8bit version of the model
#8
by
varun500
- opened
- README.md +10 -53
- config.json +2 -10
- quantize_config.json +1 -2
- special_tokens_map.json +5 -22
- model.safetensors → stable-vicuna-13B-GPTQ-4bit.compat.no-act-order.safetensors +2 -2
- tokenizer_config.json +5 -4
README.md
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- tatsu-lab/alpaca
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inference: false
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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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# StableVicuna-13B-GPTQ
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This repo contains 4bit GPTQ format quantised models of [
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It is the result of first merging the deltas from the above repository with the original Llama 13B weights, then quantising to 4bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa).
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## Repositories available
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* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/stable-vicuna-13B-GPTQ).
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* [
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* [Unquantised
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## PROMPT TEMPLATE
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4. Wait until it says it's finished downloading.
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5. Click the **Refresh** icon next to **Model** in the top left.
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6. In the **Model drop-down**: choose the model you just downloaded,`stable-vicuna-13B-GPTQ`.
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## Provided files
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```
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CUDA_VISIBLE_DEVICES=0 python3 llama.py stable-vicuna-13B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors stable-vicuna-13B-GPTQ-4bit.act-order.safetensors
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```
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## Manual instructions for `text-generation-webui`
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File `stable-vicuna-13B-GPTQ-4bit.compat.no-act-order.safetensors` can be loaded the same as any other GPTQ file, without requiring any updates to [oobaboogas text-generation-webui](https://github.com/oobabooga/text-generation-webui).
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If you can't update GPTQ-for-LLaMa or don't want to, you can use `stable-vicuna-13B-GPTQ-4bit.no-act-order.safetensors` as mentioned above, which should work without any upgrades to text-generation-webui.
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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:
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[TheBloke AI's Discord server](https://discord.gg/theblokeai)
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## Thanks, and how to contribute.
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Thanks to the [chirper.ai](https://chirper.ai) team!
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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.
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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.
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Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits.
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* Patreon: https://patreon.com/TheBlokeAI
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* Ko-Fi: https://ko-fi.com/TheBlokeAI
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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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<!-- footer end -->
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# Original StableVicuna-13B model card
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## Model Description
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Zack Witten and
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alexandremuzio and
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crumb},
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title = {{CarperAI/trlx: v0.6.0: LLaMa (Alpaca), Benchmark
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Util, T5 ILQL, Tests}},
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month = mar,
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year = 2023,
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- tatsu-lab/alpaca
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inference: false
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---
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# StableVicuna-13B-GPTQ
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This repo contains 4bit GPTQ format quantised models of [CarterAI's StableVicuna 13B](https://huggingface.co/CarperAI/stable-vicuna-13b-delta).
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It is the result of first merging the deltas from the above repository with the original Llama 13B weights, then quantising to 4bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa).
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## Repositories available
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* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/stable-vicuna-13B-GPTQ).
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* [4bit and 5bit GGML models for CPU inference](https://huggingface.co/TheBloke/stable-vicuna-13B-GGML).
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* [Unquantised 16bit model in HF format](https://huggingface.co/TheBloke/stable-vicuna-13B-HF).
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## PROMPT TEMPLATE
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4. Wait until it says it's finished downloading.
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5. Click the **Refresh** icon next to **Model** in the top left.
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6. In the **Model drop-down**: choose the model you just downloaded,`stable-vicuna-13B-GPTQ`.
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7. If you see an error in the bottom right, ignore it - it's temporary.
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8. Fill out the `GPTQ parameters` on the right: `Bits = 4`, `Groupsize = 128`, `model_type = Llama`
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9. Click **Save settings for this model** in the top right.
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10. Click **Reload the Model** in the top right.
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11. Once it says it's loaded, click the **Text Generation tab** and enter a prompt!
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## Provided files
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```
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CUDA_VISIBLE_DEVICES=0 python3 llama.py stable-vicuna-13B-HF c4 --wbits 4 --true-sequential --act-order --groupsize 128 --save_safetensors stable-vicuna-13B-GPTQ-4bit.act-order.safetensors
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```
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## Manual instructions for `text-generation-webui`
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File `stable-vicuna-13B-GPTQ-4bit.compat.no-act-order.safetensors` can be loaded the same as any other GPTQ file, without requiring any updates to [oobaboogas text-generation-webui](https://github.com/oobabooga/text-generation-webui).
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If you can't update GPTQ-for-LLaMa or don't want to, you can use `stable-vicuna-13B-GPTQ-4bit.no-act-order.safetensors` as mentioned above, which should work without any upgrades to text-generation-webui.
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# Original StableVicuna-13B model card
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## Model Description
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Zack Witten and
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alexandremuzio and
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crumb},
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title = {{CarperAI/trlx: v0.6.0: LLaMa (Alpaca), Benchmark
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Util, T5 ILQL, Tests}},
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month = mar,
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year = 2023,
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config.json
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"torch_dtype": "float16",
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"transformers_version": "4.28.1",
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"use_cache": true,
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"vocab_size": 32001
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"bits": 4,
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"damp_percent": 0.01,
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"desc_act": false,
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"group_size": 128,
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"model_file_base_name": "model",
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"quant_method": "gptq"
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}
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}
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"torch_dtype": "float16",
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"transformers_version": "4.28.1",
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"use_cache": true,
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"vocab_size": 32001
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}
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quantize_config.json
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"bits": 4,
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"damp_percent": 0.01,
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"desc_act": false,
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"group_size": 128
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"model_file_base_name": "model"
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}
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"bits": 4,
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"damp_percent": 0.01,
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"desc_act": false,
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"group_size": 128
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}
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special_tokens_map.json
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{
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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{
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"bos_token": "</s>",
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"eos_token": "</s>",
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"pad_token": "[PAD]",
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"unk_token": "</s>"
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}
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model.safetensors → stable-vicuna-13B-GPTQ-4bit.compat.no-act-order.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:442d71b56bc16721d28aeb2d5e0ba07cf04bfb61cc7af47993d5f0a15133b520
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size 7255179696
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tokenizer_config.json
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"add_eos_token": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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},
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"model_max_length": 2048,
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"pad_token": null,
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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"add_eos_token": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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},
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"model_max_length": 2048,
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"pad_token": null,
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"padding_side": "right",
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"sp_model_kwargs": {},
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"tokenizer_class": "LlamaTokenizer",
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"unk_token": {
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"__type": "AddedToken",
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"content": "",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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}
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}
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