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Model: fhai50032/BeagleLake-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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- mistral
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- fhai50032/RolePlayLake-7B
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- mlabonne/NeuralBeagle14-7B
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base_model:
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- fhai50032/RolePlayLake-7B
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- mlabonne/NeuralBeagle14-7B
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model-index:
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- name: BeagleLake-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: 70.39
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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=fhai50032/BeagleLake-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: 87.38
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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=fhai50032/BeagleLake-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: 64.25
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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=fhai50032/BeagleLake-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: 64.92
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/BeagleLake-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: 83.19
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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=fhai50032/BeagleLake-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: 63.91
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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=fhai50032/BeagleLake-7B
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name: Open LLM Leaderboard
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---
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# BeagleLake-7B
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BeagleLake-7B is a merge of the following models :
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* [fhai50032/RolePlayLake-7B](https://huggingface.co/fhai50032/RolePlayLake-7B)
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* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
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Merging models are not powerful but are helpful in the case that it can work like Transfer Learning similar idk.. But they perform high on Leaderboard
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For ex. NeuralBeagle is powerful model with lot of potential to grow and RolePlayLake is Suitable for RP (No-Simping) and is significantly uncensored and nice obligations
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Fine-tuning a Merged model as a base model is surely a way to look forward and see a lot of potential going forward..
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Much thanks to [Charles Goddard](https://huggingface.co/chargoddard) for making simple interface ['mergekit' ](https://github.com/cg123/mergekit)
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## 🧩 Configuration
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```yaml
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models:
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- model: mlabonne/NeuralBeagle14-7B
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# no params for base model
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- model: fhai50032/RolePlayLake-7B
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parameters:
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weight: 0.8
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density: 0.6
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- model: mlabonne/NeuralBeagle14-7B
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parameters:
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weight: 0.3
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density: [0.1,0.3,0.5,0.7,1]
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merge_method: dare_ties
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base_model: mlabonne/NeuralBeagle14-7B
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parameters:
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normalize: true
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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 = "fhai50032/BeagleLake-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_fhai50032__BeagleLake-7B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |72.34|
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|AI2 Reasoning Challenge (25-Shot)|70.39|
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|HellaSwag (10-Shot) |87.38|
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|MMLU (5-Shot) |64.25|
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|TruthfulQA (0-shot) |64.92|
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|Winogrande (5-shot) |83.19|
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|GSM8k (5-shot) |63.91|
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26
config.json
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{
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"_name_or_path": "mlabonne/NeuralBeagle14-7B",
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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": "float16",
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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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18
mergekit_config.yml
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mergekit_config.yml
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models:
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- model: mlabonne/NeuralBeagle14-7B
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# no params for base model
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- model: fhai50032/RolePlayLake-7B
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parameters:
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weight: 0.8
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density: 0.6
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- model: mlabonne/NeuralBeagle14-7B
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parameters:
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weight: 0.3
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density: [0.1,0.3,0.5,0.7,1]
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merge_method: dare_ties
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base_model: mlabonne/NeuralBeagle14-7B
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parameters:
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normalize: true
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int8_mask: true
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dtype: float16
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special_tokens_map.json
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special_tokens_map.json
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tokenizer.model
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}
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