diff --git a/README.md b/README.md
index edead901..24058be8 100644
--- a/README.md
+++ b/README.md
@@ -75,7 +75,7 @@
     cd tensorrt_llm_july-release-v1/examples/qwen/
     ```
 
-7. 将Huggingface格式的数据转成FT(FastTransformer)需要的数据格式（非必选，不convert直接build也是可以的，两种方式都兼容，直接build更省空间，但是不支持smooth quant）
+7. 将Huggingface格式的数据转成FT(FastTransformer)需要的数据格式（非必选，不convert直接build也是可以的，两种方式都兼容，直接build更省空间，但是不支持smooth quant; 运行该代码默认是需要加载cuda版huggingface模型再转换，所以低于24G显存的显卡建议跳过这步。）
 
     ```bash
     python3 hf_qwen_convert.py
@@ -83,7 +83,7 @@
 
 8. 修改编译参数（可选）
 
-    - 默认编译参数，包括batch_size, max_input_len, max_new_tokens都存放在`default_config.py`中
+    - 默认编译参数，包括batch_size, max_input_len, max_new_tokens, seq_length都存放在`default_config.py`中
     - 对于24G显存用户，直接编译即可，默认是fp16数据类型，max_batch_size=2
     - 对于低显存用户，可以降低max_batch_size=1，或者继续降低max_input_len, max_new_tokens
 
diff --git a/requirements-dev.txt b/requirements-dev.txt
index 2496650e..1d76afa1 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -8,7 +8,7 @@ onnx==1.12.0
 mpi4py
 tensorrt>=8.6.0
 numpy
-cuda-python==12.1.0
+cuda-python==12.2.0
 mypy
 pytest-cov
 pytest-xdist
diff --git a/tensorrt_llm_july-release-v1/examples/qwen/build.py b/tensorrt_llm_july-release-v1/examples/qwen/build.py
index db610fe9..b39f562c 100644
--- a/tensorrt_llm_july-release-v1/examples/qwen/build.py
+++ b/tensorrt_llm_july-release-v1/examples/qwen/build.py
@@ -323,7 +323,7 @@ def build_rank_engine(builder: Builder,
         num_layers=args.n_layer,
         num_heads=args.n_head,
         hidden_size=args.n_embd,
-        seq_length=2048,
+        seq_length=default_config.seq_length,
         vocab_size=args.vocab_size,
         hidden_act=args.hidden_act,
         max_position_embeddings=args.n_positions,
@@ -360,7 +360,8 @@ def build_rank_engine(builder: Builder,
             QuantMode.use_weight_only(use_int4_weights=True)
         )
 
-    if args.hf_model_dir is not None and args.ft_dir_path is None:
+    if args.hf_model_dir is not None and \
+        (args.ft_dir_path is None or not os.path.exists(args.ft_dir_path)):
         logger.info(f'Loading HF QWen ... from {args.hf_model_dir}')
         tik = time.time()
         hf_qwen = AutoModelForCausalLM.from_pretrained(
@@ -381,7 +382,6 @@ def build_rank_engine(builder: Builder,
             rank,
             args.world_size,
             max_position_embeddings=args.n_positions,
-            seq_length=args.max_input_len,
             kv_channels=args.kv_channels,
             rotary_emb_base=args.rotary_emb_base,
             dtype=args.dtype,
diff --git a/tensorrt_llm_july-release-v1/examples/qwen/default_config.py b/tensorrt_llm_july-release-v1/examples/qwen/default_config.py
index accebae6..9d9a2d74 100644
--- a/tensorrt_llm_july-release-v1/examples/qwen/default_config.py
+++ b/tensorrt_llm_july-release-v1/examples/qwen/default_config.py
@@ -24,6 +24,11 @@ class DefaultConfig:
     # Maximum number of generate new tokens.
     max_new_tokens = 2048
 
+    # Maximum sequence length.
+    # for Qwen-7B-Chat V1.0, the seq_length is 2048
+    # for Qwen-7B-Chat V1.1, the seq_length is 8192
+    # for Qwen-14B-Chat, the seq_length is 8192
+    seq_length = 2048
 
     # Top p for sampling.
     top_p = 0.5
diff --git a/tensorrt_llm_july-release-v1/examples/qwen/weight.py b/tensorrt_llm_july-release-v1/examples/qwen/weight.py
index 22dc4bda..a05fc90c 100644
--- a/tensorrt_llm_july-release-v1/examples/qwen/weight.py
+++ b/tensorrt_llm_july-release-v1/examples/qwen/weight.py
@@ -391,7 +391,6 @@ def load_from_hf_qwen(tensorrt_llm_qwen: QWenForCausalLM,
                        hf_qwen,
                        rank=0,
                        tensor_parallel=1,
-                       seq_length=2048,
                        max_position_embeddings=8192,
                        rotary_emb_base=10000,
                        kv_channels=128,
@@ -463,7 +462,7 @@ def load_from_hf_qwen(tensorrt_llm_qwen: QWenForCausalLM,
             if layer_idx is None:
                 continue
             idx = int(layer_idx)
-            if idx >= tensorrt_llm_qwen.num_layers:
+            if idx >= tensorrt_llm_qwen._num_layers:
                 continue
             if 'ln_1.weight' in k:
                 tensorrt_llm_qwen.layers[idx].ln_1.weight.value = v