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+ ---
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+ license: other
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+ license_name: qwen
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+ license_link: https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ tags:
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+ - chat
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+ - qwen
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+ - qwen2.5
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+ - finetune
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+ - english
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+ library_name: transformers
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+ inference: false
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+ model_creator: MaziyarPanahi
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+ quantized_by: MaziyarPanahi
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+ base_model: MaziyarPanahi/calme-3-selfmerge-qwen2-78b
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+ model_name: calme-3.1-instruct-78b
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+ ---
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+
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+ <img src="./calme_3.png" alt="Calme-3 Models" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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+
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+ > [!TIP]
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+ > This is avery small model, so it might not perform well for some prompts and may be sensitive to hyper parameters. I would appreciate any feedback to see if I can fix any issues in the next iteration. ❤️
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+
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+ # MaziyarPanahi/calme-3.1-instruct-78b
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+
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+ This model is an advanced iteration of the powerful `Qwen/Qwen2.5-72B`, specifically fine-tuned to enhance its capabilities in generic domains. The `Qwen2.5-72B` base model was merged with itself to create a larger model. After that, the model was fine-tuned on a custom datasets.
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+
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+ # ⚡ Quantized GGUF
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+
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+ Coming soon!
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+
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+ # 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+
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+ Leaderboard 2 coming soon!
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+
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+ # Prompt Template
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+
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+ This model uses `ChatML` prompt template:
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+
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+ ```sh
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+ <|im_start|>system
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+ {System}
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+ <|im_end|>
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+ <|im_start|>user
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+ {User}
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+ <|im_end|>
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+ <|im_start|>assistant
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+ {Assistant}
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+ ````
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+
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+ # How to use
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+
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+ ```python
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+
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+ # Use a pipeline as a high-level helper
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+
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+ from transformers import pipeline
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+
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+ messages = [
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+ {"role": "user", "content": "Who are you?"},
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+ ]
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+ pipe = pipeline("text-generation", model="MaziyarPanahi/calme-3.1-instruct-78b")
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+ pipe(messages)
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+
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+
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+ # Load model directly
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+
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+
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+ tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-3.1-instruct-78b")
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+ model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-3.1-instruct-78b")
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+ ```
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+
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+ # Ethical Considerations
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+
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+ As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.