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license: mit
---

### SuperHOT Prototype 2 w/ 16K Context

This is a second prototype of SuperHOT, a NSFW focused LoRA, this time with 16K context and no RLHF, using the same technique described in [the github blog](https://kaiokendev.github.io/til#extending-context-to-8k).
Tests have shown that the model does indeed leverage the extended context at 8K, so naturally, let's try going even further.

#### Looking for Merged & Quantized Models?
- 13B 16K GGML: [tmpupload/superhot-13b-16k-no-rlhf-test-GGML](https://huggingface.co/tmpupload/superhot-13b-16k-no-rlhf-test-GGML)
- 13B 16K CUDA (no groupsize): [tmpupload/superhot-13b-16k-no-rlhf-test-GPTQ](https://huggingface.co/tmpupload/superhot-13b-16k-no-rlhf-test-GPTQ)

#### Using the monkey-patch?
You will need to **use either the monkeypatch** or, if you are already using the monkeypatch, **change the scaling factor to 0.125 and the maximum sequence length to 16384**

#### Using Oobabooga with Exllama?
- `python server.py --max_seq_len 16384 --compress_pos_emb 8 --loader exllama_hf`

I trained the LoRA with the following configuration: 
- 1200 samples (~400 samples over 2048 sequence length)
- learning rate of 3e-4 
- 3 epochs
- The exported modules are:
    - q_proj
    - k_proj
    - v_proj
    - o_proj
    - no bias
- Rank = 4
- Alpha = 8
- no dropout
- weight decay of 0.1
- AdamW beta1 of 0.9 and beta2 0.99, epsilon of 1e-5
- Trained on 4-bit base model
- Cutoff of 4096