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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":"14B-8K-rwkvstic-2-1-2.rwkv"
    #"useLogFix":False # When enabled, use BlinkDLs version of the att.
}

title = "RWKV-4 (14B 8k)"

# 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.pqth",
     **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)"