README.md

---
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])