✨ feat: add GLM-4-9B-Chat-1M model support

Add support for GLM-4 model architecture with the following changes:

- Add glm4.py with ChatGLMForCausalLM, GLM4Model, GLM4Attention, GLM4MLP
- Add GLM4RotaryEmbedding with interleaved partial rotation (rotary_dim = head_dim // 2)
- Add apply_rotary_emb_interleaved function for GLM-4 style RoPE
- Add GLM-4 weight name conversion and loading in loader.py
- Add GLM-4 chat template conversion in test_ruler.py
- Add trust_remote_code=True for GLM-4 config loading

Key GLM-4 specific adaptations:
- QKV bias enabled (add_qkv_bias: true)
- RoPE with rope_ratio scaling (base = 10000 * rope_ratio)
- Interleaved RoPE (pairs adjacent elements, not first/second half)
- Partial rotation (only half of head_dim is rotated)
- Uses multi_query_group_num instead of num_key_value_heads
- Uses kv_channels instead of head_dim
- Uses ffn_hidden_size instead of intermediate_size

Tested with RULER niah_single_1 (5 samples): 100% accuracy
Both GPU-only and CPU offload modes verified

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

nanovllm/config.py

@@ -57,8 +57,11 @@ class Config:
         assert os.path.isdir(self.model)
         assert self.kvcache_block_size % 256 == 0
         assert 1 <= self.tensor_parallel_size <= 8
-        self.hf_config = AutoConfig.from_pretrained(self.model)
-        self.max_model_len = min(self.max_model_len, self.hf_config.max_position_embeddings)
+        self.hf_config = AutoConfig.from_pretrained(self.model, trust_remote_code=True)
+        # Get max position embeddings (GLM-4 uses seq_length instead of max_position_embeddings)
+        max_pos = getattr(self.hf_config, 'max_position_embeddings',
+                         getattr(self.hf_config, 'seq_length', 4096))
+        self.max_model_len = min(self.max_model_len, max_pos)
         assert self.max_num_batched_tokens >= self.max_model_len
 
         # Override torch_dtype if user specified