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 model and Yi-1.5-9B-Chat made with Mergekit using this config file:
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
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])
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