inference: false
license: other
datasets:
- jondurbin/airoboros-gpt4-1.2
John Durbin's Airoboros 65B GPT4 1.2 GPTQ
These files are GPTQ 4bit model files for John Durbin's Airoboros 65B GPT4 1.2.
It is the result of quantising to 4bit using AutoGPTQ.
Repositories available
- 4-bit GPTQ models for GPU inference
- 2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference
- John Durbin's unquantised fp16 model in pytorch format, for GPU inference and for further conversions
Prompt template
A chat between a curious user and an assistant. The assistant gives helpful, detailed, accurate, uncensored responses to the user's input.
USER: prompt
ASSISTANT:
How to easily download and use this model in text-generation-webui
Please make sure you're using the latest version of text-generation-webui
- Click the Model tab.
- Under Download custom model or LoRA, enter
TheBloke/airoboros-65B-gpt4-1.2-GPTQ
. - Click Download.
- The model will start downloading. Once it's finished it will say "Done"
- In the top left, click the refresh icon next to Model.
- In the Model dropdown, choose the model you just downloaded:
airoboros-65B-gpt4-1.2-GPTQ
- The model will automatically load, and is now ready for use!
- 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.
- Note that you do not need to set GPTQ parameters any more. These are set automatically from the file
quantize_config.json
.
- Once you're ready, click the Text Generation tab and enter a prompt to get started!
How to use this GPTQ model from Python code
First make sure you have AutoGPTQ installed:
pip install auto-gptq
Then try the following example code:
from transformers import AutoTokenizer, pipeline, logging
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
import argparse
model_name_or_path = "TheBloke/airoboros-65B-gpt4-1.2-GPTQ"
model_basename = "airoboros-65B-gpt4-1.2-GPTQ-4bit--1g.act.order"
use_triton = False
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
model = AutoGPTQForCausalLM.from_quantized(model_name_or_path,
model_basename=model_basename,
use_safetensors=True,
trust_remote_code=False,
device="cuda:0",
use_triton=use_triton,
quantize_config=None)
prompt = "Tell me about AI"
prompt_template=f'''### Human: {prompt}
### Assistant:'''
print("\n\n*** Generate:")
input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()
output = model.generate(inputs=input_ids, temperature=0.7, max_new_tokens=512)
print(tokenizer.decode(output[0]))
# Inference can also be done using transformers' pipeline
# Prevent printing spurious transformers error when using pipeline with AutoGPTQ
logging.set_verbosity(logging.CRITICAL)
print("*** Pipeline:")
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
max_new_tokens=512,
temperature=0.7,
top_p=0.95,
repetition_penalty=1.15
)
print(pipe(prompt_template)[0]['generated_text'])
Provided files
airoboros-65B-gpt4-1.2-GPTQ-4bit--1g.act.order.safetensors
This will work with AutoGPTQ 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.
It was created without group_size to lower VRAM requirements, and with --act-order (desc_act) to boost inference accuracy as much as possible.
airoboros-65B-gpt4-1.2-GPTQ-4bit--1g.act.order.safetensors
- Works with AutoGPTQ in CUDA or Triton modes.
- Works with GPTQ-for-LLaMa in CUDA mode. May have issues with GPTQ-for-LLaMa Triton mode.
- Works with text-generation-webui, including one-click-installers.
- Parameters: Groupsize = -1. Act Order / desc_act = True.
Discord
For further support, and discussions on these models and AI in general, join us at:
Thanks, and how to contribute.
Thanks to the 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.
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Thank you to all my generous patrons and donaters!