[Test-fix]: HF_TOKEN param removed from MM test Script (#425)

### Previous Behavior:
The `HF_TOKEN` parameter in the test script was explicitly set to an
empty string. This caused authentication failures with Hugging Face, as
an empty token overrides the environment-provided `HF_TOKEN`, preventing
its intended use.

### Current Update:
The `HF_TOKEN `parameter has been removed from the script. The script
will now default to using the `HF_TOKEN `from the environment, allowing
user-provided tokens to be utilized as expected.

---------

Signed-off-by: Abukhoyer Shaik <[email protected]>

Author: abukhoy

tests/transformers/models/test_image_text_to_text_models.py

@@ -27,7 +27,6 @@
 from QEfficient.utils.run_utils import ApiRunnerInternVL, ApiRunnerVlm
 from QEfficient.utils.test_utils import InternProcessor
 
-HF_TOKEN = ""
 NEW_GENERATION_TOKENS = 10
 test_models_config = [
     # CONFIG PARAMS NEEDED FOR A MODEL TO BE TESTED
@@ -104,21 +103,18 @@
 def load_image_text_to_text_model(model_config):
     model_path = hf_download(
         repo_id=model_config._name_or_path,
-        hf_token=HF_TOKEN,
         ignore_patterns=["*.onnx", "*.ot", "*.md", "*.tflite", "*.pdf", "*.h5", "*.msgpack"],
     )
     try:
         model_hf = AutoModelForImageTextToText.from_pretrained(
             model_path,
             low_cpu_mem_usage=False,
-            token=HF_TOKEN,
             config=model_config,
         )
     except ValueError:
         model_hf = AutoModelForCausalLM.from_pretrained(
             model_path,
             low_cpu_mem_usage=False,
-            token=HF_TOKEN,
             trust_remote_code=True,
             config=model_config,
         )
@@ -160,9 +156,7 @@ def check_image_text_to_text_pytorch_vs_kv_vs_ort_vs_ai100(
 ):
     model_config = {"model_name": model_name}
     model_config["img_size"] = img_size
-    config = AutoConfig.from_pretrained(
-        model_config["model_name"], token=HF_TOKEN, trust_remote_code=True, padding=True
-    )
+    config = AutoConfig.from_pretrained(model_config["model_name"], trust_remote_code=True, padding=True)
     config = set_num_layers(config, n_layer=n_layer)
     model_hf, _ = load_image_text_to_text_model(config)
     processor = AutoProcessor.from_pretrained(model_name, trust_remote_code=True, padding=True)
@@ -199,7 +193,6 @@ def check_image_text_to_text_pytorch_vs_kv_vs_ort_vs_ai100(
         model_config["model_name"],
         kv_offload=kv_offload,
         config=config,
-        token=HF_TOKEN,
     )
 
     # pytorch_kv_tokens = api_runner.run_vlm_kv_model_on_pytorch(qeff_model.model)
@@ -284,7 +277,6 @@ def check_intern_image_text_to_text_pytorch_vs_kv_vs_ort_vs_ai100(
         model_config["model_name"],
         kv_offload=kv_offload,
         config=config,
-        token=HF_TOKEN,
     )
     # pytorch_kv_tokens = api_runner.run_vlm_kv_model_on_pytorch(qeff_model.model)
     # assert (pytorch_hf_tokens == pytorch_kv_tokens).all(), (