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--- |
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base_model: SvalTek/Qwen3-ColdBrew-14B |
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tags: |
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- merge |
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- lazymergekit |
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--- |
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# ColdBrew-12B-Nemo-test2 |
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## 🧩 Configuration |
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```yaml |
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name: ColdBrew-12B-Nemo-test2 |
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models: |
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- model: SvalTek/ColdBrew-12B-Nemo-test1 |
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parameters: |
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weight: 1.0 |
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- model: elinas/Chronos-Gold-12B-1.0 |
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parameters: |
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weight: 0.3 |
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base_model: SvalTek/ColdBrew-12B-Nemo-test1 |
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merge_method: task_arithmetic |
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chat_template: "chatml" |
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tokenizer: |
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source: union # keep everyone’s vocab; union is a documented option |
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tokens: |
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"<|im_start|>": |
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source: "elinas/Chronos-Gold-12B-1.0" |
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force: true |
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"<|im_end|>": |
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source: "elinas/Chronos-Gold-12B-1.0" |
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force: true |
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dtype: bfloat16 |
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normalize: true |
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int8_mask: true |
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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 = "SvalTek/ColdBrew-12B-Nemo-test2" |
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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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``` |
