rwkv7-2.9B-world / README.md
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metadata
license: apache-2.0
language:
  - en
  - zh
  - ja
  - ko
  - fr
  - ar
  - es
  - pt
metrics:
  - accuracy
base_model:
  - BlinkDL/rwkv-7-world
pipeline_tag: text-generation

rwkv7-2.9B-world

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: 2.9B
  • Tokenizer: RWKV World tokenizer
  • Vocabulary size: 65,536

Model Sources

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/rwkv7-2.9B-world', trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained('fla-hub/rwkv7-2.9B-world', trust_remote_code=True)

Training Data

This model is trained on the World v3 with a total of 3.119 trillion tokens.

Training Hyperparameters

  • Training regime: bfloat16, lr 4e-4 to 1e-5 "delayed" cosine decay, wd 0.1 (with increasing batch sizes during the middle)
  • Final Loss: 1.8745
  • Token Count: 3.119 trillion

FAQ

Q: safetensors metadata is none.

A: upgrade transformers to >=4.48.0: pip install 'transformers>=4.48.0'