update model

tests/python_tests/test_cache_optimizations.py

@@ -150,7 +150,7 @@ def test_cache_optimized_generation_is_similar_to_unoptimized(converted_model, t
 
 @pytest.fixture(scope='module')
 def phi3_converted_model(tmp_path_factory):
-    model_id = "microsoft/Phi-3-mini-4k-instruct"
+    model_id = "meta-llama/Llama-3.2-3B-Instruct"
     model = OVModelForCausalLM.from_pretrained(model_id, export=True, trust_remote_code=True)
     tokenizer = AutoTokenizer.from_pretrained(model_id)
     models_path = tmp_path_factory.mktemp("cacheopt_test_models") / model_id
@@ -167,7 +167,7 @@ def phi3_converted_model(tmp_path_factory):
 @pytest.mark.precommit
 @pytest.mark.parametrize("subset", ["samsum", "qmsum", "trec", "qasper", "hotpotqa", "repobench-p"])
 def test_unoptimized_generation_longbench(phi3_converted_model, subset):
-    seqs_per_request = 2
+    seqs_per_request = 32
     num_kv_blocks = 1000
     scheduler_config = get_scheduler_config(num_kv_blocks)
     models_path = phi3_converted_model.models_path

tests/python_tests/utils_longbench.py

@@ -146,10 +146,12 @@ def qa_f1_score(prediction, ground_truth, **kwargs):
 
 # Max length for NVIDIA GeForce RTX 3090 (24 GB)
 model2maxlen = {
-    "meta-llama/Llama-2-7b-chat-hf": 3500,
+    "meta-llama/Llama-2-7b-chat-hf": 4096,
     "meta-llama/Meta-Llama-3-8B-Instruct": 5000,
-    "meta-llama/Llama-3.1-8B-Instruct": 5000,
+    "meta-llama/Llama-3.1-8B-Instruct": 10000,
     "microsoft/Phi-3-mini-4k-instruct": 4096,
+    'meta-llama/Llama-3.2-1B-Instruct': 10000,
+    'meta-llama/Llama-3.2-3B-Instruct': 10000,
 }
 
 dataset2maxlen = {
@@ -250,7 +252,7 @@ def preprocess_prompt(tokenizer, data_sample, subset, model_name):
 
 
 def post_process_pred(pred, subset, model_name):
-    if subset in ["samsum", "qsum", "hotpotqa", "qasper"] and "Llama-3-8B" in model_name:
+    if subset in ["samsum", "qsum", "hotpotqa", "qasper"] and "Llama-3" in model_name:
         pred = pred[:pred.find("assistant")]
     elif subset == "samsum":
         pred = pred[:pred.find("\nDialogue")]