✨ 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/engine/llm_engine.py

@@ -30,7 +30,7 @@ class LLMEngine:
             self.ps.append(process)
             self.events.append(event)
         self.model_runner = ModelRunner(config, 0, self.events)
-        self.tokenizer = AutoTokenizer.from_pretrained(config.model, use_fast=True)
+        self.tokenizer = AutoTokenizer.from_pretrained(config.model, use_fast=True, trust_remote_code=True)
         config.eos = self.tokenizer.eos_token_id
         # Set Sequence.block_size to match the KV cache block size
         Sequence.block_size = config.kvcache_block_size