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---
license: mit
language:
- en
base_model:
- 01-ai/Yi-1.5-9B-Chat
- Qwen/Qwen2-7B-Instruct
library_name: transformers
tags:
- mergekit
- merge
- conversational
- chicka
- chinese
- china
---
# ChinaLM by Chickaboo AI
Welcome to ChinaLM, a Chinese LLM merge made Chickaboo AI. ChinaLM is designed to deliver a high-quality conversational experience in Chinese.
## Table of Contents
- **Model Details**
- **Benchmarks**
- **Usage**
## Model Details
ChinaLM is a merge of the [Qwen2-7B-Instruct](https://huggingface.co/Qwen/Qwen2-7B-Instruct) model and [Yi-1.5-9B-Chat](https://huggingface.co/01-ai/Yi-1.5-9B-Chat) made with Mergekit using this config file:
``` json
slices:
- sources:
- model: 01-ai/Yi-1.5-9B-Chat
layer_range: [0, 20]
- sources:
- model: Qwen/Qwen2-7B-Instruct
layer_range: [0, 20]
merge_method: passthrough
dtype: bfloat16
```
## Open Chinese LLM Leaderboard
Coming soon
| **Benchmark** | **ChinaLM-9B** | **ChinaLM-13B (Unrealesed)** | **Mistral-7B-Instruct-v0.2** | **Meta-Llama-3-8B** | **Yi-1.5-9B-Chat** | **Qwen2-7B-Instruct** |
|------------------|-----------------|------------------|------------------------------|---------------------|------------|--------------|
| **Average** | **--** | -- | -- | -- | -- | -- |
| **ARC** | **--** | -- | -- | -- | -- | -- |
| **Hellaswag** | **--** | -- | -- | -- | -- | -- |
| **MMLU** | **--** | -- | -- | -- | -- | -- |
| **TruthfulQA** | **--** | -- | -- | -- | -- | -- |
| **Winogrande** | **--** | -- |-- | -- | -- | -- |
| **GSM8K** | **--** | -- | -- | -- | -- | -- |
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained("Chickaboo/ChinaLM-9B")
tokenizer = AutoTokenizer.from_pretrained("Chickaboo/ChinaLM-9B")
messages = [
{"role": "user", "content": "What is your favourite condiment?"},
{"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
{"role": "user", "content": "Do you have mayonnaise recipes?"}
]
encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
model_inputs = encodeds.to(device)
model.to(device)
generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
|