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Model: kevin009/lamatama Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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model-index:
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- name: lamatama
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 36.35
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 61.12
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 24.72
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 37.67
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 60.77
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 2.27
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kevin009/lamatama
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name: Open LLM Leaderboard
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---
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# Model Card: kevin009/lamatama
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## Model Description
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The `kevin009/lamatama` model is a groundbreaking achievement in the field of language modeling, showcasing the power of leveraging a substantial dataset and state-of-the-art training techniques. This model is designed to push the boundaries of what's possible in natural language understanding and generation.
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### Training Details
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- **Model Architecture**: The `kevin009/lamatama` model is built upon the architecture and tokenizer of Llama 2, ensuring compatibility and easy integration with various open-source projects.
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- **Dataset**: It was pretrained on an impressive 3 trillion tokens, a scale that allows for a deep and nuanced understanding of language.
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- **Training Period**: The training process was carried out over 90 days, utilizing 16 A100-40G GPUs, a testament to the model's efficiency and the team's optimization skills.
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### Fine-tuning
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This specific version of the model has been fine-tuned to excel in chat-based applications. It builds upon the `TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T` model, incorporating learnings and optimizations from HF's Zephyr's training recipe.
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- **Initial Phase**: The model was first fine-tuned on a variant of the UltraChat dataset, which is rich in synthetic dialogues generated by ChatGPT.
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- **Further Alignment**: Subsequent alignment was achieved using 🤗 TRL's DPOTrainer with the openbmb/UltraFeedback dataset, comprising 64k prompts and model completions ranked by GPT-4.
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## How to Use
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Ensure you have `transformers>=4.34`. For detailed instructions and updates, check out the GitHub page for `kevin009/lamatama`.
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### Installation (for versions <= v4.34)
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```bash
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pip install git+https://github.com/huggingface/transformers.git
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pip install accelerate
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```
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### Example Usage
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Here's a quick guide on using `kevin009/lamatama` for generating text:
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```python
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import torch
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from transformers import pipeline
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# Initialize the pipeline
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pipe = pipeline("text-generation", model="kevin009/lamatama", torch_dtype=torch.bfloat16, device_map="auto")
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# Sample dialogue with templating
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messages = [
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{"role": "system", "content": "You are a friendly chatbot who always responds in the style of a pirate"},
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{"role": "user", "content": "How many helicopters can a human eat in one sitting?"}
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]
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# Generate prompt and outputs
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prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipe(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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```
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## Acknowledgements
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This model is a product of collaboration and innovative approaches to language modeling. We extend our thanks to all contributors, as well as the creators of the datasets and training methodologies that made `kevin009/lamatama` a reality.
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---
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This model card introduces `kevin009/lamatama`, a versatile and powerful language model fine-tuned for chat applications, demonstrating exceptional understanding and generation capabilities.
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_kevin009__lamatama)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |37.15|
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|AI2 Reasoning Challenge (25-Shot)|36.35|
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|HellaSwag (10-Shot) |61.12|
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|MMLU (5-Shot) |24.72|
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|TruthfulQA (0-shot) |37.67|
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|Winogrande (5-shot) |60.77|
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|GSM8k (5-shot) | 2.27|
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