fix(server): fix llamav2 config (#635)

Author: OlivierDehaene

server/text_generation_server/models/custom_modeling/flash_llama_modeling.py

@@ -23,6 +23,7 @@
 
 from torch import nn
 from transformers.activations import ACT2FN
+from transformers.configuration_utils import PretrainedConfig
 from typing import Optional, List, Tuple
 
 # Flash attention imports
@@ -43,6 +44,56 @@
 )
 
 
+class LlamaConfig(PretrainedConfig):
+    def __init__(
+        self,
+        vocab_size=32000,
+        hidden_size=4096,
+        intermediate_size=11008,
+        num_hidden_layers=32,
+        num_attention_heads=32,
+        num_key_value_heads=None,
+        hidden_act="silu",
+        max_position_embeddings=2048,
+        initializer_range=0.02,
+        rms_norm_eps=1e-6,
+        use_cache=True,
+        pad_token_id=0,
+        bos_token_id=1,
+        eos_token_id=2,
+        pretraining_tp=1,
+        tie_word_embeddings=False,
+        rope_scaling=None,
+        **kwargs,
+    ):
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+
+        # for backward compatibility
+        if num_key_value_heads is None:
+            num_key_value_heads = num_attention_heads
+
+        self.num_key_value_heads = num_key_value_heads
+        self.hidden_act = hidden_act
+        self.initializer_range = initializer_range
+        self.rms_norm_eps = rms_norm_eps
+        self.pretraining_tp = pretraining_tp
+        self.use_cache = use_cache
+        self.rope_scaling = rope_scaling
+
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )
+
+
 class LlamaRMSNorm(nn.Module):
     def __init__(self, prefix, weights, eps=1e-6):
         """

server/text_generation_server/models/flash_llama.py

@@ -2,13 +2,13 @@
 import torch.distributed
 
 from opentelemetry import trace
-from transformers import AutoConfig
 from transformers.models.llama import LlamaTokenizer, LlamaTokenizerFast
 from typing import Optional
 
 from text_generation_server.models import FlashCausalLM
 from text_generation_server.models.custom_modeling.flash_llama_modeling import (
     FlashLlamaForCausalLM,
+    LlamaConfig,
 )
 from text_generation_server.utils import (
     initialize_torch_distributed,
@@ -52,7 +52,7 @@ def __init__(
                 trust_remote_code=trust_remote_code,
             )
 
-        config = AutoConfig.from_pretrained(
+        config = LlamaConfig.from_pretrained(
             model_id, revision=revision, trust_remote_code=trust_remote_code
         )