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--- |
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inference: false |
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license: other |
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--- |
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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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# Panchovix's merge of Guanaco 33B and SuperHOT 8K GPTQ |
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These files are GPTQ 4bit model files for [Panchovix's merge of Guanaco 33B and SuperHOT 8K](https://huggingface.co/Panchovix/Guanaco-33B-SuperHOT-8k). |
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It is the result of quantising to 4bit using [GPTQ-for-LLaMa](https://github.com/qwopqwop200/GPTQ-for-LLaMa). |
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## Repositories available |
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* [4-bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/Guanaco-33B-SuperHOT-8K-GPTQ) |
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* [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference](https://huggingface.co/none) |
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* [Unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/Panchovix/Guanaco-33B-SuperHOT-8k) |
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## How to easily download and use this model in text-generation-webui |
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Please make sure you're using the latest version of text-generation-webui |
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1. Click the **Model tab**. |
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2. Under **Download custom model or LoRA**, enter `TheBloke/Guanaco-33B-SuperHOT-8K-GPTQ`. |
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3. Click **Download**. |
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4. The model will start downloading. Once it's finished it will say "Done" |
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5. In the top left, click the refresh icon next to **Model**. |
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6. In the **Model** dropdown, choose the model you just downloaded: `Guanaco-33B-SuperHOT-8K-GPTQ` |
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7. The model will automatically load, and is now ready for use! |
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8. If you want any custom settings, set them and then click **Save settings for this model** followed by **Reload the Model** in the top right. |
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* Note that you do not need to and should not set manual GPTQ parameters any more. These are set automatically from the file `quantize_config.json`. |
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9. Once you're ready, click the **Text Generation tab** and enter a prompt to get started! |
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## How to use this GPTQ model from Python code |
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First make sure you have [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ) installed: |
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`pip install auto-gptq` |
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Then try the following example code: |
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```python |
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from transformers import AutoTokenizer, pipeline, logging |
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from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig |
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import argparse |
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model_name_or_path = "TheBloke/Guanaco-33B-SuperHOT-8K-GPTQ" |
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model_basename = "guanaco-33b-superhot-8k-GPTQ-4bit--1g.act.order" |
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use_triton = False |
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tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True) |
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model = AutoGPTQForCausalLM.from_quantized(model_name_or_path, |
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model_basename=model_basename, |
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use_safetensors=True, |
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trust_remote_code=False, |
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device="cuda:0", |
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use_triton=use_triton, |
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quantize_config=None) |
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# Note: check the prompt template is correct for this model. |
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prompt = "Tell me about AI" |
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prompt_template=f'''USER: {prompt} |
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ASSISTANT:''' |
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print("\n\n*** Generate:") |
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input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda() |
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output = model.generate(inputs=input_ids, temperature=0.7, max_new_tokens=512) |
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print(tokenizer.decode(output[0])) |
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# Inference can also be done using transformers' pipeline |
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# Prevent printing spurious transformers error when using pipeline with AutoGPTQ |
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logging.set_verbosity(logging.CRITICAL) |
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print("*** Pipeline:") |
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pipe = pipeline( |
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"text-generation", |
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model=model, |
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tokenizer=tokenizer, |
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max_new_tokens=512, |
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temperature=0.7, |
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top_p=0.95, |
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repetition_penalty=1.15 |
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) |
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print(pipe(prompt_template)[0]['generated_text']) |
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``` |
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## Provided files |
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**guanaco-33b-superhot-8k-GPTQ-4bit--1g.act.order.safetensors** |
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This will work with AutoGPTQ, ExLlama, and CUDA versions of GPTQ-for-LLaMa. There are reports of issues with Triton mode of recent GPTQ-for-LLaMa. If you have issues, please use AutoGPTQ instead. |
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It was created without group_size to lower VRAM requirements, and with --act-order (desc_act) to boost inference accuracy as much as possible. |
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* `guanaco-33b-superhot-8k-GPTQ-4bit--1g.act.order.safetensors` |
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* Works with AutoGPTQ in CUDA or Triton modes. |
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* LLaMa models also work with [ExLlama](https://github.com/turboderp/exllama}, which usually provides much higher performance, and uses less VRAM, than AutoGPTQ. |
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* Works with GPTQ-for-LLaMa in CUDA mode. May have issues with GPTQ-for-LLaMa Triton mode. |
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* Works with text-generation-webui, including one-click-installers. |
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* Parameters: Groupsize = -1. Act Order / desc_act = True. |
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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: |
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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**: Luke from CarbonQuill, Aemon Algiz, Dmitriy Samsonov. |
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**Patreon special mentions**: Pyrater, WelcomeToTheClub, Kalila, Mano Prime, Trenton Dambrowitz, Spiking Neurons AB, Pierre Kircher, Fen Risland, Kevin Schuppel, Luke, Rainer Wilmers, vamX, Gabriel Puliatti, Alex , Karl Bernard, Ajan Kanaga, Talal Aujan, Space Cruiser, ya boyyy, biorpg, Johann-Peter Hartmann, Asp the Wyvern, Ai Maven, Ghost , Preetika Verma, Nikolai Manek, trip7s trip, John Detwiler, Fred von Graf, Artur Olbinski, subjectnull, John Villwock, Junyu Yang, Rod A, Lone Striker, Chris McCloskey, Iucharbius , Matthew Berman, Illia Dulskyi, Khalefa Al-Ahmad, Imad Khwaja, chris gileta, Willem Michiel, Greatston Gnanesh, Derek Yates, K, Alps Aficionado, Oscar Rangel, David Flickinger, Luke Pendergrass, Deep Realms, Eugene Pentland, Cory Kujawski, terasurfer , Jonathan Leane, senxiiz, Joseph William Delisle, Sean Connelly, webtim, zynix , Nathan LeClaire. |
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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: Panchovix's merge of Guanaco 33B and SuperHOT 8K |
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[guanaco-33b](https://huggingface.co/timdettmers/guanaco-33b-merged) merged with kaiokendev's [33b SuperHOT 8k LoRA](https://huggingface.co/kaiokendev/superhot-30b-8k-no-rlhf-test), without quant. (Full FP16 model) |
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