---
language:
- en
library_name: peft
datasets:
- EleutherAI/wikitext_document_level
pipeline_tag: text-generation
base_model: huggyllama/llama-30b
---

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)

LLaMA 33b finetuned on `wikitext_document_level` with a combination of both linear and NTK-aware ROPE scaling.

Trained with alpha=4, scale=2. Definitely works for sequence lengths up to and including 4096. Might work for much longer, but I don't have the VRAM to test properly. ¯\\\_(ツ)\_/¯

<img src="llama33b-s2a4-qlora/resolve/main/perplexity.png" alt="Perplexity Graph" />

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions


- PEFT 0.4.0.dev0