RWKV7-G1 "GooseOne" pure RNN reasoning model

These are BASE models (pretrained with web/code/synthetic + instruction/chat/reasoning data), suitable for post-training and fine-tuning (check https://huggingface.co/spaces/Jellyfish042/UncheatableEval to see their performance at language modeling).

More info & Gradio demo: https://rwkv.com/

For developers: https://github.com/BlinkDL/RWKV-LM

RWKV-7 pth => GGUF script: https://github.com/MollySophia/rwkv-mobile/blob/master/converter/convert_rwkv_pth_to_gguf.py

GGUF: https://huggingface.co/collections/shoumenchougou/rwkv7-gxx-gguf

Ollama GGUF: https://ollama.com/mollysama

Use rwkv pip package 0.8.29+ for RWKV-7 inference: https://pypi.org/project/rwkv/

Efficient inference project: https://github.com/BlinkDL/Albatross

RWKV APP: https://github.com/RWKV-APP/RWKV_APP (local inference on Android/iOS)

Please always use latest models (with newest date) (better at everything).

Decoding Suggestion (note: this is for RWKV pip pkg, which apply temp after topp):

Chat: temp 1, topp 0.5, alpha_presence 2, alpha_frequency 0.1, alpha_decay 0.99

Creative (great for fiction etc.): temp 0.6, topp 0.6 ~ 0.8, alpha_presence 2, alpha_frequency 0.2, alpha_decay 0.99

There should not be any space at the end of your input (so strip it) or you will upset the tokenizer and see non-English reponse.

Chat prompt (note: better replace all \n\n in USER_PROMPT to \n as i am using \n\n as "chat round separator" in pretrain data):

System: YOU_CAN_USE_SYSTEM_IF_NEEDED

User: PREVIOUS_STUFF

Assistant: PREVIOUS_STUFF

User: USER_PROMPT

Assistant:

Think prompt (for hard prompts):

User: USER_PROMPT

Assistant: <think

Fake think prompt (great result, highly recommended):

User: USER_PROMPT

Assistant: <think></think

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Think prompt, alternative style, for G1c and newer models. Note there is a space before the "(think)" after USER_PROMPT:

User: USER_PROMPT (think)

Assistant: <think

Shorter think, same style:

User: USER_PROMPT (think a bit)

Assistant: <think

Longer think, same style:

User: USER_PROMPT (think a lot)

Assistant: <think

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FIM prompt (for G1c and newer models, works for text & code & everything):

✿prefix✿When I was young, I only liked to✿suffix✿and that’s how first I got interested in AI research.✿middle✿

Better (recommended):

✿prefix✿✿suffix✿and that’s how first I got interested in AI research.✿middle✿When I was young, I only liked to

Note "✿" will always be tokenized to one single token in RWKV tokenizer, so I picked it.

Gxx = Data Version

G0x = less than 1 epoch, as training 1 epoch for a large model is expensive :(
G0 G0a G0a2 G0a3 ... G0b ... = adding more (newer and better) data, so G0a has better quality (but less) data than G1

G1x = more than 1 epoch
G1 G1a G1a2 G1a3 ... G1b ... = adding more (newer and better) data, note G1a has better quality (and more) data than G0a