[CI/UT] Unify model usage via ModelScope in CI (#1207)

### What this PR does / why we need it?
Unify Model Usage via ModelScope

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
CI passed

Signed-off-by: hfadzxy <starmoon_zhang@163.com>

.github/workflows/accuracy_test.yaml

@@ -125,10 +125,9 @@ jobs:
     container:
       image: m.daocloud.io/quay.io/ascend/cann:8.1.rc1-910b-ubuntu22.04-py3.10
       env:
-        HF_ENDPOINT: https://hf-mirror.com
-        HF_TOKEN: ${{ secrets.HF_TOKEN }}
         DATASET_SOURCE: ModelScope
         VLLM_USE_MODELSCOPE: True
+        USE_MODELSCOPE_HUB: 1
         # 1. If version specified (work_dispatch), do specified branch accuracy test
         # 2. If no version (labeled PR), do accuracy test by default ref:
         # The branch, tag or SHA to checkout. When checking out the repository that

.github/workflows/nightly_benchmarks.yaml

@@ -69,8 +69,7 @@ jobs:
         --device /dev/devmm_svm
         --device /dev/hisi_hdc
       env:
-        HF_ENDPOINT: https://hf-mirror.com
-        HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        VLLM_USE_MODELSCOPE: True
         ES_OM_DOMAIN: ${{ secrets.ES_OM_DOMAIN }}
         ES_OM_AUTHORIZATION: ${{ secrets.ES_OM_AUTHORIZATION }}
         VLLM_USE_V1: ${{ matrix.vllm_use_v1 }}

.github/workflows/vllm_ascend_test.yaml

@@ -209,6 +209,7 @@ jobs:
       image: m.daocloud.io/quay.io/ascend/cann:8.1.rc1-910b-ubuntu22.04-py3.10
       env:
         VLLM_LOGGING_LEVEL: ERROR
+        VLLM_USE_MODELSCOPE: True
     steps:
       - name: Check npu and CANN info
         run: |
@@ -257,9 +258,7 @@ jobs:
           VLLM_USE_MODELSCOPE: True
         run: |
           pytest -sv tests/e2e/singlecard/test_offline_inference.py
-          # TODO: switch hf to modelscope
-          VLLM_USE_MODELSCOPE=False HF_ENDPOINT=https://hf-mirror.com \
-            pytest -sv tests/e2e/singlecard/test_ilama_lora.py
+          pytest -sv tests/e2e/singlecard/test_ilama_lora.py
           pytest -sv tests/e2e/singlecard/test_guided_decoding.py
           pytest -sv tests/e2e/singlecard/test_camem.py
           pytest -sv tests/e2e/singlecard/test_embedding.py
@@ -277,9 +276,7 @@ jobs:
           VLLM_USE_MODELSCOPE: True
         run: |
           pytest -sv tests/e2e/singlecard/test_offline_inference.py
-          # TODO: switch hf to modelscope
-          VLLM_USE_MODELSCOPE=False HF_ENDPOINT=https://hf-mirror.com \
-            pytest -sv tests/e2e/singlecard/test_ilama_lora.py
+          pytest -sv tests/e2e/singlecard/test_ilama_lora.py
           pytest -sv tests/e2e/singlecard/test_guided_decoding.py
           pytest -sv tests/e2e/singlecard/test_camem.py
           pytest -sv tests/e2e/singlecard/test_prompt_embedding.py
@@ -357,9 +354,7 @@ jobs:
           VLLM_WORKER_MULTIPROC_METHOD: spawn
           VLLM_USE_MODELSCOPE: True
         run: |
-          # TODO: switch hf to modelscope
-          VLLM_USE_MODELSCOPE=False HF_ENDPOINT=https://hf-mirror.com \
-            pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py
+          pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py
           # Fixme: run VLLM_USE_MODELSCOPE=True pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py will raise error.
           # To avoid oom, we need to run the test in a single process.
           pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_DeepSeek_multistream_moe
@@ -380,9 +375,7 @@ jobs:
           VLLM_USE_V1: 0
           VLLM_USE_MODELSCOPE: True
         run: |
-          # TODO: switch hf to modelscope
-          VLLM_USE_MODELSCOPE=False HF_ENDPOINT=https://hf-mirror.com \
-            pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py
+          pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py
           # Fixme: run VLLM_USE_MODELSCOPE=True pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py will raise error.
           # To avoid oom, we need to run the test in a single process.
           pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_QwQ

.github/workflows/vllm_ascend_test_long_term.yaml

@@ -50,9 +50,8 @@ jobs:
       # TODO(yikun): Remove m.daocloud.io prefix when infra proxy ready
       image: m.daocloud.io/quay.io/ascend/cann:8.1.rc1-910b-ubuntu22.04-py3.10
       env:
-        HF_ENDPOINT: https://hf-mirror.com
-        HF_TOKEN: ${{ secrets.HF_TOKEN }}
         VLLM_LOGGING_LEVEL: ERROR
+        VLLM_USE_MODELSCOPE: True
     steps:
       - name: Check npu and CANN info
         run: |

.github/workflows/vllm_ascend_test_pd.yaml

@@ -64,8 +64,7 @@ jobs:
         --device /dev/devmm_svm
         --device /dev/hisi_hdc
       env:
-        HF_ENDPOINT: https://hf-mirror.com
-        HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        VLLM_USE_MODELSCOPE: True
     steps:
       - name: Check npu and CANN info
         run: |