Downloads · 30 days
22
1% of all-time downloads
rexwang8/qilin-lit-6b
qilin-lit-6b is a text generation model from rexwang8. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Most updated version is V1.1.0 which is fine-tuned on 550 MB of webnovels found on the NovelUpdates website. (https://www.novelupdates.com/)
Downloads · 30 days
22
1% of all-time downloads
All-time downloads
2.4K
Public
Repo size
36.5 GB
Likes
6
Public
Click a slice to open those files.
.bin12.2 GB · 100%
From the Hugging Face model README
Most updated version is V1.1.0 which is fine-tuned on 550 MB of webnovels found on the NovelUpdates website. (https://www.novelupdates.com/)
The style is SFW and whimsical, excelling at telling fantasy stories, especially webnovels.
This model can be used for entertainment purposes and as a creative writing assistant for fiction writers.
GPU -> https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/GPU.ipynb TPU -> https://colab.research.google.com/github/KoboldAI/KoboldAI-Client/blob/main/colab/TPU.ipynb Replace the drop-down value with "rexwang8/qilin-lit-6b" and select that model.
Load at AI/load a model from it's directory. Model name is "rexwang8/qilin-lit-6b". If you get a config.json not found error, reload the program and give it some time to find your GPUs.
from transformers import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained('rexwang8/qilin-lit-6b')
tokenizer = AutoTokenizer.from_pretrained('rexwang8/lit-6b')
prompt = '''I had eyes but couldn't see Mount Tai!'''
input_ids = tokenizer.encode(prompt, return_tensors='pt')
output = model.generate(input_ids, do_sample=True, temperature=1.0, top_p=0.9, repetition_penalty=1.2, max_length=len(input_ids[0])+100, pad_token_id=tokenizer.eos_token_id)
generated_text = tokenizer.decode(output[0])
print(generated_text)
Fine-tuned version of EleutherAI/gpt-j-6B (https://huggingface.co/EleutherAI/gpt-j-6B) on Coreweave's infrastructure (https://www.coreweave.com/) using an A40 over ~80 hours.
3150 steps, 1 epoch trained on 550 MB of primarily Xianxia genre Webnovels. (Translated to English)
Rex Wang - Author
Coreweave - Computational materials
With help from:
Wes Brown, Anthony Mercurio
1.1.0 - 550 MB Dataset(34 books) 3150 steps (no reordering, no sampling)
1.0.0 - 100 MB Dataset(3 books) 300 steps (no reordering, no sampling)