[UPDATE: Try RWKV-4-World (
https://huggingface.co/BlinkDL/rwkv-4-world ) for generation & chat & code in 100+ world languages, with great English zero-shot & in-context learning ability too.]
RWKV-4 7B is a L32-D4096 causal language model trained on the Pile. See
https://github.com/BlinkDL/RWKV-LM for details.
RWKV-4-Pile-7B-20230109-ctx4096.pth : Fine-tuned to ctx_len 4096.
"Raven": RWKV alpaca+vicuna-style model:
https://huggingface.co/BlinkDL/rwkv-4-raven (highly recommended)
It is a strong chat model too. You can use +i for "Alpaca Instruct" in latest ChatRWKV v2. Examples:
+i Explain the following metaphor: "Life is like cats".
+i write a python function to read data from an excel file.RWKV-4-Pile-7B-20230xxx-ctx8192-testxxx : Fine-tuned to ctx_len 8192.
RWKV-4-Pile-7B-20221115-8047.pth : Trained on the Pile for 332B tokens.
Note I am using "Q: instruct\n\nA: result" prompt for all instructs.
RWKV-4-Pile-7B-Instruct-test2
instruct-tuned on
https://huggingface.co/datasets/Muennighoff/flan & NIv2
RWKV-4-Pile-7B-EngChn-testNovel-xxx for writing Chinese novels (trained on 200G Chinese novels.)
