Model Card for Mobius-12B-base-m1
The Mobius-12B-base-m1 Large Language Model (LLM) is a pretrained model based on RWKV v5 arch. We utilized 0.01 billion tokens to conduct post-training on this model for alignment benchmarks, excluding the utilization of DPO and SFT. The process took approximately 10 hours, employing 4 * a800.
Warning
This repo contains weights that are not compatible with Hugging Face transformers library yet. But you can try thisPR as well. RWKV runner or AI00 server also work.
Instruction|Chat format
This format must be strictly respected, otherwise the model will generate sub-optimal outputs.
The template used to build a prompt for the Instruct model is defined as follows:
User: {Instruction|prompt}\n\nAssistant:
Run the model
need to convert checkpoint to HF format
Need to install this PR pip install -e git://github.com/BBuf/transformers.git
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("TimeMobius/Mobius-12B-base-m1", torch_dtype=torch.float16).to(0)
tokenizer = AutoTokenizer.from_pretrained("TimeMobius/Mobius-12B-base-m1", trust_remote_code=True)
text = "x"
prompt = f'Question: {text.strip()}\n\nAnswer:'
inputs = tokenizer(prompt, return_tensors="pt").to(0)
output = model.generate(inputs["input_ids"], max_new_tokens=40)
print(tokenizer.decode(output[0].tolist(), skip_special_tokens=True))
Limitations
The Mobius base m1 is the base model can be easily fine-tuned to achieve compelling performance. if you wanna better benchmark results use DPO and SFT ,details in readme
Benchmark
| Mobius-12B-base-m1 | |
|---|---|
| lambda ppl | 3.41 |
| lambda | 0.72 |
| piqa | 0.78 |
| hellaswag 10 shots | 0.72 |
| winogrande | 0.68 |
| arc_challenge 25shots | 0.47 |
| arc_easy | 0.73 |
| openbookqa | 0.40 |
| sciq | 0.93 |