rwkv7-168M-pile
This is RWKV-7 model under flash-linear attention format.
Model Details
Model Description
- Developed by: Bo Peng, Yu Zhang, Songlin Yang, Ruichong Zhang
- Funded by: RWKV Project (Under LF AI & Data Foundation)
- Model type: RWKV7
- Language(s) (NLP): English
- License: Apache-2.0
- Parameter count: 168M
- Tokenizer: GPT-NeoX 20B tokenizer
Model Sources
- Repository: https://github.com/fla-org/flash-linear-attention ; https://github.com/BlinkDL/RWKV-LM
- Paper: https://huggingface.co/papers/2503.14456
- Weights: Converted from https://modelscope.cn/models/RWKV/rwkv-7-pile/file/view/master?fileName=RWKV-x070-Pile-168M-20241120-ctx4096.pth
Uses
Install flash-linear-attention and the latest version of transformers before using this model:
pip install git+https://github.com/fla-org/flash-linear-attention
pip install 'transformers>=4.48.0'
Direct Use
You can use this model just as any other HuggingFace models:
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('fla-hub/rwkv7-168M-pile', trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained('fla-hub/rwkv7-168M-pile', trust_remote_code=True)
Training Details
Training Data
This model is trained on the Pile with a total of 332 billion tokens.
Training Hyperparameters
- Training regime: bfloat16, lr 8e-4 to 3e-5 cosine decay, wd 0.1, bsz 8x30x4096
Evaluation
Metrics
lambada_openai: ppl 14.2 acc 45.6%
piqa: acc 65.5%
FAQ
Q: safetensors metadata is none.
A: upgrade transformers to >=4.48.0: pip install 'transformers>=4.48.0'