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---
language:
- en
tags:
- pytorch
- text-generation
- causal-lm
- rwkv
license: apache-2.0
datasets:
- the_pile
---
# RWKV-4 7B
## Model Description
RWKV-4 7B is a L32-D4096 causal language model trained on the Pile. See https://github.com/BlinkDL/RWKV-LM for details.
Use https://github.com/BlinkDL/ChatRWKV to run it.
ctx_len = 1024
n_layer = 32
n_embd = 4096
(there are ctx_len 2048 and 4096 models though they might be slightly weaker at generating short contents)
Final checkpoint: RWKV-4-Pile-7B-20221115-8047.pth : Trained on the Pile for 332B tokens.
* Pile loss 1.8415
* LAMBADA ppl 4.38, acc 67.18%
* PIQA acc 76.06%
* SC2016 acc 73.44%
* Hellaswag acc_norm 65.51%
### Instruct-test models: only useful if you construct your prompt following dataset templates
Note I am using "Q: instruct\n\nA: result" prompt for all instructs.
RWKV-4-Pile-7B-Instruct-test1
instruct-tuned on https://huggingface.co/datasets/bigscience/xP3all/viewer/en/train
RWKV-4-Pile-7B-Instruct-test2
instruct-tuned on https://huggingface.co/datasets/Muennighoff/flan & NIv2
### Chinese models
RWKV-4-Pile-7B-EngChn-testNovel-xxx for writing Chinese novels (trained on 200G Chinese novels.)
RWKV-4-Pile-7B-EngChn-testxxx for Chinese Q&A (trained on 10G Chinese text. only for testing purposes.)
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