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ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1-GPTQ_Q4
Llama-3.1-8B-ArliAI-RPMax-v1.1-GPTQ_Q4 is a machine learning model from ArliAI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as llama3.
Downloads · 30 days
11
4% of all-time downloads
All-time downloads
291
Public
Parameters
8B
5.7 GB on disk
Likes
2
Public
Click a slice to open those files.
.safetensors5.7 GB · 100%
How the weights are stored.
I327B · 87%
From the Hugging Face model README
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| 2B | 3.8B | 8B | 9B | 12B | 20B | 22B | 70B |
RPMax is a series of models that are trained on a diverse set of curated creative writing and RP datasets with a focus on variety and deduplication. This model is designed to be highly creative and non-repetitive by making sure no two entries in the dataset have repeated characters or situations, which makes sure the model does not latch on to a certain personality and be capable of understanding and acting appropriately to any characters or situations.
Early tests by users mentioned that these models does not feel like any other RP models, having a different style and generally doesn't feel in-bred.
You can access the model at https://arliai.com and ask questions at https://www.reddit.com/r/ArliAI/
We also have a models ranking page at https://www.arliai.com/models-ranking
Ask questions in our new Discord Server! https://discord.com/invite/t75KbPgwhk
Llama-3.1-8B-ArliAI-RPMax-v1.1 is a variant of the Meta-Llama-3.1-8B model.
v1.1 is just a small fix to not train and save the embeddings layer and small changes to the dataset, since v1.0 had the lm_head unnecessarily trained on accident.
The model is available in quantized formats:
We recommend using full weights or GPTQ
Llama 3 Instruct Format
Example:
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
You are [character]. You have a personality of [personality description]. [Describe scenario]<|eot_id|><|start_header_id|>user<|end_header_id|>
{{ user_message_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
{{ model_answer_1 }}<|eot_id|><|start_header_id|>user<|end_header_id|>
{{ user_message_2 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>