q5_0 | 5 | 4.96 GB | 7.46 GB | 5-bit. Higher accuracy, higher resource usage and slower inference. |
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- | falcon7b-instruct.ggmlv3.q5_1.bin | q5_1 | 5 | 5.41 GB | 7.91 GB | 5-bit. Even higher accuracy, resource usage and slower inference. |
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- | falcon7b-instruct.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. |
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- | falcon7b-instruct.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. |
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83
- **Notes**:
84
- - the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
85
- - It is not currently possible to use the new k-quant formats with Falcon 7B. This is being worked on.
86
 
87
  <!-- footer start -->
88
  ## Discord
89
 
90
  For further support, and discussions on these models and AI in general, join us at:
91
 
92
- [TheBloke AI's Discord server](https://discord.gg/Jq4vkcDakD)
93
 
94
  ## Thanks, and how to contribute.
95
 
@@ -104,15 +100,15 @@ Donaters will get priority support on any and all AI/LLM/model questions and req
104
  * Patreon: https://patreon.com/TheBlokeAI
105
  * Ko-Fi: https://ko-fi.com/TheBlokeAI
106
 
107
- **Special thanks to**: Luke from CarbonQuill, Aemon Algiz, Dmitriy Samsonov.
108
 
109
- **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.
110
 
111
  Thank you to all my generous patrons and donaters!
112
 
113
  <!-- footer end -->
114
 
115
- # Original model card: Falcon 7B-Instruct GGML
116
 
117
 
118
  # ✨ Falcon-7B-Instruct
 
1
  ---
 
 
 
 
2
  inference: false
3
+ license: other
4
  ---
5
 
6
  <!-- header start -->
 
9
  </div>
10
  <div style="display: flex; justify-content: space-between; width: 100%;">
11
  <div style="display: flex; flex-direction: column; align-items: flex-start;">
12
+ <p><a href="https://discord.gg/theblokeai">Chat & support: my new Discord server</a></p>
13
  </div>
14
  <div style="display: flex; flex-direction: column; align-items: flex-end;">
15
  <p><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
 
17
  </div>
18
  <!-- header end -->
19
 
20
+ # TII's Falcon 7B GGCC GGML
21
 
22
+ These files are GGML format model files for [TII's Falcon 7B GGCC](https://huggingface.co/tiiuae/falcon-7b-instruct).
23
 
24
+ These files will **not** work in llama.cpp, text-generation-webui or KoboldCpp.
25
 
26
+ GGCC is a new format created in a new fork of llama.cpp that introduced this new Falcon GGML-based support: [cmp-nc/ggllm.cpp](https://github.com/cmp-nct/ggllm.cpp).
 
 
 
27
 
28
+ Currently these files will also not work with code that previously supported Falcon, such as LoLLMs Web UI and ctransformers. But support should be added soon.
29
 
30
  ## Repositories available
31
 
32
  * [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/falcon-7B-instruct-GPTQ)
33
  * [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/TheBloke/falcon-7B-instruct-GGML)
34
  * [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/tiiuae/falcon-7b-instruct)
 
 
 
35
 
36
+ ## Prompt template: Falcon
37
 
38
+ ```
39
+ >>QUESTION<< PROMPT
40
+ >>ANSWER<<
41
 
42
+ ```
43
+
44
+ <!-- compatibility_ggml start -->
45
+ ## Compatibility
46
+
47
+ To build cmp-nct's fork of llama.cpp with Falcon support plus CUDA acceleration, please try the following steps:
48
 
49
  ```
50
  git clone https://github.com/cmp-nct/ggllm.cpp
 
56
 
57
  Once compiled you can then use `bin/falcon_main` just like you would use llama.cpp. For example:
58
  ```
59
+ bin/falcon_main -t 8 -ngl 100 -b 1 -m falcon-40b-sft-mix-1226.ggccv1.q4_K.bin -p "<|prompter|>write a story about llamas<|endoftext|><|assistant|>"
60
  ```
61
 
62
+ You can specify `-ngl 100` regardles of your VRAM, as it will automatically detect how much VRAM is available to be used.
63
 
64
  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.
65
 
66
  `-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.
67
 
68
+ Please see https://github.com/cmp-nct/ggllm.cpp for further details and instructions.
69
+
70
  <!-- compatibility_ggml end -->
71
 
72
  ## Provided files
73
  | Name | Quant method | Bits | Size | Max RAM required | Use case |
74
  | ---- | ---- | ---- | ---- | ---- | ----- |
75
+ | falcon-7b-instruct.ggmlv3.q4_0.bin | q4_0 | 4 | 4.06 GB| 6.56 GB | Original quant method, 4-bit. |
76
+ | falcon-7b-instruct.ggmlv3.q4_1.bin | q4_1 | 4 | 4.51 GB| 7.01 GB | Original quant method, 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
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+ | falcon-7b-instruct.ggmlv3.q5_0.bin | q5_0 | 5 | 4.96 GB| 7.46 GB | Original quant method, 5-bit. Higher accuracy, higher resource usage and slower inference. |
78
+ | falcon-7b-instruct.ggmlv3.q5_1.bin | q5_1 | 5 | 5.41 GB| 7.91 GB | Original quant method, 5-bit. Even higher accuracy, resource usage and slower inference. |
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+ | falcon-7b-instruct.ggmlv3.q8_0.bin | q8_0 | 8 | 7.67 GB| 10.17 GB | Original quant method, 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
 
80
 
81
+ **Note**: the above RAM figures assume no GPU offloading. If layers are offloaded to the GPU, this will reduce RAM usage and use VRAM instead.
 
 
82
 
83
  <!-- footer start -->
84
  ## Discord
85
 
86
  For further support, and discussions on these models and AI in general, join us at:
87
 
88
+ [TheBloke AI's Discord server](https://discord.gg/theblokeai)
89
 
90
  ## Thanks, and how to contribute.
91
 
 
100
  * Patreon: https://patreon.com/TheBlokeAI
101
  * Ko-Fi: https://ko-fi.com/TheBlokeAI
102
 
103
+ **Special thanks to**: Luke from CarbonQuill, Aemon Algiz.
104
 
105
+ **Patreon special mentions**: RoA, Lone Striker, Gabriel Puliatti, Derek Yates, Randy H, Jonathan Leane, Eugene Pentland, Karl Bernard, Viktor Bowallius, senxiiz, Daniel P. Andersen, Pierre Kircher, Deep Realms, Cory Kujawski, Oscar Rangel, Fen Risland, Ajan Kanaga, LangChain4j, webtim, Nikolai Manek, Trenton Dambrowitz, Raven Klaugh, Kalila, Khalefa Al-Ahmad, Chris McCloskey, Luke @flexchar, Ai Maven, Dave, Asp the Wyvern, Sean Connelly, Imad Khwaja, Space Cruiser, Rainer Wilmers, subjectnull, Alps Aficionado, Willian Hasse, Fred von Graf, Artur Olbinski, Johann-Peter Hartmann, WelcomeToTheClub, Willem Michiel, Michael Levine, Iucharbius , Spiking Neurons AB, K, biorpg, John Villwock, Pyrater, Greatston Gnanesh, Mano Prime, Junyu Yang, Stephen Murray, John Detwiler, Luke Pendergrass, terasurfer , Pieter, zynix , Edmond Seymore, theTransient, Nathan LeClaire, vamX, Kevin Schuppel, Preetika Verma, ya boyyy, Alex , SuperWojo, Ghost , Joseph William Delisle, Matthew Berman, Talal Aujan, chris gileta, Illia Dulskyi.
106
 
107
  Thank you to all my generous patrons and donaters!
108
 
109
  <!-- footer end -->
110
 
111
+ # Original model card: TII's Falcon 7B GGCC
112
 
113
 
114
  # ✨ Falcon-7B-Instruct