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Model: mlabonne/Beagle14-7B Source: Original Platform
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README.md
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---
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license: cc-by-nc-4.0
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tags:
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- merge
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- mergekit
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- lazymergekit
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- fblgit/UNA-TheBeagle-7b-v1
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- argilla/distilabeled-Marcoro14-7B-slerp
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base_model:
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- fblgit/UNA-TheBeagle-7b-v1
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- argilla/distilabeled-Marcoro14-7B-slerp
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model-index:
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- name: Beagle14-7B
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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: 72.95
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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=mlabonne/Beagle14-7B
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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: 87.95
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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=mlabonne/Beagle14-7B
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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: 64.7
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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=mlabonne/Beagle14-7B
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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: 68.88
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B
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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: 82.64
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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=mlabonne/Beagle14-7B
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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: 71.42
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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=mlabonne/Beagle14-7B
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name: Open LLM Leaderboard
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---
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# Beagle14-7B
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**Update 01/16/24: Check the DPO fine-tuned version of this model, [NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B) (probably the best 7B model you can find)! 🎉**
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Beagle14-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [fblgit/UNA-TheBeagle-7b-v1](https://huggingface.co/fblgit/UNA-TheBeagle-7b-v1)
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* [argilla/distilabeled-Marcoro14-7B-slerp](https://huggingface.co/argilla/distilabeled-Marcoro14-7B-slerp)
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## 🏆 Evaluation
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The evaluation was performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval) on Nous suite.
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| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
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|----------------------------------------------------------|------:|------:|---------:|-------:|------:|
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|[**Beagle14-7B**](https://huggingface.co/mlabonne/Beagle14-7B)| **44.38**| **76.53**| **69.44**| **47.25**| **59.4**|
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|[OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)| 42.75| 72.99| 52.99| 40.94| 52.42|
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|[NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)| 43.67| 73.24| 55.37| 41.76| 53.51|
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|[Nous-Hermes-2-SOLAR-10.7B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B)| 47.79| 74.69| 55.92| 44.84| 55.81|
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|[Marcoro14-7B-slerp](https://huggingface.co/mlabonne/Marcoro14-7B-slerp) | 44.66| 76.24| 64.15| 45.64| 57.67|
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|[CatMarcoro14-7B-slerp](https://huggingface.co/occultml/CatMarcoro14-7B-slerp)| 45.21| 75.91| 63.81| 47.31| 58.06|
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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: fblgit/UNA-TheBeagle-7b-v1
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layer_range: [0, 32]
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- model: argilla/distilabeled-Marcoro14-7B-slerp
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layer_range: [0, 32]
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merge_method: slerp
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base_model: fblgit/UNA-TheBeagle-7b-v1
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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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 = "mlabonne/Beagle14-7B"
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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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```
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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_mlabonne__Beagle14-7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |74.76|
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|AI2 Reasoning Challenge (25-Shot)|72.95|
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|HellaSwag (10-Shot) |87.95|
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|MMLU (5-Shot) |64.70|
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|TruthfulQA (0-shot) |68.88|
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|Winogrande (5-shot) |82.64|
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|GSM8k (5-shot) |71.42|
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config.json
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{
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"_name_or_path": "fblgit/UNA-TheBeagle-7b-v1",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.35.2",
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"use_cache": false,
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"vocab_size": 32000
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}
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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mergekit_config.yml
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mergekit_config.yml
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slices:
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- sources:
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- model: fblgit/UNA-TheBeagle-7b-v1
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layer_range: [0, 32]
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- model: argilla/distilabeled-Marcoro14-7B-slerp
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layer_range: [0, 32]
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merge_method: slerp
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base_model: fblgit/UNA-TheBeagle-7b-v1
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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tokenizer_config.json
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