
# RWKV-3 430M

## Model Description

RWKV-3 430M is a L24-D1024 causal language model trained on the Pile. See https://github.com/BlinkDL/RWKV-LM for details.

At this moment you have to use my Github code (https://github.com/BlinkDL/RWKV-v2-RNN-Pile) to run it.

ctx_len = 768
n_layer = 24
n_embd = 1024

Final checkpoint: RWKV-3-Pile-430M-20220817-10602.pth : Trained on the Pile for 326B tokens.
* Pile loss 2.288
* LAMBADA ppl 12.83, acc 45.45%
* PIQA acc 68.50%
* SC2016 acc 63.60%
* Hellaswag acc_norm 40.68%

Preview checkpoint: RWKV-3-Pile-20220721-3029.pth : Trained on the Pile for 93B tokens.
* Pile loss 2.341
* LAMBADA ppl 14.18, acc 44.25%
* PIQA acc 67.95%
* SC2016 acc 63.39%
* Hellaswag acc_norm 39.06%

{"language": ["en"], "license": "apache-2.0", "tags": ["pytorch", "text-generation", "causal-lm", "rwkv"], "datasets": ["The Pile"]}
pytorch text-generation causal-lm rwkv en license:apache-2.0 has_space region:us
TAGS
#pytorch #text-generation #causal-lm #rwkv #en #license-apache-2.0 #has_space #region-us 


# RWKV-3 430M

## Model Description

RWKV-3 430M is a L24-D1024 causal language model trained on the Pile. See URL for details.

At this moment you have to use my Github code (URL to run it.

ctx_len = 768
n_layer = 24
n_embd = 1024

Final checkpoint: URL : Trained on the Pile for 326B tokens.
* Pile loss 2.288
* LAMBADA ppl 12.83, acc 45.45%
* PIQA acc 68.50%
* SC2016 acc 63.60%
* Hellaswag acc_norm 40.68%

Preview checkpoint: URL : Trained on the Pile for 93B tokens.
* Pile loss 2.341
* LAMBADA ppl 14.18, acc 44.25%
* PIQA acc 67.95%
* SC2016 acc 63.39%
* Hellaswag acc_norm 39.06%

# RWKV-3 430M ## Model Description

RWKV-3 430M is a L24-D1024 causal language model trained on the Pile. See URL for details.

At this moment you have to use my Github code (URL to run it.

ctx_len = 768
n_layer = 24
n_embd = 1024

Final checkpoint: URL : Trained on the Pile for 326B tokens.
* Pile loss 2.288
* LAMBADA ppl 12.83, acc 45.45%
* PIQA acc 68.50%
* SC2016 acc 63.60%
* Hellaswag acc_norm 40.68%

Preview checkpoint: URL : Trained on the Pile for 93B tokens.
* Pile loss 2.341
* LAMBADA ppl 14.18, acc 44.25%
* PIQA acc 67.95%
* SC2016 acc 63.39%
* Hellaswag acc_norm 39.06%
TAGS
#pytorch #text-generation #causal-lm #rwkv #en #license-apache-2.0 #has_space #region-us 
 # RWKV-3 430M ## Model Description

RWKV-3 430M is a L24-D1024 causal language model trained on the Pile. See URL for details.

At this moment you have to use my Github code (URL to run it.

ctx_len = 768
n_layer = 24
n_embd = 1024

Final checkpoint: URL : Trained on the Pile for 326B tokens.
* Pile loss 2.288
* LAMBADA ppl 12.83, acc 45.45%
* PIQA acc 68.50%
* SC2016 acc 63.60%
* Hellaswag acc_norm 40.68%

Preview checkpoint: URL : Trained on the Pile for 93B tokens.
* Pile loss 2.341
* LAMBADA ppl 14.18, acc 44.25%
* PIQA acc 67.95%
* SC2016 acc 63.39%
* Hellaswag acc_norm 39.06%
passage: TAGS
#pytorch #text-generation #causal-lm #rwkv #en #license-apache-2.0 #has_space #region-us 
# RWKV-3 430M## Model Description

RWKV-3 430M is a L24-D1024 causal language model trained on the Pile. See URL for details.

At this moment you have to use my Github code (URL to run it.

ctx_len = 768
n_layer = 24
n_embd = 1024

Final checkpoint: URL : Trained on the Pile for 326B tokens.
* Pile loss 2.288
* LAMBADA ppl 12.83, acc 45.45%
* PIQA acc 68.50%
* SC2016 acc 63.60%
* Hellaswag acc_norm 40.68%

Preview checkpoint: URL : Trained on the Pile for 93B tokens.
* Pile loss 2.341
* LAMBADA ppl 14.18, acc 44.25%
* PIQA acc 67.95%
* SC2016 acc 63.39%
* Hellaswag acc_norm 39.06%