feat(server): Support BLOOMChat-176B (#348) (#351)

@njhill, 
temporary workaround to be able to run our CI as secrets are not
available to runners run by external contributors. I will ask around to
see if there is a better way.
Co-authored-by: Nick Hill <nickhill@us.ibm.com>

server/text_generation_server/models/bloom.py

@@ -131,7 +131,10 @@ class BLOOMSharded(BLOOM):
                 file, framework="pt", device=str(device) if quantize is None else "cpu"
             ) as f:
                 for name in f.keys():
-                    full_name = f"transformer.{name}"
+                    if name.startswith("transformer.") or name.startswith("lm_head."):
+                        full_name = name
+                    else:
+                        full_name = f"transformer.{name}"
 
                     module_name, param_name = full_name.rsplit(".", 1)
                     module = model.get_submodule(module_name)
@@ -157,7 +160,7 @@ class BLOOMSharded(BLOOM):
                             # XXX: Hack for Rowlinear to add the bias only once.
                             if rank != 0:
                                 tensor = torch.zeros_like(tensor)
-                    elif isinstance(module, TensorParallelEmbedding):
+                    elif isinstance(module, TensorParallelEmbedding) or name == "lm_head.weight":
                         size = slice_.get_shape()[0]
                         block_size = size // world_size
                         start = rank * block_size

server/text_generation_server/models/causal_lm.py

@@ -504,6 +504,7 @@ class CausalLM(Model):
             position_ids=position_ids,
             past_key_values=past_key_values,
             use_cache=True,
+            return_dict=True,
         )
         return outputs.logits, outputs.past_key_values