Separate Qwen2 from Qwen3 implementation:
- Qwen2: Uses QKV bias, no QK norm
- Qwen3: Has optional QK norm when no bias
Tested with Qwen2.5-7B-Instruct-1M, RULER niah_single_1 passed.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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>
