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fix lint

pull/752/head
RangiLyu 2024-07-03 20:22:19 +08:00
parent 5e594c1699
commit 6908fa5e16
9 changed files with 140 additions and 106 deletions
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10
agent/pal_inference.py
View File

@ -189,8 +189,8 @@ def generate_interactive(
generation_config.max_length = generation_config.max_new_tokens + input_ids_seq_length generation_config.max_length = generation_config.max_new_tokens + input_ids_seq_length
if not has_default_max_length: if not has_default_max_length:
logger.warn( # pylint: disable=W4902 logger.warn( # pylint: disable=W4902
f"Both `max_new_tokens` (={generation_config.max_new_tokens}) and `max_length`(=" f'Both `max_new_tokens` (={generation_config.max_new_tokens}) and `max_length`(='
f"{generation_config.max_length}) seem to have been set. `max_new_tokens` will take precedence. " f'{generation_config.max_length}) seem to have been set. `max_new_tokens` will take precedence. '
'Please refer to the documentation for more information. ' 'Please refer to the documentation for more information. '
'(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)', '(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)',
UserWarning, UserWarning,
@ -199,8 +199,8 @@ def generate_interactive(
if input_ids_seq_length >= generation_config.max_length: if input_ids_seq_length >= generation_config.max_length:
input_ids_string = 'input_ids' input_ids_string = 'input_ids'
logger.warning( logger.warning(
f"Input length of {input_ids_string} is {input_ids_seq_length}, but `max_length` is set to" f'Input length of {input_ids_string} is {input_ids_seq_length}, but `max_length` is set to'
f" {generation_config.max_length}. This can lead to unexpected behavior. You should consider" f' {generation_config.max_length}. This can lead to unexpected behavior. You should consider'
' increasing `max_new_tokens`.') ' increasing `max_new_tokens`.')
# 2. Set generation parameters if not already defined # 2. Set generation parameters if not already defined
@ -510,7 +510,7 @@ def main():
interface.clear_history() interface.clear_history()
f.flush() f.flush()
print(f"{args.model}: Accuracy - {sum(scores) / len(scores)}") print(f'{args.model}: Accuracy - {sum(scores) / len(scores)}')
torch.cuda.empty_cache() torch.cuda.empty_cache()

13
chat/web_demo.py
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@ -77,7 +77,8 @@ def generate_interactive(
'max_length') is None and generation_config.max_length is not None 'max_length') is None and generation_config.max_length is not None
if has_default_max_length and generation_config.max_new_tokens is None: if has_default_max_length and generation_config.max_new_tokens is None:
warnings.warn( warnings.warn(
f"Using 'max_length''s default ({repr(generation_config.max_length)}) \ f"Using 'max_length''s default \
({repr(generation_config.max_length)}) \
to control the generation length. " to control the generation length. "
'This behaviour is deprecated and will be removed from the \ 'This behaviour is deprecated and will be removed from the \
config in v5 of Transformers -- we' config in v5 of Transformers -- we'
@ -102,7 +103,7 @@ def generate_interactive(
if input_ids_seq_length >= generation_config.max_length: if input_ids_seq_length >= generation_config.max_length:
input_ids_string = 'input_ids' input_ids_string = 'input_ids'
logger.warning( logger.warning(
f"Input length of {input_ids_string} is {input_ids_seq_length}, " f'Input length of {input_ids_string} is {input_ids_seq_length}, '
f"but 'max_length' is set to {generation_config.max_length}. " f"but 'max_length' is set to {generation_config.max_length}. "
'This can lead to unexpected behavior. You should consider' 'This can lead to unexpected behavior. You should consider'
" increasing 'max_new_tokens'.") " increasing 'max_new_tokens'.")
@ -180,9 +181,9 @@ def on_btn_click():
@st.cache_resource @st.cache_resource
def load_model(): def load_model():
model = (AutoModelForCausalLM.from_pretrained('internlm/internlm2_5-7b-chat', model = (AutoModelForCausalLM.from_pretrained(
trust_remote_code=True).to( 'internlm/internlm2_5-7b-chat',
torch.bfloat16).cuda()) trust_remote_code=True).to(torch.bfloat16).cuda())
tokenizer = AutoTokenizer.from_pretrained('internlm/internlm2_5-7b-chat', tokenizer = AutoTokenizer.from_pretrained('internlm/internlm2_5-7b-chat',
trust_remote_code=True) trust_remote_code=True)
return model, tokenizer return model, tokenizer
@ -216,7 +217,7 @@ def combine_history(prompt):
meta_instruction = ('You are InternLM (书生·浦语), a helpful, honest, ' meta_instruction = ('You are InternLM (书生·浦语), a helpful, honest, '
'and harmless AI assistant developed by Shanghai ' 'and harmless AI assistant developed by Shanghai '
'AI Laboratory (上海人工智能实验室).') 'AI Laboratory (上海人工智能实验室).')
total_prompt = f"<s><|im_start|>system\n{meta_instruction}<|im_end|>\n" total_prompt = f'<s><|im_start|>system\n{meta_instruction}<|im_end|>\n'
for message in messages: for message in messages:
cur_content = message['content'] cur_content = message['content']
if message['role'] == 'user': if message['role'] == 'user':

3
long_context/README.md
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@ -35,6 +35,7 @@ Currently, we support PDF, TXT, and Markdown files, with more file types to be s
### Installation ### Installation
To get started, install the required packages: To get started, install the required packages:
```bash ```bash
pip install "fairy-doc[cpu]" pip install "fairy-doc[cpu]"
pip install streamlit pip install streamlit
@ -77,8 +78,6 @@ The effect is demonstrated in the video below.
https://github.com/libowen2121/InternLM/assets/19970308/1d7f9b87-d458-4f24-9f7a-437a4da3fa6e https://github.com/libowen2121/InternLM/assets/19970308/1d7f9b87-d458-4f24-9f7a-437a4da3fa6e
## 🔜 Stay Tuned for More ## 🔜 Stay Tuned for More
We are continuously enhancing our models to better understand and reason with extensive long inputs. Expect new features, improved performance, and expanded capabilities in upcoming updates! We are continuously enhancing our models to better understand and reason with extensive long inputs. Expect new features, improved performance, and expanded capabilities in upcoming updates!

3
long_context/README_zh-CN.md
View File

@ -32,6 +32,7 @@
### 安装 ### 安装
开始前，请安装所需的依赖： 开始前，请安装所需的依赖：
```bash ```bash
pip install "fairy-doc[cpu]" pip install "fairy-doc[cpu]"
pip install streamlit pip install streamlit
@ -76,4 +77,4 @@ https://github.com/libowen2121/InternLM/assets/19970308/1d7f9b87-d458-4f24-9f7a-
## 🔜 敬请期待更多 ## 🔜 敬请期待更多
我们将不断优化和更新长文本模型，以提升其在长文本上的理解和分析能力。敬请关注！ 我们将不断优化和更新长文本模型，以提升其在长文本上的理解和分析能力。敬请关注！

145
long_context/doc_chat_demo.py
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@ -1,12 +1,15 @@
import argparse
import logging import logging
from dataclasses import dataclass from dataclasses import dataclass
import streamlit as st import streamlit as st
from openai import OpenAI
from magic_doc.docconv import DocConverter from magic_doc.docconv import DocConverter
import argparse from openai import OpenAI
# Set up logging # Set up logging
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") logging.basicConfig(level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s')
@dataclass @dataclass
class GenerationConfig: class GenerationConfig:
@ -16,13 +19,14 @@ class GenerationConfig:
temperature: float = 0.1 temperature: float = 0.1
repetition_penalty: float = 1.005 repetition_penalty: float = 1.005
def generate( def generate(
client, client,
messages, messages,
generation_config, generation_config,
): ):
stream = client.chat.completions.create( stream = client.chat.completions.create(
model=st.session_state["model_name"], model=st.session_state['model_name'],
messages=messages, messages=messages,
stream=True, stream=True,
temperature=generation_config.temperature, temperature=generation_config.temperature,
@ -32,113 +36,140 @@ def generate(
) )
return stream return stream
def prepare_generation_config(): def prepare_generation_config():
with st.sidebar: with st.sidebar:
max_tokens = st.number_input("Max Tokens", min_value=100, max_value=4096, value=1024) max_tokens = st.number_input('Max Tokens',
top_p = st.number_input("Top P", 0.0, 1.0, 1.0, step=0.01) min_value=100,
temperature = st.number_input("Temperature", 0.0, 1.0, 0.05, step=0.01) max_value=4096,
repetition_penalty = st.number_input("Repetition Penalty", 0.8, 1.2, 1.02, step=0.001, format="%0.3f") value=1024)
st.button("Clear Chat History", on_click=on_btn_click) top_p = st.number_input('Top P', 0.0, 1.0, 1.0, step=0.01)
temperature = st.number_input('Temperature', 0.0, 1.0, 0.05, step=0.01)
repetition_penalty = st.number_input('Repetition Penalty',
0.8,
1.2,
1.02,
step=0.001,
format='%0.3f')
st.button('Clear Chat History', on_click=on_btn_click)
generation_config = GenerationConfig( generation_config = GenerationConfig(max_tokens=max_tokens,
max_tokens=max_tokens, top_p=top_p,
top_p=top_p, temperature=temperature,
temperature=temperature, repetition_penalty=repetition_penalty)
repetition_penalty=repetition_penalty
)
return generation_config return generation_config
def on_btn_click(): def on_btn_click():
del st.session_state.messages del st.session_state.messages
st.session_state.file_content_found = False st.session_state.file_content_found = False
st.session_state.file_content_used = False st.session_state.file_content_used = False
user_avator = 'assets/user.png' user_avator = 'assets/user.png'
robot_avator = 'assets/robot.png' robot_avator = 'assets/robot.png'
st.title('InternLM2.5 File Chat 📝') st.title('InternLM2.5 File Chat 📝')
def main(base_url): def main(base_url):
# Initialize the client for the model # Initialize the client for the model
client = OpenAI( client = OpenAI(base_url=base_url, timeout=12000)
base_url=base_url,
timeout=12000
)
# Get the model ID # Get the model ID
model_name = client.models.list().data[0].id model_name = client.models.list().data[0].id
st.session_state["model_name"] = model_name st.session_state['model_name'] = model_name
# Get the generation config # Get the generation config
generation_config = prepare_generation_config() generation_config = prepare_generation_config()
# Initialize session state # Initialize session state
if "messages" not in st.session_state: if 'messages' not in st.session_state:
st.session_state.messages = [] st.session_state.messages = []
if "file_content_found" not in st.session_state: if 'file_content_found' not in st.session_state:
st.session_state.file_content_found = False st.session_state.file_content_found = False
st.session_state.file_content_used = False st.session_state.file_content_used = False
st.session_state.file_name = "" st.session_state.file_name = ''
# Handle file upload # Handle file upload
if not st.session_state.file_content_found: if not st.session_state.file_content_found:
uploaded_file = st.file_uploader("Upload an article", type=("txt", "md", "pdf")) uploaded_file = st.file_uploader('Upload an article',
file_content = "" type=('txt', 'md', 'pdf'))
file_content = ''
if uploaded_file is not None: if uploaded_file is not None:
if uploaded_file.type == "application/pdf": if uploaded_file.type == 'application/pdf':
with open("uploaded_file.pdf", "wb") as f: with open('uploaded_file.pdf', 'wb') as f:
f.write(uploaded_file.getbuffer()) f.write(uploaded_file.getbuffer())
converter = DocConverter(s3_config=None) converter = DocConverter(s3_config=None)
file_content, time_cost = converter.convert("uploaded_file.pdf", conv_timeout=300) file_content, time_cost = converter.convert(
st.session_state.file_content_found = True # Reset flag when a new file is uploaded 'uploaded_file.pdf', conv_timeout=300)
st.session_state.file_content = file_content # Store the file content in session state # Reset flag when a new file is uploaded
st.session_state.file_name = uploaded_file.name # Store the file name in session state st.session_state.file_content_found = True
# Store the file content in session state
st.session_state.file_content = file_content
# Store the file name in session state
st.session_state.file_name = uploaded_file.name
else: else:
file_content = uploaded_file.read().decode("utf-8") file_content = uploaded_file.read().decode('utf-8')
st.session_state.file_content_found = True # Reset flag when a new file is uploaded # Reset flag when a new file is uploaded
st.session_state.file_content = file_content # Store the file content in session state st.session_state.file_content_found = True
st.session_state.file_name = uploaded_file.name # Store the file name in session state # Store the file content in session state
st.session_state.file_content = file_content
# Store the file name in session state
st.session_state.file_name = uploaded_file.name
if st.session_state.file_content_found: if st.session_state.file_content_found:
st.success(f"File '{st.session_state.file_name}' has been successfully uploaded!") st.success(f"File '{st.session_state.file_name}' "
'has been successfully uploaded!')
# Display chat messages # Display chat messages
for message in st.session_state.messages: for message in st.session_state.messages:
with st.chat_message(message["role"], avatar=message.get("avatar")): with st.chat_message(message['role'], avatar=message.get('avatar')):
st.markdown(message["content"]) st.markdown(message['content'])
# Handle user input and response generation # Handle user input and response generation
if prompt := st.chat_input("What's up?"): if prompt := st.chat_input("What's up?"):
turn = {"role": "user", "content": prompt, "avatar": user_avator} turn = {'role': 'user', 'content': prompt, 'avatar': user_avator}
if st.session_state.file_content_found and not st.session_state.file_content_used: if (st.session_state.file_content_found
and not st.session_state.file_content_used):
assert st.session_state.file_content is not None assert st.session_state.file_content is not None
merged_prompt = f"{st.session_state.file_content}\n\n{prompt}" merged_prompt = f'{st.session_state.file_content}\n\n{prompt}'
st.session_state.file_content_used = True # Set flag to indicate file content has been used # Set flag to indicate file content has been used
turn["merged_content"] = merged_prompt st.session_state.file_content_used = True
turn['merged_content'] = merged_prompt
st.session_state.messages.append(turn) st.session_state.messages.append(turn)
with st.chat_message("user", avatar=user_avator): with st.chat_message('user', avatar=user_avator):
st.markdown(prompt) st.markdown(prompt)
with st.chat_message("assistant", avatar=robot_avator): with st.chat_message('assistant', avatar=robot_avator):
messages = [ messages = [{
{ 'role':
"role": m["role"], m['role'],
"content": m["merged_content"] if "merged_content" in m else m["content"], 'content':
} m['merged_content'] if 'merged_content' in m else m['content'],
for m in st.session_state.messages } for m in st.session_state.messages]
]
# Log messages to the terminal # Log messages to the terminal
for m in messages: for m in messages:
logging.info(f"\n\n*** [{m['role']}] ***\n\n\t{m['content']}\n\n") logging.info(
f"\n\n*** [{m['role']}] ***\n\n\t{m['content']}\n\n")
stream = generate(client, messages, generation_config) stream = generate(client, messages, generation_config)
response = st.write_stream(stream) response = st.write_stream(stream)
st.session_state.messages.append({"role": "assistant", "content": response, "avatar": robot_avator}) st.session_state.messages.append({
'role': 'assistant',
'content': response,
'avatar': robot_avator
})
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run Streamlit app with OpenAI client.") if __name__ == '__main__':
parser.add_argument("--base_url", type=str, required=True, help="Base URL for the OpenAI client") parser = argparse.ArgumentParser(
description='Run Streamlit app with OpenAI client.')
parser.add_argument('--base_url',
type=str,
required=True,
help='Base URL for the OpenAI client')
args = parser.parse_args() args = parser.parse_args()
main(args.base_url) main(args.base_url)

17
model_cards/internlm2.5_7b.md
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@ -42,16 +42,15 @@ We have evaluated InternLM2.5 on several important benchmarks using the open-sou
### Chat Model ### Chat Model
| Benchmark | InternLM2-Chat-7B | LLaMA-3-8B-Instruct | Yi-1.5-9B-Chat | GLM-4-9B-Chat | Qwen2-7B-Instruct | Gemma2-9B-IT | InternLM2.5-7B-Chat | Llama-3-70B-Instruct | | Benchmark | InternLM2-Chat-7B | LLaMA-3-8B-Instruct | Yi-1.5-9B-Chat | GLM-4-9B-Chat | Qwen2-7B-Instruct | Gemma2-9B-IT | InternLM2.5-7B-Chat | Llama-3-70B-Instruct |
| ----------------- | ----------------- | ------------------- | -------------- | ------------- | ----------------- | ------------ | ------------------- |------------------- | | ----------------- | ----------------- | ------------------- | -------------- | ------------- | ----------------- | ------------ | ------------------- | -------------------- |
| MMLU(5-shot) | 62.3 | 68.4 | 71.0 | 71.4 | 70.8 | 70.9 | 72.8 | 80.5 | | MMLU(5-shot) | 62.3 | 68.4 | 71.0 | 71.4 | 70.8 | 70.9 | 72.8 | 80.5 |
| CMMLU(5-shot) | 62.4 | 53.3 | 74.5 | 74.5 | 80.9 | 60.3 | 78.0 | 70.1 | | CMMLU(5-shot) | 62.4 | 53.3 | 74.5 | 74.5 | 80.9 | 60.3 | 78.0 | 70.1 |
| BBH(3-shot CoT) | 59.0 | 54.4 | 69.6 | 69.6 | 65.0 | 68.2\* | 71.6 | 80.5 | | BBH(3-shot CoT) | 59.0 | 54.4 | 69.6 | 69.6 | 65.0 | 68.2\* | 71.6 | 80.5 |
| MATH(0-shot CoT) | 27.6 | 27.9 | 51.1 | 51.1 | 48.6 | 46.9 | 60.1 | 47.1 | | MATH(0-shot CoT) | 27.6 | 27.9 | 51.1 | 51.1 | 48.6 | 46.9 | 60.1 | 47.1 |
| GSM8K(0-shot CoT) | 72.5 | 72.9 | 80.1 | 85.3 | 82.9 | 88.9 | 86.0 | 92.8 | | GSM8K(0-shot CoT) | 72.5 | 72.9 | 80.1 | 85.3 | 82.9 | 88.9 | 86.0 | 92.8 |
| GPQA(0-shot) | 29.8 | 26.1 | 37.9 | 36.9 | 38.4 | 33.8 | 38.4 | 38.9 | | GPQA(0-shot) | 29.8 | 26.1 | 37.9 | 36.9 | 38.4 | 33.8 | 38.4 | 38.9 |
- We use `ppl` for the MCQ evaluation on base model. - We use `ppl` for the MCQ evaluation on base model.
- The evaluation results were obtained from [OpenCompass](https://github.com/open-compass/opencompass) , and evaluation configuration can be found in the configuration files provided by [OpenCompass](https://github.com/open-compass/opencompass). - The evaluation results were obtained from [OpenCompass](https://github.com/open-compass/opencompass) , and evaluation configuration can be found in the configuration files provided by [OpenCompass](https://github.com/open-compass/opencompass).
- The evaluation data may have numerical differences due to the version iteration of [OpenCompass](https://github.com/open-compass/opencompass), so please refer to the latest evaluation results of [OpenCompass](https://github.com/open-compass/opencompass). - The evaluation data may have numerical differences due to the version iteration of [OpenCompass](https://github.com/open-compass/opencompass), so please refer to the latest evaluation results of [OpenCompass](https://github.com/open-compass/opencompass).
- \* means the result is copied from the original paper. - \* means the result is copied from the original paper.

33
model_cards/internlm2_1.8b.md
View File

@ -5,7 +5,7 @@
InternLM2-1.8B is the 1.8 billion parameter version of the second generation InternLM series. In order to facilitate user use and research, InternLM2-1.8B has three versions of open-source models. They are: InternLM2-1.8B is the 1.8 billion parameter version of the second generation InternLM series. In order to facilitate user use and research, InternLM2-1.8B has three versions of open-source models. They are:
- InternLM2-1.8B: Foundation models with high quality and high adaptation flexibility, which serve as a good starting point for downstream deep adaptations. - InternLM2-1.8B: Foundation models with high quality and high adaptation flexibility, which serve as a good starting point for downstream deep adaptations.
- InternLM2-Chat-1.8B-SFT: Chat model after supervised fine-tuning (SFT) on InternLM2-1.8B. - InternLM2-Chat-1.8B-SFT: Chat model after supervised fine-tuning (SFT) on InternLM2-1.8B.
- InternLM2-Chat-1.8B: Further aligned on top of InternLM2-Chat-1.8B-SFT through online RLHF. InternLM2-Chat-1.8B exhibits better instruction following, chat experience, and function calling, which is recommended for downstream applications. - InternLM2-Chat-1.8B: Further aligned on top of InternLM2-Chat-1.8B-SFT through online RLHF. InternLM2-Chat-1.8B exhibits better instruction following, chat experience, and function calling, which is recommended for downstream applications.
The base model of InternLM2 has the following technical features: The base model of InternLM2 has the following technical features:
@ -15,26 +15,25 @@ The base model of InternLM2 has the following technical features:
## Model Zoo ## Model Zoo
| Model | Transformers(HF) | ModelScope(HF) | OpenXLab(HF) | OpenXLab(Origin) | Release Date | | Model | Transformers(HF) | ModelScope(HF) | OpenXLab(HF) | OpenXLab(Origin) | Release Date |
| -------------------------- | ------------------------------------------ | ---------------------------------------- | -------------------------------------- | ------------------------------------------ | ------------ | | --------------------------- | ----------------------------------------- | ---------------------------------------- | -------------------------------------- | ------------------------------------------ | ------------ |
| **InternLM2-1.8B** | [🤗internlm2-1.8b](https://huggingface.co/internlm/internlm2-1_8b) | [<img src="./assets/modelscope_logo.png" width="20px" /> internlm2-1.8b](https://www.modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-1_8b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-base-1.8b) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-base-1.8b-original) | 2024-01-31 | | **InternLM2-1.8B** | [🤗internlm2-1.8b](https://huggingface.co/internlm/internlm2-1_8b) | [<img src="./assets/modelscope_logo.png" width="20px" /> internlm2-1.8b](https://www.modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-1_8b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-base-1.8b) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-base-1.8b-original) | 2024-01-31 |
| **InternLM2-Chat-1.8B-SFT** | [🤗internlm2-chat-1.8b-sft](https://huggingface.co/internlm/internlm2-chat-1_8b-sft) | [<img src="./assets/modelscope_logo.png" width="20px" /> internlm2-chat-1.8b-sft](https://www.modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-1_8b-sft/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b-sft) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b-sft-original) | 2024-01-31 | | **InternLM2-Chat-1.8B-SFT** | [🤗internlm2-chat-1.8b-sft](https://huggingface.co/internlm/internlm2-chat-1_8b-sft) | [<img src="./assets/modelscope_logo.png" width="20px" /> internlm2-chat-1.8b-sft](https://www.modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-1_8b-sft/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b-sft) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b-sft-original) | 2024-01-31 |
| **InternLM2-Chat-1.8B** | [🤗internlm2-chat-1.8b](https://huggingface.co/internlm/internlm2-chat-1_8b) | [<img src="./assets/modelscope_logo.png" width="20px" /> internlm2-chat-1.8b](https://www.modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-1_8b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b-original) | 2024-02-19 | | **InternLM2-Chat-1.8B** | [🤗internlm2-chat-1.8b](https://huggingface.co/internlm/internlm2-chat-1_8b) | [<img src="./assets/modelscope_logo.png" width="20px" /> internlm2-chat-1.8b](https://www.modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-1_8b/summary) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b) | [![Open in OpenXLab](https://cdn-static.openxlab.org.cn/header/openxlab_models.svg)](https://openxlab.org.cn/models/detail/OpenLMLab/internlm2-chat-1.8b-original) | 2024-02-19 |
## Performance Evaluation ## Performance Evaluation
We have evaluated InternLM2 on several important benchmarks using the open-source evaluation tool [OpenCompass](https://github.com/open-compass/opencompass). Some of the evaluation results are shown in the table below. You are welcome to visit the [OpenCompass Leaderboard](https://opencompass.org.cn/rank) for more evaluation results. We have evaluated InternLM2 on several important benchmarks using the open-source evaluation tool [OpenCompass](https://github.com/open-compass/opencompass). Some of the evaluation results are shown in the table below. You are welcome to visit the [OpenCompass Leaderboard](https://opencompass.org.cn/rank) for more evaluation results.
| Dataset\Models | InternLM2-1.8B | InternLM2-Chat-1.8B-SFT | InternLM2-Chat-1.8B | InternLM2-7B | InternLM2-Chat-7B | | Dataset\\Models | InternLM2-1.8B | InternLM2-Chat-1.8B-SFT | InternLM2-Chat-1.8B | InternLM2-7B | InternLM2-Chat-7B |
| :---: | :---: | :---: | :---: | :---: | :---: | | :-------------: | :------------: | :---------------------: | :-----------------: | :----------: | :---------------: |
| MMLU | 46.9 | 47.1 | 44.1 | 65.8 | 63.7 | | MMLU | 46.9 | 47.1 | 44.1 | 65.8 | 63.7 |
| AGIEval | 33.4 | 38.8 | 34.6 | 49.9 | 47.2 | | AGIEval | 33.4 | 38.8 | 34.6 | 49.9 | 47.2 |
| BBH | 37.5 | 35.2 | 34.3 | 65.0 | 61.2 | | BBH | 37.5 | 35.2 | 34.3 | 65.0 | 61.2 |
| GSM8K | 31.2 | 39.7 | 34.3 | 70.8 | 70.7 | | GSM8K | 31.2 | 39.7 | 34.3 | 70.8 | 70.7 |
| MATH | 5.6 | 11.8 | 10.7 | 20.2 | 23.0 | | MATH | 5.6 | 11.8 | 10.7 | 20.2 | 23.0 |
| HumanEval | 25.0 | 32.9 | 29.3 | 43.3 | 59.8 | | HumanEval | 25.0 | 32.9 | 29.3 | 43.3 | 59.8 |
| MBPP(Sanitized) | 22.2 | 23.2 | 27.0 | 51.8 | 51.4 | | MBPP(Sanitized) | 22.2 | 23.2 | 27.0 | 51.8 | 51.4 |
- The evaluation results were obtained from [OpenCompass](https://github.com/open-compass/opencompass) , and evaluation configuration can be found in the configuration files provided by [OpenCompass](https://github.com/open-compass/opencompass).
- The evaluation results were obtained from [OpenCompass](https://github.com/open-compass/opencompass) , and evaluation configuration can be found in the configuration files provided by [OpenCompass](https://github.com/open-compass/opencompass).
- The evaluation data may have numerical differences due to the version iteration of [OpenCompass](https://github.com/open-compass/opencompass), so please refer to the latest evaluation results of [OpenCompass](https://github.com/open-compass/opencompass). - The evaluation data may have numerical differences due to the version iteration of [OpenCompass](https://github.com/open-compass/opencompass), so please refer to the latest evaluation results of [OpenCompass](https://github.com/open-compass/opencompass).

14
tests/test_hf_model.py
View File

@ -21,10 +21,10 @@ class TestChat:
@pytest.mark.parametrize( @pytest.mark.parametrize(
'model_name', 'model_name',
[ [
'internlm/internlm2_5-7b-chat', 'internlm/internlm2_5-7b-chat', 'internlm/internlm2-chat-7b',
'internlm/internlm2-chat-7b', 'internlm/internlm2-chat-7b-sft', 'internlm/internlm2-chat-7b-sft', 'internlm/internlm2-chat-20b',
'internlm/internlm2-chat-20b', 'internlm/internlm2-chat-20b-sft', 'internlm/internlm2-chat-20b-sft', 'internlm/internlm2-chat-1_8b',
'internlm/internlm2-chat-1_8b', 'internlm/internlm2-chat-1_8b-sft' 'internlm/internlm2-chat-1_8b-sft'
], ],
) )
@pytest.mark.parametrize( @pytest.mark.parametrize(
@ -128,8 +128,10 @@ class TestMath:
@pytest.mark.parametrize( @pytest.mark.parametrize(
'model_name', 'model_name',
['internlm/internlm2-math-7b', 'internlm/internlm2-math-base-7b', [
'internlm/internlm2-math-plus-1_8b', 'internlm/internlm2-math-plus-7b' 'internlm/internlm2-math-7b', 'internlm/internlm2-math-base-7b',
'internlm/internlm2-math-plus-1_8b',
'internlm/internlm2-math-plus-7b'
], ],
) )
@pytest.mark.parametrize( @pytest.mark.parametrize(

8
tools/convert2llama.py
View File

@ -59,8 +59,8 @@ def convert(src, tgt):
assert not config.bias, 'Cannot convert InternLM Model with bias to LLaMA.' assert not config.bias, 'Cannot convert InternLM Model with bias to LLaMA.'
head_dim = config.hidden_size // config.num_attention_heads head_dim = config.hidden_size // config.num_attention_heads
num_key_value_groups = config.num_attention_heads \ num_key_value_groups = \
// config.num_key_value_heads config.num_attention_heads // config.num_key_value_heads
# load index json file # load index json file
index_file = 'pytorch_model.bin.index.json' index_file = 'pytorch_model.bin.index.json'
@ -140,7 +140,9 @@ def convert(src, tgt):
print(f'Saving to {os.path.join(tgt, filename)}...', flush=True) print(f'Saving to {os.path.join(tgt, filename)}...', flush=True)
if filename.endswith('.safetensors'): if filename.endswith('.safetensors'):
from safetensors.torch import save_file from safetensors.torch import save_file
save_file(llama_states, os.path.join(tgt, filename), metadata={"format": "pt"}) save_file(llama_states,
os.path.join(tgt, filename),
metadata={'format': 'pt'})
else: else:
torch.save(llama_states, os.path.join(tgt, filename)) torch.save(llama_states, os.path.join(tgt, filename))
del states del states