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updating new git organization to remove sif file

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mgaughan 2025-06-03 09:52:20 -05:00
parent ff8ca0b46e
commit c50a3b57ff
4 changed files with 2975 additions and 2 deletions
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.gitignore vendored Normal file
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*.sif

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cites/060325_olmo_categorized_citations.csv Normal file
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cites/second-p1-categorization.log Normal file
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starting the job at: Mon Jun 2 22:58:46 CDT 2025
setting up the environment
running the p1 categorization script
cuda
NVIDIA A100-PCIE-40GB
_CudaDeviceProperties(name='NVIDIA A100-PCIE-40GB', major=8, minor=0, total_memory=40442MB, multi_processor_count=108, uuid=a48cfab5-6d74-8479-c725-d4a6e53059e3, L2_cache_size=40MB)
Loading checkpoint shards: 0%| | 0/6 [00:00<?, ?it/s] Loading checkpoint shards: 17%|█▋ | 1/6 [00:01<00:06, 1.36s/it] Loading checkpoint shards: 33%|███▎ | 2/6 [00:02<00:05, 1.33s/it] Loading checkpoint shards: 50%|█████ | 3/6 [00:03<00:03, 1.28s/it] Loading checkpoint shards: 67%|██████▋ | 4/6 [00:05<00:02, 1.46s/it] Loading checkpoint shards: 83%|████████▎ | 5/6 [00:07<00:01, 1.47s/it] Loading checkpoint shards: 100%|██████████| 6/6 [00:08<00:00, 1.30s/it] Loading checkpoint shards: 100%|██████████| 6/6 [00:08<00:00, 1.35s/it]
job finished, cleaning up
job pau at: Tue Jun 3 00:46:04 CDT 2025

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models/p1-categorization.py
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@ -12,7 +12,7 @@ olmo = AutoModelForCausalLM.from_pretrained("allenai/OLMo-2-1124-7B").to(device)
tokenizer = AutoTokenizer.from_pretrained("allenai/OLMo-2-1124-7B")
#priming prompt
prompt_1 = "For the GIVEN DATA, Please categorize it based on the following numbered characteristics: \n\n 1: YES/NO (Characteristic 1. This is an English language empirical study. Empirical studies discuss data or observations.) \n 2: YES/NO (Characteristic 2. This discusses free and open source software (FOSS or OSS). The focus of the GIVEN DATA is on free or open source software projects or ecosystems.) \n 3: YES/NO (Characteristic 3. The GIVEN DATA discusses FOSS project evolution. FOSS project evolution describes any changes to free and open source projects.) \n 4: YES/NO (Characteristic 4. This GIVEN DATA discusses FOSS project adaptation. FOSS project adaptation describes the intentional strategic changes made by projects to better align with the project's broader environment.) \n\n Only respond with the appropriate number followed by 'YES' if the characteristic is present in the provided data or 'NO' if it is not (e.g. '1. YES; 2. NO;'). Do not provide any additional information."
prompt_1 = "For the GIVEN DATA, Please categorize it based on the following numbered characteristics: \n\n 1: YES/NO (Characteristic 1. This is an English language empirical study. Empirical studies discuss data or observations.) \n 2: YES/NO (Characteristic 2. This discusses free and open source software (FOSS or OSS). The focus of the GIVEN DATA is on free or open source software projects or ecosystems.) \n 3: YES/NO (Characteristic 3. The GIVEN DATA discusses FOSS project evolution. FOSS project evolution describes any changes to free and open source projects.) \n 4: YES/NO (Characteristic 4. This GIVEN DATA discusses FOSS project adaptation. FOSS project adaptation describes the intentional strategic changes made by projects to better align with the project's broader environment.) \n\n Characteristics 2, 3, and 4 can only be YES if the preceding characteristic was also a YES. \n\n Only respond with the appropriate number followed by 'YES' if the characteristic is present in the provided data or 'NO' if it is not (e.g. '1. YES; 2. NO;'). Do not provide any additional information."
example_4 = "Example 4: TITLE - Analysis of Open Source Software Evolution Using Evolution Curve Method \n ABSTRACT - Design and evolution of modem information systems is influenced by many factors: technical, organizational, social, and psychological. This is especially true for open source software systems (OSSS), when many developers from different backgrounds interact, share their ideas and contribute towards the development and improvement of a software product. The evolution of all OSSS is a continuous process of source code development, adaptation, improvement and maintenance. Studying changes to the various characteristics of source code can help us understand the evolution of a software system. In this paper, the software evolution process is analyzed using a proposed Evolution curve (E-curve) method, which is based on information theoretic metrics of source code. The method allows identifying major evolution stages and transition points of an analyzed software system. The application of the E-curves is demonstrated for the eMule system. .\n CATEGORIES: 1. YES; 2. YES; 3.YES; 4. NO"
@ -62,4 +62,4 @@ with open("cites/053025_man_filtered_dedup.csv", mode='r', newline='') as file:
array_of_categorizations.append(cite_dict)
#CSV everything
df = pd.DataFrame(array_of_categorizations)
df.to_csv('060225_olmo_categorized_citations.csv', index=False)
df.to_csv('060325_olmo_categorized_citations.csv', index=False)