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--- |
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base_model: |
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- crestf411/nemo-sunfall-v0.6.1 |
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- unsloth/Mistral-Nemo-Instruct-2407 |
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- RozGrov/NemoDori-v0.1-12B-MS |
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tags: |
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- merge |
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- mergekit |
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- lazymergekit |
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- crestf411/nemo-sunfall-v0.6.1 |
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- unsloth/Mistral-Nemo-Instruct-2407 |
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- RozGrov/NemoDori-v0.1-12B-MS |
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library_name: transformers |
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pipeline_tag: text-generation |
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--- |
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# NemoDori-v0.2-12B-MN-BT |
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NemoDori-v0.2-12B-MN-BT is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [crestf411/nemo-sunfall-v0.6.1](https://huggingface.co/crestf411/nemo-sunfall-v0.6.1) |
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* [unsloth/Mistral-Nemo-Instruct-2407](https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407) |
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* [RozGrov/NemoDori-v0.1-12B-MS](https://huggingface.co/RozGrov/NemoDori-v0.1-12B-MS) |
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Experimental 'sequel' of NemoDori ([v0.1](https://huggingface.co/RozGrov/NemoDori-v0.1-12B-MS)), an ERP-focused model, just for testing purpose. I still don't know what I've done... |
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My short experience using this: |
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- When you instruct it to roleplay, it generates short chat-like response and to-the-point. (sometimes really short) |
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- It advances the story slowly (even slower than v0.1 i think), responding to the last roleplay message quite nicely. |
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- Creativity is *maybe* good(?). |
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- Can follow instructions quite well (even on depth-0). |
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<u>Update 1</u>: |
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<br> |
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I was playing around with [**Talemate**](https://github.com/vegu-ai/talemate) and... this model is pretty good. It was able to follow Talemate's instructions well, which Talemate then parsed it into it's format. |
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<br> |
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It can become all of Talemate agents (mostly maybe). So far i've tested, it is best when having a Conversation, capable of generating character's attributes (Creator) and the world state. When it's used for narrating (Narrator), sometimes it speaks for you and includes the Talemate's conversation (for this one, maybe I just didn't have a good instruction for it). |
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<br><br> |
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Those are my experiences using default presets from Talemate. I did tweaked them and played a bit near the end, and it does affect the results in a good way. |
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<br> |
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I'll try to test it again some more later. |
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## 🧩 Configuration |
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```yaml |
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models: |
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- model: crestf411/nemo-sunfall-v0.6.1 |
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parameters: |
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weight: 0.5 |
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- model: unsloth/Mistral-Nemo-Instruct-2407 |
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parameters: |
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weight: 0.3 |
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- model: RozGrov/NemoDori-v0.1-12B-MS |
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parameters: |
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weight: 1.0 |
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merge_method: breadcrumbs_ties |
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base_model: RozGrov/NemoDori-v0.1-12B-MS |
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parameters: |
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density: 0.95 |
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gamma: 0.01 |
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dtype: float16 |
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``` |
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## 💻 Usage |
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```python |
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!pip install -qU transformers accelerate |
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "RozGrov/NemoDori-v0.2-12B-MN-BT" |
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messages = [{"role": "user", "content": "What is a large language model?"}] |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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torch_dtype=torch.float16, |
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device_map="auto", |
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) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
