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Model: AbacusResearch/haLLAwa3 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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- openchat/openchat-3.5-0106
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- machinists/Mistral-7B-SQL
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model-index:
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- name: haLLAwa3
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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: 67.83
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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=AbacusResearch/haLLAwa3
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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: 87.02
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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=AbacusResearch/haLLAwa3
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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: 64.23
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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=AbacusResearch/haLLAwa3
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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: 63.71
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AbacusResearch/haLLAwa3
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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: 80.51
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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=AbacusResearch/haLLAwa3
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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: 64.75
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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=AbacusResearch/haLLAwa3
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name: Open LLM Leaderboard
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---
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# Hallawa3: The Fusion of Expertise and Precision for 7B Models"
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Unveiling 'Hallawa', an AI marvel that embodies the perfect blend of expert knowledge and cutting-edge technology, tailored for 7B models where direct answers are paramount. This AI powerhouse excels in delivering precise responses, ideal for use cases that demand accuracy and immediacy.
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Excelling in document understanding and prompts in its size.
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With 'Hallawa', you tap into a repository of intelligence that's been acknowledged by over 1400 downloads on the OpenLLM leaderboard, boasting a remarkable score of 71. This model isn't just about quantity but quality, setting new benchmarks in the realm of language models.
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Whether you're looking to enhance customer service, drive research, or accelerate decision-making, 'Hallawa' stands as your go-to solution, engineered to exceed expectations in scenarios where only the most accurate and immediate answers will suffice. Join the ranks of those leveraging 'Hallawa' for their most critical applications and witness the transformation it brings to your operations.
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haLLAwa3 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
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* [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106)
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* [machinists/Mistral-7B-SQL](https://huggingface.co/machinists/Mistral-7B-SQL)
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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: openchat/openchat-3.5-0106
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layer_range: [0, 32]
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- model: machinists/Mistral-7B-SQL
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layer_range: [0, 32]
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merge_method: slerp
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base_model: openchat/openchat-3.5-0106
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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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# [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_AbacusResearch__haLLAwa3)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |71.34|
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|AI2 Reasoning Challenge (25-Shot)|67.83|
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|HellaSwag (10-Shot) |87.02|
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|MMLU (5-Shot) |64.23|
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|TruthfulQA (0-shot) |63.71|
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|Winogrande (5-shot) |80.51|
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|GSM8k (5-shot) |64.75|
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config.json
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{
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"_name_or_path": "paulml/OGNO-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": "4.37.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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mergekit_config.yml
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slices:
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- sources:
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- model: paulml/OGNO-7B
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layer_range: [0, 32]
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- model: AbacusResearch/haLLAwa2
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layer_range: [0, 32]
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merge_method: slerp
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base_model: paulml/OGNO-7B
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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 # fallback for rest of tensors
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dtype: bfloat16
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