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Model: mayacinka/yam-sam-7B Source: Original Platform
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README.md
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---
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license: apache-2.0
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tags:
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- merge
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- mergekit
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- lazymergekit
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- cognitivecomputations/samantha-mistral-7b
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- CorticalStack/shadow-clown-7B-dare
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- yam-peleg/Experiment26-7B
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base_model:
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- cognitivecomputations/samantha-mistral-7b
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- CorticalStack/shadow-clown-7B-dare
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- yam-peleg/Experiment26-7B
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model-index:
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- name: yam-sam-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: 70.9
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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=mayacinka/yam-sam-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: 87.92
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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=mayacinka/yam-sam-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: 65.39
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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=mayacinka/yam-sam-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: 71.3
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mayacinka/yam-sam-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: 83.03
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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=mayacinka/yam-sam-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: 68.92
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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=mayacinka/yam-sam-7B
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name: Open LLM Leaderboard
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---
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# yam-sam-7B
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yam-sam-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [cognitivecomputations/samantha-mistral-7b](https://huggingface.co/cognitivecomputations/samantha-mistral-7b)
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* [CorticalStack/shadow-clown-7B-dare](https://huggingface.co/CorticalStack/shadow-clown-7B-dare)
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* [yam-peleg/Experiment26-7B](https://huggingface.co/yam-peleg/Experiment26-7B)
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## 🧩 Configuration
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```yaml
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models:
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- model: yam-peleg/Experiment27-7B
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# No parameters necessary for base model
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- model: cognitivecomputations/samantha-mistral-7b
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parameters:
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weight: 0.3
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density: 0.8
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- model: CorticalStack/shadow-clown-7B-dare
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parameters:
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weight: 0.1
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density: 0.8
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- model: yam-peleg/Experiment26-7B
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parameters:
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weight: 0.6
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density: 0.8
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merge_method: dare_ties
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base_model: yam-peleg/Experiment27-7B
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parameters:
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int8_mask: true
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dtype: bfloat16
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random_seed: 0
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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 = "mayacinka/yam-sam-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_mayacinka__yam-sam-7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |74.58|
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|AI2 Reasoning Challenge (25-Shot)|70.90|
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|HellaSwag (10-Shot) |87.92|
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|MMLU (5-Shot) |65.39|
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|TruthfulQA (0-shot) |71.30|
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|Winogrande (5-shot) |83.03|
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|GSM8k (5-shot) |68.92|
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config.json
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{
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"_name_or_path": "yam-peleg/Experiment27-7B",
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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": "4.38.1",
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"use_cache": true,
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"vocab_size": 32000
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}
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23
mergekit_config.yml
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mergekit_config.yml
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models:
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- model: yam-peleg/Experiment27-7B
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# No parameters necessary for base model
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- model: cognitivecomputations/samantha-mistral-7b
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parameters:
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weight: 0.3
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density: 0.8
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- model: CorticalStack/shadow-clown-7B-dare
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parameters:
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weight: 0.1
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density: 0.8
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- model: yam-peleg/Experiment26-7B
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parameters:
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weight: 0.6
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density: 0.8
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merge_method: dare_ties
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base_model: yam-peleg/Experiment27-7B
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parameters:
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int8_mask: true
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dtype: bfloat16
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random_seed: 0
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model-00001-of-00002.safetensors
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