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Model: mwitiderrick/open_llama_3b_code_instruct_0.1 Source: Original Platform
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README.md
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- transformers
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datasets:
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- mwitiderrick/AlpacaCode
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base_model: openlm-research/open_llama_3b
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inference: true
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model_type: llama
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prompt_template: '### Instruction:\n
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{prompt}
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### Response:
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'
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created_by: mwitiderrick
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pipeline_tag: text-generation
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model-index:
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- name: mwitiderrick/open_llama_3b_instruct_v_0.2
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results:
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- task:
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type: text-generation
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dataset:
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name: hellaswag
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type: hellaswag
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metrics:
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- type: hellaswag (0-Shot)
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value: 0.6581
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name: hellaswag(0-Shot)
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- task:
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type: text-generation
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dataset:
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name: winogrande
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type: winogrande
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metrics:
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- type: winogrande (0-Shot)
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value: 0.6267
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name: winogrande(0-Shot)
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- task:
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type: text-generation
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dataset:
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name: arc_challenge
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type: arc_challenge
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metrics:
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- type: arc_challenge (0-Shot)
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value: 0.3712
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name: arc_challenge(0-Shot)
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source:
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url: https://huggingface.co/mwitiderrick/open_llama_3b_instruct_v_0.2
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name: open_llama_3b_instruct_v_0.2 model card
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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: 41.21
|
||||
name: normalized accuracy
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||||
source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1
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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: 66.96
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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=mwitiderrick/open_llama_3b_code_instruct_0.1
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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: 27.82
|
||||
name: accuracy
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||||
source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1
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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: 35.01
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source:
|
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1
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name: Open LLM Leaderboard
|
||||
- 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: 65.43
|
||||
name: accuracy
|
||||
source:
|
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1
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name: Open LLM Leaderboard
|
||||
- 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: 1.9
|
||||
name: accuracy
|
||||
source:
|
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mwitiderrick/open_llama_3b_code_instruct_0.1
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name: Open LLM Leaderboard
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---
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# OpenLLaMA Code Instruct: An Open Reproduction of LLaMA
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This is an [OpenLlama model](https://huggingface.co/openlm-research/open_llama_3b) that has been fine-tuned on 1 epoch of the
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[AlpacaCode](https://huggingface.co/datasets/mwitiderrick/AlpacaCode) dataset (122K rows).
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## Prompt Template
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```
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### Instruction:
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{query}
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### Response:
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<Leave new line for model to respond>
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```
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM,pipeline
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tokenizer = AutoTokenizer.from_pretrained("mwitiderrick/open_llama_3b_code_instruct_0.1")
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model = AutoModelForCausalLM.from_pretrained("mwitiderrick/open_llama_3b_code_instruct_0.1")
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query = "Write a quick sort algorithm in Python"
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text_gen = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
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output = text_gen(f"### Instruction:\n{query}\n### Response:\n")
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print(output[0]['generated_text'])
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"""
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### Instruction:
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write a quick sort algorithm in Python
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### Response:
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def quick_sort(arr):
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if len(arr) <= 1:
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return arr
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else:
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pivot = arr[len(arr) // 2]
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left = [x for x in arr if x < pivot]
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middle = [x for x in arr if x == pivot]
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right = [x for x in arr if x > pivot]
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return quick_sort(left) + middle + quick_sort(right)
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arr = [5,2,4,3,1]
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print(quick_sort(arr))
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"""
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[1, 2, 3, 4, 5]
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"""
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```
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## Metrics
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[Detailed metrics](https://huggingface.co/datasets/open-llm-leaderboard/details_mwitiderrick__open_llama_3b_code_instruct_0.1)
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```
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| Tasks |Version|Filter|n-shot|Metric|Value | |Stderr|
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|----------|-------|------|-----:|------|-----:|---|-----:|
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|winogrande|Yaml |none | 0|acc |0.6267|± |0.0136|
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||||
|hellaswag|Yaml |none | 0|acc |0.4962|± |0.0050|
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||||
| | |none | 0|acc_norm|0.6581|± |0.0047|
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||||
|arc_challenge|Yaml |none | 0|acc |0.3481|± |0.0139|
|
||||
| | |none | 0|acc_norm|0.3712|± |0.0141|
|
||||
|truthfulqa|N/A |none | 0|bleu_max | 24.2580|± |0.5985|
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||||
| | |none | 0|bleu_acc | 0.2876|± |0.0003|
|
||||
| | |none | 0|bleu_diff | -8.3685|± |0.6065|
|
||||
| | |none | 0|rouge1_max | 49.3907|± |0.7350|
|
||||
| | |none | 0|rouge1_acc | 0.2558|± |0.0002|
|
||||
| | |none | 0|rouge1_diff|-10.6617|± |0.6450|
|
||||
| | |none | 0|rouge2_max | 32.4189|± |0.9587|
|
||||
| | |none | 0|rouge2_acc | 0.2142|± |0.0002|
|
||||
| | |none | 0|rouge2_diff|-12.9903|± |0.9539|
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||||
| | |none | 0|rougeL_max | 46.2337|± |0.7493|
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||||
| | |none | 0|rougeL_acc | 0.2424|± |0.0002|
|
||||
| | |none | 0|rougeL_diff|-11.0285|± |0.6576|
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| | |none | 0|acc | 0.3072|± |0.0405|
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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_mwitiderrick__open_llama_3b_code_instruct_0.1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |39.72|
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|AI2 Reasoning Challenge (25-Shot)|41.21|
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|HellaSwag (10-Shot) |66.96|
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|MMLU (5-Shot) |27.82|
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|TruthfulQA (0-shot) |35.01|
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|Winogrande (5-shot) |65.43|
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|GSM8k (5-shot) | 1.90|
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28
config.json
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{
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"_name_or_path": "openlm-research/open_llama_3b",
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"architectures": [
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"LlamaForCausalLM"
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],
|
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"attention_bias": false,
|
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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": 3200,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 8640,
|
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"max_position_embeddings": 2048,
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"model_type": "llama",
|
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"num_attention_heads": 32,
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"num_hidden_layers": 26,
|
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"num_key_value_heads": 32,
|
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
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"rope_theta": 10000.0,
|
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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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24
special_tokens_map.json
Normal file
24
special_tokens_map.json
Normal file
@@ -0,0 +1,24 @@
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|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "</s>",
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
96955
tokenizer.json
Normal file
96955
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:ab1b681ec7fc02fed5edd3026687d7a692a918c4dd8e150ca2e3994a6229843b
|
||||
size 534194
|
||||
41
tokenizer_config.json
Normal file
41
tokenizer_config.json
Normal file
@@ -0,0 +1,41 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 2048,
|
||||
"pad_token": "</s>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user