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--- |
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license: apache-2.0 |
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language: |
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- fr |
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- it |
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- de |
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- es |
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- en |
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- zh |
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inference: false |
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--- |
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# Model Card for Mobius-12B-base-m1 |
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The Mobius-12B-base-m1 Large Language Model (LLM) is a pretrained model based on RWKV v5 arch. We use 0.01B tokens to post train this model for alignment the benchmark. |
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## Warning |
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This repo contains weights that are not compatible with Hugging Face [transformers](https://github.com/huggingface/transformers) library yet. But you can try this[PR](https://github.com/huggingface/transformers/pull/26963) as well. |
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[RWKV runner]() or [AI00 server]() also work. |
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## Instruction|Chat format |
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This format must be strictly respected, otherwise the model will generate sub-optimal outputs. |
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The template used to build a prompt for the Instruct model is defined as follows: |
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``` |
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User: {Instruction|prompt}\n\nAssistant: |
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``` |
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## Run the model |
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Need to install this [PR](https://github.com/huggingface/transformers/pull/26963) |
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pip install -e git://github.com/BBuf/transformers.git |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("TimeMobius/Mobius-12B-base-m1", torch_dtype=torch.float16).to(0) |
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tokenizer = AutoTokenizer.from_pretrained("TimeMobius/Mobius-12B-base-m1", trust_remote_code=True) |
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text = "x" |
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prompt = f'Question: {text.strip()}\n\nAnswer:' |
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inputs = tokenizer(prompt, return_tensors="pt").to(0) |
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output = model.generate(inputs["input_ids"], max_new_tokens=40) |
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print(tokenizer.decode(output[0].tolist(), skip_special_tokens=True)) |
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``` |
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## Limitations |
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The Mobius base m1 is the base model can be easily fine-tuned to achieve compelling performance. |
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### Benchmark |
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| Mobius-12B-base-m1 | | |
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| lambda ppl | 3.41 | |
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| lambda | 0.72 | |
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| piqa | 0.78 | |
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| hellaswag 10 shots | 0.72 | |
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| winogrande | 0.68 | |
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| arc_challenge 25shots | 0.47 | |
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| arc_easy | 0.73 | |
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| openbookqa | 0.40 | |
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| sciq | 0.93 | |
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# @TimeMobius |
