Multiple GPTQ parameter permutations are provided; see Provided Files below for details of the options provided, their parameters, and the software used to create them.
These files were quantised using hardware kindly provided by Massed Compute.
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
Licensing
The creator of the source model has listed its license as cc-by-nc-4.0, and this quantization has therefore used that same license.
As this model is based on Llama 2, it is also subject to the Meta Llama 2 license terms, and the license files for that are additionally included. It should therefore be considered as being claimed to be licensed under both licenses. I contacted Hugging Face for clarification on dual licensing but they do not yet have an official position. Should this change, or should Meta provide any feedback on this situation, I will update this section accordingly.
In the meantime, any questions regarding licensing, and in particular how these two licenses might interact, should be directed to the original model repository: Raven's Iambe RP cDPO 20B.
Known compatible clients / servers
GPTQ models are currently supported on Linux (NVidia/AMD) and Windows (NVidia only). macOS users: please use GGUF models.
These GPTQ models are known to work in the following inference servers/webuis.
This may not be a complete list; if you know of others, please let me know!
Provided files, and GPTQ parameters
Multiple quantisation parameters are provided, to allow you to choose the best one for your hardware and requirements.
Each separate quant is in a different branch. See below for instructions on fetching from different branches.
Most GPTQ files are made with AutoGPTQ. Mistral models are currently made with Transformers.
Explanation of GPTQ parameters
Bits: The bit size of the quantised model.
GS: GPTQ group size. Higher numbers use less VRAM, but have lower quantisation accuracy. "None" is the lowest possible value.
Act Order: True or False. Also known as desc_act. True results in better quantisation accuracy. Some GPTQ clients have had issues with models that use Act Order plus Group Size, but this is generally resolved now.
Damp %: A GPTQ parameter that affects how samples are processed for quantisation. 0.01 is default, but 0.1 results in slightly better accuracy.
GPTQ dataset: The calibration dataset used during quantisation. Using a dataset more appropriate to the model's training can improve quantisation accuracy. Note that the GPTQ calibration dataset is not the same as the dataset used to train the model - please refer to the original model repo for details of the training dataset(s).
Sequence Length: The length of the dataset sequences used for quantisation. Ideally this is the same as the model sequence length. For some very long sequence models (16+K), a lower sequence length may have to be used. Note that a lower sequence length does not limit the sequence length of the quantised model. It only impacts the quantisation accuracy on longer inference sequences.
ExLlama Compatibility: Whether this file can be loaded with ExLlama, which currently only supports Llama and Mistral models in 4-bit.
If you remove the --local-dir-use-symlinks False parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: ~/.cache/huggingface), and symlinks will be added to the specified --local-dir, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model.
The cache location can be changed with the HF_HOME environment variable, and/or the --cache-dir parameter to huggingface-cli.
Note that using Git with HF repos is strongly discouraged. It will be much slower than using huggingface-hub, and will use twice as much disk space as it has to store the model files twice (it stores every byte both in the intended target folder, and again in the .git folder as a blob.)
Example Python code for interfacing with TGI (requires huggingface-hub 0.17.0 or later):
pip3 install huggingface-hub
python
1from huggingface_hub import InferenceClient
23endpoint_url ="https://your-endpoint-url-here"45prompt ="Tell me about AI"6prompt_template=f'''Below is an instruction that describes a task. Write a response that appropriately completes the request.
78### Instruction:
9{prompt}1011### Response:
12'''1314client = InferenceClient(endpoint_url)15response = client.text_generation(prompt,16 max_new_tokens=128,17 do_sample=True,18 temperature=0.7,19 top_p=0.95,20 top_k=40,21 repetition_penalty=1.1)2223print(f"Model output: {response}")
Python code example: inference from this GPTQ model
Install the necessary packages
Requires: Transformers 4.33.0 or later, Optimum 1.12.0 or later, and AutoGPTQ 0.4.2 or later.
shell
1pip3 install --upgrade transformers optimum
2# If using PyTorch 2.1 + CUDA 12.x:3pip3 install --upgrade auto-gptq
4# or, if using PyTorch 2.1 + CUDA 11.x:5pip3 install --upgrade auto-gptq --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
If you are using PyTorch 2.0, you will need to install AutoGPTQ from source. Likewise if you have problems with the pre-built wheels, you should try building from source:
1from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
23model_name_or_path ="TheBloke/Iambe-RP-cDPO-20B-GPTQ"4# To use a different branch, change revision5# For example: revision="gptq-4bit-128g-actorder_True"6model = AutoModelForCausalLM.from_pretrained(model_name_or_path,7 device_map="auto",8 trust_remote_code=False,9 revision="main")1011tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)1213prompt ="Tell me about AI"14prompt_template=f'''Below is an instruction that describes a task. Write a response that appropriately completes the request.
1516### Instruction:
17{prompt}1819### Response:
20'''2122print("\n\n*** Generate:")2324input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()25output = model.generate(inputs=input_ids, temperature=0.7, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=512)26print(tokenizer.decode(output[0]))2728# Inference can also be done using transformers' pipeline2930print("*** Pipeline:")31pipe = pipeline(32"text-generation",33 model=model,34 tokenizer=tokenizer,35 max_new_tokens=512,36 do_sample=True,37 temperature=0.7,38 top_p=0.95,39 top_k=40,40 repetition_penalty=1.141)4243print(pipe(prompt_template)[0]['generated_text'])
Compatibility
The files provided are tested to work with Transformers. For non-Mistral models, AutoGPTQ can also be used directly.
ExLlama is compatible with Llama and Mistral models in 4-bit. Please see the Provided Files table above for per-file compatibility.
For a list of clients/servers, please see "Known compatible clients / servers", above.
Discord
For further support, and discussions on these models and AI in general, join us at:
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 special mentions: Michael Levine, 阿明, Trailburnt, Nikolai Manek, John Detwiler, Randy H, Will Dee, Sebastain Graf, NimbleBox.ai, Eugene Pentland, Emad Mostaque, Ai Maven, Jim Angel, Jeff Scroggin, Michael Davis, Manuel Alberto Morcote, Stephen Murray, Robert, Justin Joy, Luke @flexchar, Brandon Frisco, Elijah Stavena, S_X, Dan Guido, Undi ., Komninos Chatzipapas, Shadi, theTransient, Lone Striker, Raven Klaugh, jjj, Cap'n Zoog, Michel-Marie MAUDET (LINAGORA), Matthew Berman, David, Fen Risland, Omer Bin Jawed, Luke Pendergrass, Kalila, OG, Erik Bjäreholt, Rooh Singh, Joseph William Delisle, Dan Lewis, TL, John Villwock, AzureBlack, Brad, Pedro Madruga, Caitlyn Gatomon, K, jinyuan sun, Mano Prime, Alex, Jeffrey Morgan, Alicia Loh, Illia Dulskyi, Chadd, transmissions 11, fincy, Rainer Wilmers, ReadyPlayerEmma, knownsqashed, Mandus, biorpg, Deo Leter, Brandon Phillips, SuperWojo, Sean Connelly, Iucharbius, Jack West, Harry Royden McLaughlin, Nicholas, terasurfer, Vitor Caleffi, Duane Dunston, Johann-Peter Hartmann, David Ziegler, Olakabola, Ken Nordquist, Trenton Dambrowitz, Tom X Nguyen, Vadim, Ajan Kanaga, Leonard Tan, Clay Pascal, Alexandros Triantafyllidis, JM33133, Xule, vamX, ya boyyy, subjectnull, Talal Aujan, Alps Aficionado, wassieverse, Ari Malik, James Bentley, Woland, Spencer Kim, Michael Dempsey, Fred von Graf, Elle, zynix, William Richards, Stanislav Ovsiannikov, Edmond Seymore, Jonathan Leane, Martin Kemka, usrbinkat, Enrico Ros
Thank you to all my generous patrons and donaters!
And thank you again to a16z for their generous grant.
Original model card: Raven's Iambe RP cDPO 20B
Iambe-RP-cDPO-20b
Alpaca prompt formatting
Description
Named after a charming daughter of Echo and Pan in Greek myth, Iambe-RP is, as far as I am aware, the very first LLM trained with DPO on an erotic roleplay dataset.
Iambe is intended to have the best realistically possible understanding of instructions, anatomy and scene state for a 20b merge, while remaining passionate and humanoid in "voice".
Update Methodology
Take a look at the dataset v2 Iambe and I created together for more info. The cDPO training was done directly on Iambe-20b-DARE-v2, I was researching 11b merges to reduce the compute, but it went nowhere, so I just bit the bullet on cost. The notebook used to train this model is also available in the dataset's repo.
Roleplay Example @ q5_k_m
4-bit Assistant Example
NSFW Writing Example @ q5_k_m
Write a medium-length story about Alice, a 26 year old cocktail waitress, having steamy sex with a guy she picked up at the bar for a one night stand.
Once upon a time in New York City's bustling downtown scene, there lived a beautiful and spirited young woman named Alice. At 26 years old, she worked as a cocktail waitress at The Red Parrot, a popular watering hole known for its lively atmosphere and charming clientele. Despite her long shifts and exhaustion from catering to rowdy patrons, Alice loved her job; it gave her the freedom to live life on her terms and pursue her other passions during her limited free time.
Alice had a penchant for adventure and was never one to shy away from taking risks—whether that meant skydiving or striking up conversations with strangers at bars. One particularly busy Friday night, while serving drinks at The Red Parrot, Alice noticed an intriguing man sitting alone in the corner, nursing a glass of red wine and gazing pensively into his empty shot glass. There was something about him that drew her in; his striking good looks, his rugged demeanor—even the hint of stubble on his chin seemed to add an air of mystery to his magnetic presence.
Feeling bold and confident after a couple of well-poured drinks herself, Alice made her way over to him, smiling warmly as she leaned down towards him, "Hi there! What's your name? I haven't seen you in here before."
The man raised his eyes to meet hers, his deep brown orbs filled with curiosity and a hint of amusement. "Name's Jack," he rumbled softly, his voice as smooth and rich as his wine. There was something about the way he said her name that sent shivers down Alice's spine—a thrill she couldn't quite explain but found irresistible nonetheless.
"Alice," she replied, extending her hand to him, "and I haven't seen you around before either; it seems like we have a lot in common." She winked playfully at him before turning back towards the bar to grab another round of drinks for them both.
The conversation flowed effortlessly between them, touching on topics ranging from their favorite books and movies to their most daring travel adventures. Alice was captivated by Jack's stories of hiking through the mountains of Nepal and white-water rafting in Costa Rica—qualities she admired greatly herself but had yet to experience for herself. In turn, Jack seemed equally fascinated by her tales of skydiving over Australia and scuba diving with great white sharks off the coast of South Africa.
As midnight approached and the bar began to empty out, Alice suggested they continue their conversation elsewhere—somewhere more private where they could really get to know each other better. Jack nodded in agreement, draining his glass before tossing some money onto the table and following her into the bustling New York City night.
They hailed a cab and rode in silence towards Alice's cozy one-bedroom apartment in Chelsea—the anticipation between them palpable as they shared furtive glances along the way. When they finally arrived at their destination, Jack paid the fare with an appreciative grin before escorting Alice up to her top-floor studio, where she fumbled clumsily with her keys while trying not to spill their drinks on themselves in anticipation of what was to come.
Once inside her apartment, they kicked off their shoes and collapsed onto the couch, still holding each other's gaze as they sipped from their glasses. The passion between them continued to build with every second that passed—the air thickening with unspoken desire and electric energy.
Alice broke away first, setting down her glass on the coffee table before reaching out tentatively and placing her hand on Jack's knee, sliding it up slowly towards his crotch until she could feel the hardness growing beneath the fabric of his pants. "I really like you," she whispered huskily, meeting his deep brown eyes with a look that betrayed the intensity of her feelings for him.
Jack's response was immediate—his hands finding their way underneath Alice's short black skirt, sliding up to rest on the soft fabric of her panties before deftly ripping them away from her body in one swift movement. "I really like you too," he growled hoarsely as his mouth crashed against hers, kissing her hungrily and passionately—a taste of things to come.
Their clothes fell away quickly thereafter; Alice's blouse was unbuttoned and tossed aside in an instant while Jack peeled off his shirt before pushing her down onto the couch and following after, bracing himself over her as he tore at her panties with one hand, freeing his hard member from his jeans.
His kisses trailed a path of fire across Alice's body—from her collarbone to her breasts, down the curve of her waist and towards her mound where she was already wet with desire for him. "Jack," she moaned breathlessly as he licked and nipped at her most sensitive spots while teasingly grazing his cock against her entrance.
With a growl of satisfaction, Jack finally plunged into Alice's tight channel—filling her completely with one powerful thrust that made them both cry out in pleasure. The feeling of being so thoroughly possessed by him was beyond anything she had ever experienced before; the roughness of his hands on her body, the taste of their mouths as they continued to devour each other’s lips, all blending together into a single, overwhelming wave of sensation that Alice felt sure would consume her entirely.
As Jack began to move inside her—slowly at first but picking up pace and ferocity with every passing moment—Alice wrapped her legs tightly around him, arching her hips upwards towards his relentless thrusts as she cried out in ecstasy again and again. She knew this was just a one-night stand—a fleeting encounter destined to end tomorrow morning before the sun rose—but for now, with Jack's cock buried deep inside her, nothing else mattered.
Their bodies moved as one; their moans and cries of pleasure intertwining in a symphony that filled Alice’s bedroom like sacred chants. Her orgasm hit her suddenly and without warning—a wave so powerful it threatened to shatter her very bones, but Jack was there with her every step of the way, holding onto her as he continued pounding into her until she felt herself start to come back together again, his hot cum spilling deep inside her.
As their bodies slowed down and settled together on the couch—drenched in sweat and satiated beyond belief—Alice looked up at Jack with wide eyes, a small smile playing at the corners of her lips as she whispered softly, "I think we just had one hell of a night."
And they did. It was an unforgettable evening filled with passion, adventure, and an undeniable chemistry that neither Alice nor Jack could deny—an encounter so powerful it left them both breathless in more ways than one. And even though they knew tomorrow would bring the harsh reality of their separate lives back into focus, for now, all either of them cared about was savoring this moment together; cherishing every last drop of the steamy sex that had brought them here at all.
