初始化项目，由ModelHub XC社区提供模型

Model: cygu/llama-2-7b-logit-watermark-distill-kgw-k1-gamma0.25-delta2
Source: Original Platform

README.md

@@ -0,0 +1,34 @@
+---
+tags:
+- generated_from_trainer
+datasets:
+- openwebtext
+license: llama2
+---
+
+## Model description
+
+Logit-based watermark distilled Llama 2 7B using the KGW \\(k=1, \gamma=0.25, \delta=2\\) watermarking strategy in the paper [On the Learnability of Watermarks for Language Models](https://arxiv.org/abs/2312.04469).
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 64
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.13.1
+- Tokenizers 0.13.3