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  license: apache-2.0
 
 
 
 
 
 
 
 
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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
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+
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+
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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]() as well.
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+ [RWKV runner]() or [AI00 server]() also work.
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+
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+ ## Instruction|Chat format
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+
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+ This format must be strictly respected, otherwise the model will generate sub-optimal outputs.
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+
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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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+
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+ ## Run the model
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+
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+ ```python
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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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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+
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+ text = "x"
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+ prompt = f'Question: {text.strip()}\n\nAnswer:'
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+
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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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+
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+ ## Limitations
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+
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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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+
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+ ### Benchmark
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+
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+ | Mobius-12B-base-m1 | |
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+ |--------------------|----------|
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+ | ppl | 3.41 |
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+ | piqa | 0.78 |
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+ | hellaswag | 0.71 |
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+ | winogrande | 0.68 |
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+ | arc_challenge | 0.42 |
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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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+
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+
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+ # @TimeMobius