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--- |
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tags: |
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- merge |
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- mergekit |
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- lazymergekit |
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- mistral |
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- ResplendentAI/Datura_7B |
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- Epiculous/Mika-7B |
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base_model: |
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- ResplendentAI/Datura_7B |
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- Epiculous/Mika-7B |
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language: |
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- en |
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library_name: transformers |
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license: apache-2.0 |
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--- |
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<div style="margin-bottom: -40px; margin-top: -30px;"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/65ad2502043d53781aad2ee4/ZrffOEBz2rxwAwdgzOkhd.png" alt="favicon" style="display: inline-block; vertical-align: middle; width: 25px; height: 25px; margin-right: 10px;"> |
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<span style="display: inline-block; vertical-align: middle; font-weight: 600; font-size: 20px;">Foxglove_7B</span> |
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</div> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/65ad2502043d53781aad2ee4/FUH__CjalqBRPiSaqZfO6.png" alt="image" width="540" height="540" style="margin-bottom: -10px;"> |
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Foxglove_7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [ResplendentAI/Datura_7B](https://huggingface.co/ResplendentAI/Datura_7B) |
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* [Epiculous/Mika-7B](https://huggingface.co/Epiculous/Mika-7B) |
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## 🧩 Configuration |
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```yaml |
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slices: |
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- sources: |
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- model: ResplendentAI/Datura_7B |
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layer_range: [0, 32] |
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- model: Epiculous/Mika-7B |
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layer_range: [0, 32] |
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merge_method: slerp |
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base_model: ResplendentAI/Datura_7B |
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parameters: |
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t: |
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- filter: self_attn |
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value: [0, 0.7, 0.4, 0.6, 1] |
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- filter: mlp |
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value: [0.8, 0.5, 0.7, 0.3, 0] |
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- value: 0.6 |
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dtype: bfloat16 |
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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 = "aridoverrun/Foxglove_7B" |
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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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``` |
