github
/
InternLM
mirror of https://github.com/InternLM/InternLM
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

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
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

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
if not has_default_max_length:
logger.warn( # pylint: disable=W4902
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'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. '
'Please refer to the documentation for more information. '
'(https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)',
UserWarning,
@ -199,8 +199,8 @@ def generate_interactive(
if input_ids_seq_length >= generation_config.max_length:
input_ids_string = 'input_ids'
logger.warning(
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'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'
' increasing `max_new_tokens`.')
# 2. Set generation parameters if not already defined
@ -510,7 +510,7 @@ def main():
interface.clear_history()
f.flush()
print(f"{args.model}: Accuracy - {sum(scores) / len(scores)}")
print(f'{args.model}: Accuracy - {sum(scores) / len(scores)}')
torch.cuda.empty_cache()

13
chat/web_demo.py
View File

@ -77,7 +77,8 @@ def generate_interactive(
'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:
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. "
'This behaviour is deprecated and will be removed from the \
config in v5 of Transformers -- we'
@ -102,7 +103,7 @@ def generate_interactive(
if input_ids_seq_length >= generation_config.max_length:
input_ids_string = 'input_ids'
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}. "
'This can lead to unexpected behavior. You should consider'
" increasing 'max_new_tokens'.")
@ -180,9 +181,9 @@ def on_btn_click():
@st.cache_resource
def load_model():
model = (AutoModelForCausalLM.from_pretrained('internlm/internlm2_5-7b-chat',
trust_remote_code=True).to(
torch.bfloat16).cuda())
model = (AutoModelForCausalLM.from_pretrained(
'internlm/internlm2_5-7b-chat',
trust_remote_code=True).to(torch.bfloat16).cuda())
tokenizer = AutoTokenizer.from_pretrained('internlm/internlm2_5-7b-chat',
trust_remote_code=True)
return model, tokenizer
@ -216,7 +217,7 @@ def combine_history(prompt):
meta_instruction = ('You are InternLM (书生·浦语), a helpful, honest, '
'and harmless AI assistant developed by Shanghai '
'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:
cur_content = message['content']
if message['role'] == 'user':

3
long_context/README.md
View File

@ -35,6 +35,7 @@ Currently, we support PDF, TXT, and Markdown files, with more file types to be s
### Installation
To get started, install the required packages:
```bash
pip install "fairy-doc[cpu]"
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
## 🔜 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!

3
long_context/README_zh-CN.md
View File

@ -32,6 +32,7 @@
### 安装
开始前，请安装所需的依赖：
```bash
pip install "fairy-doc[cpu]"
pip install streamlit
@ -76,4 +77,4 @@ https://github.com/libowen2121/InternLM/assets/19970308/1d7f9b87-d458-4f24-9f7a-
## 🔜 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
View File

@ -1,12 +1,15 @@
import argparse
import logging
from dataclasses import dataclass
import streamlit as st
from openai import OpenAI
from magic_doc.docconv import DocConverter
import argparse
from openai import OpenAI
# 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
class GenerationConfig:
@ -16,13 +19,14 @@ class GenerationConfig:
temperature: float = 0.1
repetition_penalty: float = 1.005
def generate(
client,
messages,
generation_config,
):
stream = client.chat.completions.create(
model=st.session_state["model_name"],
model=st.session_state['model_name'],
messages=messages,
stream=True,
temperature=generation_config.temperature,
@ -32,113 +36,140 @@ def generate(
)
return stream
def prepare_generation_config():
with st.sidebar:
max_tokens = st.number_input("Max Tokens", min_value=100, max_value=4096, value=1024)
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)
max_tokens = st.number_input('Max Tokens',
min_value=100,
max_value=4096,
value=1024)
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(
max_tokens=max_tokens,
top_p=top_p,
temperature=temperature,
repetition_penalty=repetition_penalty
)
generation_config = GenerationConfig(max_tokens=max_tokens,
top_p=top_p,
temperature=temperature,
repetition_penalty=repetition_penalty)
return generation_config
def on_btn_click():
del st.session_state.messages
st.session_state.file_content_found = False
st.session_state.file_content_used = False
user_avator = 'assets/user.png'
robot_avator = 'assets/robot.png'
st.title('InternLM2.5 File Chat 📝')
def main(base_url):
# Initialize the client for the model
client = OpenAI(
base_url=base_url,
timeout=12000
)
client = OpenAI(base_url=base_url, timeout=12000)
# Get the model 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
generation_config = prepare_generation_config()
# Initialize session state
if "messages" not in st.session_state:
if 'messages' not in st.session_state:
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_used = False
st.session_state.file_name = ""
st.session_state.file_name = ''
# Handle file upload
if not st.session_state.file_content_found:
uploaded_file = st.file_uploader("Upload an article", type=("txt", "md", "pdf"))
file_content = ""
uploaded_file = st.file_uploader('Upload an article',
type=('txt', 'md', 'pdf'))
file_content = ''
if uploaded_file is not None:
if uploaded_file.type == "application/pdf":
with open("uploaded_file.pdf", "wb") as f:
if uploaded_file.type == 'application/pdf':
with open('uploaded_file.pdf', 'wb') as f:
f.write(uploaded_file.getbuffer())
converter = DocConverter(s3_config=None)
file_content, time_cost = converter.convert("uploaded_file.pdf", conv_timeout=300)
st.session_state.file_content_found = True # 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_name = uploaded_file.name # Store the file name in session state
file_content, time_cost = converter.convert(
'uploaded_file.pdf', conv_timeout=300)
# Reset flag when a new file is uploaded
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:
file_content = uploaded_file.read().decode("utf-8")
st.session_state.file_content_found = True # 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_name = uploaded_file.name # Store the file name in session state
file_content = uploaded_file.read().decode('utf-8')
# Reset flag when a new file is uploaded
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
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
for message in st.session_state.messages:
with st.chat_message(message["role"], avatar=message.get("avatar")):
st.markdown(message["content"])
with st.chat_message(message['role'], avatar=message.get('avatar')):
st.markdown(message['content'])
# Handle user input and response generation
if prompt := st.chat_input("What's up?"):
turn = {"role": "user", "content": prompt, "avatar": user_avator}
if st.session_state.file_content_found and not st.session_state.file_content_used:
turn = {'role': 'user', 'content': prompt, 'avatar': user_avator}
if (st.session_state.file_content_found
and not st.session_state.file_content_used):
assert st.session_state.file_content is not None
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
turn["merged_content"] = merged_prompt
merged_prompt = f'{st.session_state.file_content}\n\n{prompt}'
# Set flag to indicate file content has been used
st.session_state.file_content_used = True
turn['merged_content'] = merged_prompt
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)
with st.chat_message("assistant", avatar=robot_avator):
messages = [
{
"role": m["role"],
"content": m["merged_content"] if "merged_content" in m else m["content"],
}
for m in st.session_state.messages
]
with st.chat_message('assistant', avatar=robot_avator):
messages = [{
'role':
m['role'],
'content':
m['merged_content'] if 'merged_content' in m else m['content'],
} for m in st.session_state.messages]
# Log messages to the terminal
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)
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.")
parser.add_argument("--base_url", type=str, required=True, help="Base URL for the OpenAI client")
if __name__ == '__main__':
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()
main(args.base_url)

17
model_cards/internlm2.5_7b.md
View File

@ -42,16 +42,15 @@ We have evaluated InternLM2.5 on several important benchmarks using the open-sou
### 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 |
| ----------------- | ----------------- | ------------------- | -------------- | ------------- | ----------------- | ------------ | ------------------- |------------------- |
| 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 |
| 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 |
| 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 |
| ----------------- | ----------------- | ------------------- | -------------- | ------------- | ----------------- | ------------ | ------------------- | -------------------- |
| 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 |
| 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 |
| 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 |
- 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 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: 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.
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 | 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-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 |
| 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-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 |
## 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.
| 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 |
| AGIEval | 33.4 | 38.8 | 34.6 | 49.9 | 47.2 |
| BBH | 37.5 | 35.2 | 34.3 | 65.0 | 61.2 |
| GSM8K | 31.2 | 39.7 | 34.3 | 70.8 | 70.7 |
| MATH | 5.6 | 11.8 | 10.7 | 20.2 | 23.0 |
| HumanEval | 25.0 | 32.9 | 29.3 | 43.3 | 59.8 |
| MBPP(Sanitized) | 22.2 | 23.2 | 27.0 | 51.8 | 51.4 |
| 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 |
| AGIEval | 33.4 | 38.8 | 34.6 | 49.9 | 47.2 |
| BBH | 37.5 | 35.2 | 34.3 | 65.0 | 61.2 |
| GSM8K | 31.2 | 39.7 | 34.3 | 70.8 | 70.7 |
| MATH | 5.6 | 11.8 | 10.7 | 20.2 | 23.0 |
| HumanEval | 25.0 | 32.9 | 29.3 | 43.3 | 59.8 |
| 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).

14
tests/test_hf_model.py
View File

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

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.'
head_dim = config.hidden_size // config.num_attention_heads
num_key_value_groups = config.num_attention_heads \
// config.num_key_value_heads
num_key_value_groups = \
config.num_attention_heads // config.num_key_value_heads
# load index json file
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)
if filename.endswith('.safetensors'):
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:
torch.save(llama_states, os.path.join(tgt, filename))
del states