from rwkvstic.agnostic.backends import TORCH, TORCH_QUANT import torch quantized = { "mode": TORCH_QUANT, "runtimedtype": torch.bfloat16, "useGPU": torch.cuda.is_available(), "chunksize": 32, # larger = more accurate, but more memory "target": 100 # your gpu max size, excess vram offloaded to cpu } # UNCOMMENT TO SELECT OPTIONS # Not full list of options, see https://pypi.org/project/rwkvstic/ and https://huggingface.co/BlinkDL/ for more models/modes # RWKV 1B5 instruct test 1 model # Approximate # [Vram usage: 6.0GB] # [File size: 3.0GB] config = { "path":"https://huggingface.co/mrsteyk/RWKV-LM-safetensors/resolve/main/RWKV-4-Pile-7B-Instruct-test1-20230124.rnn.safetensors", } title = "RWKV-7B ( rwkv-rs, CPU )" # RWKV 1B5 instruct model quantized # Approximate # [Vram usage: 1.3GB] # [File size: 3.0GB] # config = { # "path": "https://huggingface.co/BlinkDL/rwkv-4-pile-1b5/resolve/main/RWKV-4-Pile-1B5-Instruct-test1-20230124.pth", # **quantized # } # title = "RWKV-4 (1.5b Instruct Quantized)" # RWKV 7B instruct pre-quantized (settings baked into model) # Approximate # [Vram usage: 7.0GB] # [File size: 8.0GB] # config = { # "path": "https://huggingface.co/Hazzzardous/RWKV-8Bit/resolve/main/RWKV-4-Pile-7B-Instruct.pqth" # } # title = "RWKV-4 (7b Instruct Quantized)" # RWKV 14B quantized (latest as of feb 9) # Approximate # [Vram usage: 15.0GB] # [File size: 15.0GB] # config = { # "path": "https://huggingface.co/Hazzzardous/RWKV-8Bit/resolve/main/RWKV-4-Pile-14B-20230204-7324.pqth" # } # title = "RWKV-4 (14b 94% trained, not yet instruct tuned, 8-Bit)"