diff --git a/pyvene/models/esm/__init__.py b/pyvene/models/esm/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/pyvene/models/esm/modelings_intervenable_esm.py b/pyvene/models/esm/modelings_intervenable_esm.py
new file mode 100644
index 00000000..5a5c21fa
--- /dev/null
+++ b/pyvene/models/esm/modelings_intervenable_esm.py
@@ -0,0 +1,63 @@
+"""
+Each modeling file in this library is a mapping between
+abstract naming of intervention anchor points and actual
+model module defined in the huggingface library.
+
+We also want to let the intervention library know how to
+config the dimensions of intervention based on model config
+defined in the huggingface library.
+"""
+
+from ..constants import (
+    CONST_INPUT_HOOK,
+    CONST_OUTPUT_HOOK
+)
+
+"""esm base model"""
+esm_type_to_module_mapping = dict(
+    block_input=("encoder.layer[%s]", CONST_INPUT_HOOK),
+    block_output=("encoder.layer[%s]", CONST_OUTPUT_HOOK),
+
+    mlp_input=("encoder.layer[%s].intermediate", CONST_INPUT_HOOK),
+    mlp_activation=("encoder.layer[%s].intermediate", CONST_OUTPUT_HOOK),
+    mlp_output=("encoder.layer[%s].output", CONST_OUTPUT_HOOK),
+
+    attention_value_output=("encoder.layer[%s].attention.output", CONST_INPUT_HOOK),
+    head_attention_value_output=("encoder.layer[%s].attention.output", CONST_INPUT_HOOK),
+
+    attention_input=("encoder.layer[%s].attention", CONST_INPUT_HOOK),
+    attention_output=("encoder.layer[%s].attention", CONST_OUTPUT_HOOK),
+
+    query_output=("encoder.layer[%s].attention.self.query", CONST_OUTPUT_HOOK),
+    head_query_output=("encoder.layer[%s].attention.self.query", CONST_OUTPUT_HOOK),
+    key_output=("encoder.layer[%s].attention.self.key", CONST_OUTPUT_HOOK),
+    head_key_output=("encoder.layer[%s].attention.self.key", CONST_OUTPUT_HOOK),
+    value_output=("encoder.layer[%s].attention.self.value", CONST_OUTPUT_HOOK),
+    head_value_output=("encoder.layer[%s].attention.self.value", CONST_OUTPUT_HOOK),
+
+)
+esm_type_to_dimension_mapping = dict(
+    block_input=("hidden_size",),
+    block_output=("hidden_size"),
+
+    mlp_input=("hidden_size",),
+    mlp_activation=("intermediate_size",),
+    mlp_output=("hidden_size",),
+
+    attention_value_output=("hidden_size",),
+    head_attention_value_output=("hidden_size/num_attention_heads",),
+
+    attention_input=("num_attention_heads",),
+    attention_output=("num_attention_heads/num_attention_heads",),
+
+    query_output=("num_attention_heads",),
+    head_query_output=("num_attention_heads/num_attention_heads",),
+    key_output=("num_attention_heads",),
+    head_key_output=("num_attention_heads/num_attention_heads",),
+    value_output=("num_attention_heads",),
+    head_value_output=("num_attention_heads/num_attention_heads",),
+)
+
+"""esm for mlm model"""
+esm_mlm_type_to_module_mapping = {k: ("esm." + i, j) for k, (i, j) in esm_type_to_module_mapping.items()}
+esm_mlm_type_to_dimension_mapping = esm_type_to_dimension_mapping.copy()
diff --git a/pyvene/models/intervenable_modelcard.py b/pyvene/models/intervenable_modelcard.py
index 1f7329f4..c500639b 100644
--- a/pyvene/models/intervenable_modelcard.py
+++ b/pyvene/models/intervenable_modelcard.py
@@ -13,6 +13,7 @@
 from .backpack_gpt2.modelings_intervenable_backpack_gpt2 import *
 from .llava.modelings_intervenable_llava import *
 from .olmo.modelings_intervenable_olmo import *
+from .esm.modelings_intervenable_esm import *
 
 #########################################################################
 """
@@ -63,6 +64,8 @@
     hf_models.gemma2.modeling_gemma2.Gemma2ForCausalLM: gemma2_lm_type_to_module_mapping,
     hf_models.olmo.modeling_olmo.OlmoModel: olmo_type_to_module_mapping,
     hf_models.olmo.modeling_olmo.OlmoForCausalLM: olmo_lm_type_to_module_mapping,  
+    hf_models.esm.modeling_esm.EsmModel: esm_type_to_module_mapping,
+    hf_models.esm.modeling_esm.EsmForMaskedLM: esm_mlm_type_to_module_mapping,
     hf_models.blip.modeling_blip.BlipForQuestionAnswering: blip_type_to_module_mapping,
     hf_models.blip.modeling_blip.BlipForImageTextRetrieval: blip_itm_type_to_module_mapping,
     MLPModel: mlp_type_to_module_mapping,
@@ -98,6 +101,8 @@
     hf_models.gemma2.modeling_gemma2.Gemma2ForCausalLM: gemma2_lm_type_to_dimension_mapping,
     hf_models.olmo.modeling_olmo.OlmoModel: olmo_type_to_dimension_mapping,
     hf_models.olmo.modeling_olmo.OlmoForCausalLM: olmo_lm_type_to_dimension_mapping, 
+    hf_models.esm.modeling_esm.EsmModel: esm_type_to_dimension_mapping,
+    hf_models.esm.modeling_esm.EsmForMaskedLM: esm_mlm_type_to_dimension_mapping,
     hf_models.blip.modeling_blip.BlipForQuestionAnswering: blip_type_to_dimension_mapping,
     hf_models.blip.modeling_blip.BlipForImageTextRetrieval: blip_itm_type_to_dimension_mapping,
     MLPModel: mlp_type_to_dimension_mapping,