Hotfix: fix of use of unquantized weights in Mixtral GQA loading (#2269)

* Update idefics_causal_lm.py

Fix syntax issues

* fix dbrx & opt model prefix bug

* Hotfix: fix of use of unquantized weights in Mixtral GQA loading

server/text_generation_server/models/custom_modeling/flash_mixtral_modeling.py

@@ -52,6 +52,7 @@ from text_generation_server.layers.layernorm import (
 from text_generation_server.layers.rotary import (
     PositionRotaryEmbedding,
 )
+from text_generation_server.utils.weights import UnquantizedWeight
 
 
 class MixtralConfig(PretrainedConfig):
@@ -138,16 +139,16 @@ def _load_gqa(config, prefix: str, weights):
         dim=0,
     )
 
-    if config.quantize not in ["gptq", "awq", "marlin"]:
-        weight = weight.to(dtype=weights.dtype).to(device=weights.device)
+    if isinstance(weight, UnquantizedWeight):
+        weight.weight = weight.weight.to(dtype=weights.dtype).to(device=weights.device)
 
         head_size = config.hidden_size // config.num_attention_heads
         num_heads = config.num_attention_heads // weights.process_group.size()
         num_key_value_heads = config.num_key_value_heads // weights.process_group.size()
-        assert list(weight.shape) == [
+        assert list(weight.weight.shape) == [
             (num_heads + 2 * num_key_value_heads) * head_size,
             config.hidden_size,
-        ], f"{list(weight.shape)} != {[(num_heads + 2 * config.num_key_value_heads) * head_size, config.hidden_size]}"
+        ], f"{list(weight.weight.shape)} != {[(num_heads + 2 * config.num_key_value_heads) * head_size, config.hidden_size]}"
 
     return TensorParallelColumnLinear(get_linear(weight, bias=None))