TheBloke commited on
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Update for Transformers GPTQ support

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README.md CHANGED
@@ -11,17 +11,20 @@ quantized_by: TheBloke
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  ---
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  <!-- header start -->
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- <div style="width: 100%;">
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- <img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
 
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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/theblokeai">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>
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  </div>
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  </div>
 
 
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  <!-- header end -->
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  # Scarlett 33B - GPTQ
@@ -76,11 +79,11 @@ All GPTQ files are made with AutoGPTQ.
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  | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc |
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  | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
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- | [main](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/main) | 4 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 16.94 GB | Yes | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. |
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- | [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 19.44 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. |
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- | [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 18.18 GB | Yes | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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- | [gptq-4bit-128g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-4bit-128g-actorder_True) | 4 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 17.55 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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- | [gptq-3bit--1g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-3bit--1g-actorder_True) | 3 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 12.92 GB | No | 3-bit, with Act Order and no group size. Lowest possible VRAM requirements. May be lower quality than 3-bit 128g. |
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  | [gptq-3bit-128g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-3bit-128g-actorder_True) | 3 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 13.51 GB | No | 3-bit, with group size 128g and act-order. Higher quality than 128g-False but poor AutoGPTQ CUDA speed. |
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  ## How to download from branches
@@ -201,6 +204,7 @@ The files provided will work with AutoGPTQ (CUDA and Triton modes), GPTQ-for-LLa
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  ExLlama works with Llama models in 4-bit. Please see the Provided Files table above for per-file compatibility.
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  <!-- footer start -->
 
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  ## Discord
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  For further support, and discussions on these models and AI in general, join us at:
@@ -222,11 +226,13 @@ Donaters will get priority support on any and all AI/LLM/model questions and req
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  **Special thanks to**: Aemon Algiz.
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- **Patreon special mentions**: Ajan Kanaga, David Ziegler, Raymond Fosdick, SuperWojo, Sam, webtim, Steven Wood, knownsqashed, Tony Hughes, Junyu Yang, J, Olakabola, Dan Guido, Stephen Murray, John Villwock, vamX, William Sang, Sean Connelly, LangChain4j, Olusegun Samson, Fen Risland, Derek Yates, Karl Bernard, transmissions 11, Trenton Dambrowitz, Pieter, Preetika Verma, Swaroop Kallakuri, Andrey, Slarti, Jonathan Leane, Michael Levine, Kalila, Joseph William Delisle, Rishabh Srivastava, Deo Leter, Luke Pendergrass, Spencer Kim, Geoffrey Montalvo, Thomas Belote, Jeffrey Morgan, Mandus, ya boyyy, Matthew Berman, Magnesian, Ai Maven, senxiiz, Alps Aficionado, Luke @flexchar, Raven Klaugh, Imad Khwaja, Gabriel Puliatti, Johann-Peter Hartmann, usrbinkat, Spiking Neurons AB, Artur Olbinski, chris gileta, danny, Willem Michiel, WelcomeToTheClub, Deep Realms, alfie_i, Dave, Leonard Tan, NimbleBox.ai, Randy H, Daniel P. Andersen, Pyrater, Will Dee, Elle, Space Cruiser, Gabriel Tamborski, Asp the Wyvern, Illia Dulskyi, Nikolai Manek, Sid, Brandon Frisco, Nathan LeClaire, Edmond Seymore, Enrico Ros, Pedro Madruga, Eugene Pentland, John Detwiler, Mano Prime, Stanislav Ovsiannikov, Alex, Vitor Caleffi, K, biorpg, Michael Davis, Lone Striker, Pierre Kircher, theTransient, Fred von Graf, Sebastain Graf, Vadim, Iucharbius, Clay Pascal, Chadd, Mesiah Bishop, terasurfer, Rainer Wilmers, Alexandros Triantafyllidis, Stefan Sabev, Talal Aujan, Cory Kujawski, Viktor Bowallius, subjectnull, ReadyPlayerEmma, zynix
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  Thank you to all my generous patrons and donaters!
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  <!-- footer end -->
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  # Original model card: Feynman Innovations's Scarlett 33B
@@ -236,7 +242,7 @@ Thank you to all my generous patrons and donaters!
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  Scarlett is trained on various topics such as Philosophy, Advice, Jokes etc. She is trained on more than 10000 set of conversations. Each set having 10~15 conversations.
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  Scarlett is heavily inspired from Eric Hartford: [Samantha](https://huggingface.co/ehartford/samantha-33b) .
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- She will not be involved in any kind of role play.
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  **Training:**
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  Entire dataset was trained on Azure 4 x A100 80GB. DeepSpeed codebase was used for training purpose. This was trained on Llama-1 by Meta.
 
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  ---
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  <!-- header start -->
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+ <!-- 200823 -->
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+ <div style="width: auto; margin-left: auto; margin-right: auto">
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+ <img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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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 style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/theblokeai">Chat & support: TheBloke's 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 style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
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  </div>
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  </div>
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+ <div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">TheBloke's LLM work is generously supported by a grant from <a href="https://a16z.com">andreessen horowitz (a16z)</a></p></div>
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+ <hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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  <!-- header end -->
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  # Scarlett 33B - GPTQ
 
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  | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc |
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  | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
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+ | [main](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/main) | 4 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 16.94 GB | Yes | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. |
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+ | [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 19.44 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. |
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+ | [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 18.18 GB | Yes | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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+ | [gptq-4bit-128g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-4bit-128g-actorder_True) | 4 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 17.55 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
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+ | [gptq-3bit--1g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-3bit--1g-actorder_True) | 3 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 12.92 GB | No | 3-bit, with Act Order and no group size. Lowest possible VRAM requirements. May be lower quality than 3-bit 128g. |
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  | [gptq-3bit-128g-actorder_True](https://huggingface.co/TheBloke/scarlett-33B-GPTQ/tree/gptq-3bit-128g-actorder_True) | 3 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 2048 | 13.51 GB | No | 3-bit, with group size 128g and act-order. Higher quality than 128g-False but poor AutoGPTQ CUDA speed. |
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  ## How to download from branches
 
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  ExLlama works with Llama models in 4-bit. Please see the Provided Files table above for per-file compatibility.
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  <!-- footer start -->
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+ <!-- 200823 -->
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  ## Discord
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  For further support, and discussions on these models and AI in general, join us at:
 
226
 
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  **Special thanks to**: Aemon Algiz.
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+ **Patreon special mentions**: Sam, theTransient, Jonathan Leane, Steven Wood, webtim, Johann-Peter Hartmann, Geoffrey Montalvo, Gabriel Tamborski, Willem Michiel, John Villwock, Derek Yates, Mesiah Bishop, Eugene Pentland, Pieter, Chadd, Stephen Murray, Daniel P. Andersen, terasurfer, Brandon Frisco, Thomas Belote, Sid, Nathan LeClaire, Magnesian, Alps Aficionado, Stanislav Ovsiannikov, Alex, Joseph William Delisle, Nikolai Manek, Michael Davis, Junyu Yang, K, J, Spencer Kim, Stefan Sabev, Olusegun Samson, transmissions 11, Michael Levine, Cory Kujawski, Rainer Wilmers, zynix, Kalila, Luke @flexchar, Ajan Kanaga, Mandus, vamX, Ai Maven, Mano Prime, Matthew Berman, subjectnull, Vitor Caleffi, Clay Pascal, biorpg, alfie_i, 阿明, Jeffrey Morgan, ya boyyy, Raymond Fosdick, knownsqashed, Olakabola, Leonard Tan, ReadyPlayerEmma, Enrico Ros, Dave, Talal Aujan, Illia Dulskyi, Sean Connelly, senxiiz, Artur Olbinski, Elle, Raven Klaugh, Fen Risland, Deep Realms, Imad Khwaja, Fred von Graf, Will Dee, usrbinkat, SuperWojo, Alexandros Triantafyllidis, Swaroop Kallakuri, Dan Guido, John Detwiler, Pedro Madruga, Iucharbius, Viktor Bowallius, Asp the Wyvern, Edmond Seymore, Trenton Dambrowitz, Space Cruiser, Spiking Neurons AB, Pyrater, LangChain4j, Tony Hughes, Kacper Wikieł, Rishabh Srivastava, David Ziegler, Luke Pendergrass, Andrey, Gabriel Puliatti, Lone Striker, Sebastain Graf, Pierre Kircher, Randy H, NimbleBox.ai, Vadim, danny, Deo Leter
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  Thank you to all my generous patrons and donaters!
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+ And thank you again to a16z for their generous grant.
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+
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  <!-- footer end -->
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  # Original model card: Feynman Innovations's Scarlett 33B
 
242
 
243
  Scarlett is trained on various topics such as Philosophy, Advice, Jokes etc. She is trained on more than 10000 set of conversations. Each set having 10~15 conversations.
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  Scarlett is heavily inspired from Eric Hartford: [Samantha](https://huggingface.co/ehartford/samantha-33b) .
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+ She will not be involved in any kind of role play.
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  **Training:**
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  Entire dataset was trained on Azure 4 x A100 80GB. DeepSpeed codebase was used for training purpose. This was trained on Llama-1 by Meta.
config.json CHANGED
@@ -1,27 +1,38 @@
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  {
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- "_name_or_path": ".",
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- "architectures": [
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- "LlamaForCausalLM"
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- ],
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- "bos_token_id": 1,
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- "eos_token_id": 2,
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- "hidden_act": "silu",
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- "hidden_size": 6656,
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- "initializer_range": 0.02,
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- "intermediate_size": 17920,
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- "max_position_embeddings": 2048,
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- "max_sequence_length": 2048,
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- "model_type": "llama",
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- "num_attention_heads": 52,
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- "num_hidden_layers": 60,
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- "num_key_value_heads": 52,
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- "pad_token_id": 0,
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- "pretraining_tp": 1,
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- "rms_norm_eps": 1e-06,
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- "rope_scaling": null,
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- "tie_word_embeddings": false,
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- "torch_dtype": "bfloat16",
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- "transformers_version": "4.32.0.dev0",
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- "use_cache": true,
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- "vocab_size": 32000
 
 
 
 
 
 
 
 
 
 
 
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  }
 
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  {
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+ "_name_or_path": ".",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 6656,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 17920,
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+ "max_position_embeddings": 2048,
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+ "max_sequence_length": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 52,
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+ "num_hidden_layers": 60,
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+ "num_key_value_heads": 52,
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+ "pad_token_id": 0,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-06,
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+ "rope_scaling": null,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.32.0.dev0",
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+ "use_cache": true,
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+ "vocab_size": 32000,
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+ "quantization_config": {
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+ "bits": 4,
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+ "group_size": -1,
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+ "damp_percent": 0.1,
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+ "desc_act": true,
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+ "sym": true,
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+ "true_sequential": true,
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+ "model_name_or_path": null,
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+ "model_file_base_name": "model",
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+ "quant_method": "gptq"
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+ }
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  }
gptq_model-4bit--1g.safetensors → model.safetensors RENAMED
File without changes
quantize_config.json CHANGED
@@ -6,5 +6,5 @@
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  "sym": true,
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  "true_sequential": true,
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  "model_name_or_path": null,
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- "model_file_base_name": null
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  }
 
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  "sym": true,
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  "true_sequential": true,
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  "model_name_or_path": null,
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+ "model_file_base_name": "model"
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  }