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InternLM
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zhulin1 2024-02-27 15:10:23 +08:00
parent b073d840de
commit 4ca04ddcc3
4 changed files with 36 additions and 10 deletions
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44
tests/test_hf_model.py
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@ -9,6 +9,8 @@ prompts = ['你好', "what's your name"]
def assert_model(response):
assert len(response) != 0
assert 'UNUSED_TOKEN' not in response
assert 'Mynameis' not in response
assert 'Iama' not in response
class TestChat:
@ -21,9 +23,17 @@ class TestChat:
'internlm/internlm2-chat-1_8b', 'internlm/internlm2-chat-1_8b-sft'
],
)
def test_demo_default(self, model_name):
@pytest.mark.parametrize(
'usefast',
[
True,
False,
],
)
def test_demo_default(self, model_name, usefast):
tokenizer = AutoTokenizer.from_pretrained(model_name,
trust_remote_code=True)
trust_remote_code=True,
use_fast=usefast)
# Set `torch_dtype=torch.float16` to load model in float16, otherwise
# it will be loaded as float32 and might cause OOM Error.
model = AutoModelForCausalLM.from_pretrained(
@ -57,9 +67,17 @@ class TestBase:
'internlm/internlm2-1_8b'
],
)
def test_demo_default(self, model_name):
@pytest.mark.parametrize(
'usefast',
[
True,
False,
],
)
def test_demo_default(self, model_name, usefast):
tokenizer = AutoTokenizer.from_pretrained(model_name,
trust_remote_code=True)
trust_remote_code=True,
use_fast=usefast)
# Set `torch_dtype=torch.float16` to load model in float16, otherwise
# it will be loaded as float32 and might cause OOM Error.
model = AutoModelForCausalLM.from_pretrained(
@ -90,9 +108,17 @@ class TestMath:
'model_name',
['internlm/internlm2-math-7b', 'internlm/internlm2-math-base-7b'],
)
def test_demo_default(self, model_name):
@pytest.mark.parametrize(
'usefast',
[
True,
False,
],
)
def test_demo_default(self, model_name, usefast):
tokenizer = AutoTokenizer.from_pretrained(model_name,
trust_remote_code=True)
trust_remote_code=True,
use_fast=usefast)
# Set `torch_dtype=torch.float16` to load model in float16, otherwise
# it will be loaded as float32 and might cause OOM Error.
model = AutoModelForCausalLM.from_pretrained(
@ -106,6 +132,7 @@ class TestMath:
meta_instruction='')
print(response)
assert_model(response)
assert '2' in response
class TestMMModel:
@ -127,7 +154,7 @@ class TestMMModel:
model_name, torch_dtype=torch.float32,
trust_remote_code=True).cuda()
tokenizer = AutoTokenizer.from_pretrained(model_name,
trust_remote_code=True)
trust_remote_code=True)
model = model.eval()
img_path_list = [
@ -184,7 +211,7 @@ class TestMMVlModel:
model = AutoModel.from_pretrained(
model_name, trust_remote_code=True).cuda().eval()
tokenizer = AutoTokenizer.from_pretrained(model_name,
trust_remote_code=True)
trust_remote_code=True)
query = '<ImageHere>Please describe this image in detail.'
image = 'tests/image.webp'
@ -198,4 +225,3 @@ class TestMMVlModel:
assert len(response) != 0
assert 'Oscar Wilde' in response
assert 'Live life with no excuses, travel with no regret' in response