91 lines
3.2 KiB
Markdown
91 lines
3.2 KiB
Markdown
---
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base_model:
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- google/gemma-2-2b-it
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- VAGOsolutions/SauerkrautLM-gemma-2-2b-it
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- stvlynn/Gemma-2-2b-Chinese-it
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library_name: transformers
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tags:
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- mergekit
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- merge
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license: apache-2.0
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---
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# Gemma2-2B-it Merged Fine-Tuned Models for Chinese & German understanding
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Lightweight language model based on Gemma2 2B created by merging multiple fine tuned Gemma2-2B-IT versions to test multilingual conversation capabilities in specialized low parameter language models.
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## 🤏 Models Merged
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) as a base.
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The following models were included in the merge:
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* [VAGOsolutions/SauerkrautLM-gemma-2-2b-it](https://huggingface.co/VAGOsolutions/SauerkrautLM-gemma-2-2b-it)
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* [stvlynn/Gemma-2-2b-Chinese-it](https://huggingface.co/stvlynn/Gemma-2-2b-Chinese-it)
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## 🧩 Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: google/gemma-2-2b-it
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- model: VAGOsolutions/SauerkrautLM-gemma-2-2b-it
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- model: stvlynn/Gemma-2-2b-Chinese-it
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merge_method: model_stock
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base_model: google/gemma-2-2b-it
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dtype: bfloat16
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```
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### 💻 Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import torch
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# Load the tokenizer and model
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tokenizer = AutoTokenizer.from_pretrained("AdamLucek/gemma2-2b-it-chinese-german")
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model = AutoModelForCausalLM.from_pretrained(
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"AdamLucek/gemma2-2b-it-chinese-german",
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device_map="cuda",
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torch_dtype=torch.bfloat16
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)
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# Prepare the input text
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input_text = "请解释一下量子力学中的叠加原理，并举例说明该原理在实际应用中的重要性和挑战。"
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input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
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# Generate the output
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outputs = model.generate(
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**input_ids,
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max_new_tokens=256,
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pad_token_id=tokenizer.eos_token_id
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)
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# Decode and print the generated text
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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**Ouptut**
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```
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## 量子叠加原理：
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**叠加原理**是量子力学中一个重要的概念，它描述了量子系统在测量之前处于多个状态的可能性。
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**简单来说，就是说，一个量子系统可以同时处于多个状态，直到我们测量它时，才会坍缩到一个确定的状态。**
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**具体来说，我们可以用以下方式理解叠加原理：**
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* **量子系统：** 比如一个原子，它可以处于多个能量状态。
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* **叠加态：** 表示量子系统同时处于多个状态的概率分布。
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* **测量：** 当我们测量量子系统时，它会坍缩到一个确定的状态。
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* **坍缩：** 测量过程会改变量子系统的状态，使其坍缩到一个确定的状态。
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**举例说明：**
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想象一下一个量子系统，它可以处于两个状态：上或下。这个系统可以被描述为一个叠加态，表示它同时处于上和下两个状态的概率分布。
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**如果我们没有测量这个系统，那么它就处于叠加态，同时处于上和下两个状态。**
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**但是，当我们测量这个系统时
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``` |