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Model: mlabonne/OmniBeagle-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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base_model:
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- shadowml/BeagleSempra-7B
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- shadowml/BeagSake-7B
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- shadowml/WestBeagle-7B
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model-index:
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- name: OmniBeagle-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: 72.61
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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/OmniBeagle-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: 88.93
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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/OmniBeagle-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: 64.8
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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/OmniBeagle-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: 74.45
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/OmniBeagle-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: 83.11
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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/OmniBeagle-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: 70.05
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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/OmniBeagle-7B
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name: Open LLM Leaderboard
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---
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# OmniBeagle-7B
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OmniBeagle-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [shadowml/BeagleSempra-7B](https://huggingface.co/shadowml/BeagleSempra-7B)
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* [shadowml/BeagSake-7B](https://huggingface.co/shadowml/BeagSake-7B)
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* [shadowml/WestBeagle-7B](https://huggingface.co/shadowml/WestBeagle-7B)
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## 🧩 Configuration
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```yaml
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models:
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- model: mistralai/Mistral-7B-v0.1
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# no parameters necessary for base model
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- model: shadowml/BeagleSempra-7B
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parameters:
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density: 0.65
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weight: 0.4
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- model: shadowml/BeagSake-7B
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parameters:
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density: 0.6
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weight: 0.35
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- model: shadowml/WestBeagle-7B
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parameters:
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density: 0.6
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weight: 0.35
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merge_method: dare_ties
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base_model: mistralai/Mistral-7B-v0.1
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parameters:
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int8_mask: true
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dtype: float16
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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/OmniBeagle-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__OmniBeagle-7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |75.66|
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|AI2 Reasoning Challenge (25-Shot)|72.61|
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|HellaSwag (10-Shot) |88.93|
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|MMLU (5-Shot) |64.80|
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|TruthfulQA (0-shot) |74.45|
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|Winogrande (5-shot) |83.11|
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|GSM8k (5-shot) |70.05|
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25
config.json
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{
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"_name_or_path": "mistralai/Mistral-7B-v0.1",
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"architectures": [
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"MistralForCausalLM"
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],
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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": "float16",
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"transformers_version": "4.35.2",
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"use_cache": true,
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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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models:
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- model: mistralai/Mistral-7B-v0.1
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# no parameters necessary for base model
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- model: shadowml/BeagleSempra-7B
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parameters:
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density: 0.65
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weight: 0.4
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- model: shadowml/BeagSake-7B
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parameters:
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density: 0.6
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weight: 0.35
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- model: shadowml/WestBeagle-7B
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parameters:
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density: 0.6
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weight: 0.35
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merge_method: dare_ties
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base_model: mistralai/Mistral-7B-v0.1
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parameters:
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int8_mask: true
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dtype: float16
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