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README.md
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- instruct
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- lightweight
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- safetensors
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license: other
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license_name: withinusai-custom-license
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- TeichAI/gpt-5.1-codex-max-1000x
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- TeichAI/gpt-5.1-high-reasoning-1000x
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# Metrics
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metrics:
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- pass@1
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- exact_match
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- accuracy
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# Eval
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model-index:
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- name: WithinUsAI/GPT2.5.2-high-reasoning-codex-0.4B
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results: []
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---
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- instruct
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- lightweight
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- safetensors
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+
- withinusai
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license: other
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license_name: withinusai-custom-license
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- TeichAI/gpt-5.1-codex-max-1000x
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- TeichAI/gpt-5.1-high-reasoning-1000x
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# Metrics you intend to report (no fake values)
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metrics:
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- pass@1
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- accuracy
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- exact_match
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# Eval Results container (empty until real numbers are added)
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model-index:
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- name: WithinUsAI/GPT2.5.2-high-reasoning-codex-0.4B
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results: []
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---
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---
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- gpt2
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- causal-lm
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- text-generation
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- code
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- coding
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- reasoning
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- instruct
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- lightweight
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- safetensors
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- withinusai
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license: other
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license_name: withinusai-custom-license
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license_link: LICENSE
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base_model: openai-community/gpt2-medium
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base_model_relation: finetune
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datasets:
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- WithinUsAI/GPT-2-to-GPT-5-5k
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- TeichAI/gpt-5.1-codex-max-1000x
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- TeichAI/gpt-5.1-high-reasoning-1000x
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# Metrics you intend to report (no fake values)
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metrics:
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- pass@1
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- accuracy
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- exact_match
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# Eval Results container (empty until real numbers are added)
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model-index:
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- name: WithinUsAI/GPT2.5.2-high-reasoning-codex-0.4B
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results: []
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---
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Prompting tips (high-reasoning unlock)
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“Give a 3-step plan, then implement.”
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“List edge cases first, then write the code.”
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“Explain root cause → propose fix → provide patch.”
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“State invariants + time/space complexity.”
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Fine-tuning and method (WithIn Us AI)
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WithIn Us AI created the concept, idea, and process behind enhancing GPT-2 Medium toward a GPT-5.2-style “twin target,” including:
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instruction/format design for reasoning + coding
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fine-tuning strategy and iteration process
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naming/versioning of the enhanced model line (“GPT2.5.2”)
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Base model credit
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This work is built on the foundation model:
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openai-community/gpt2-medium
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Training data (datasets used)
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This model is trained using a mixture of WithIn Us AI datasets plus third-party datasets used to improve training results:
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WithIn Us AI dataset (creator-owned):
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WithinUsAI/GPT-2-to-GPT-5-5k
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Third-party datasets (no ownership claimed, credited explicitly):
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TeichAI/gpt-5.1-codex-max-1000x
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TeichAI/gpt-5.1-high-reasoning-1000x
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Evaluation (add results when available)
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The metadata includes a model-index block so evaluation results can be added later and rendered by the Hub.
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Suggested benchmarks:
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Category Benchmark Metric
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Code HumanEval pass@1
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Code MBPP pass@1
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Reasoning Custom reasoning set accuracy
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Reliability Bugfix set fix rate
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Limitations
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May hallucinate library/API details; validate via execution
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Small models can struggle with long multi-hop constraints
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Always run unit tests and check edge cases
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Ethics & responsible use
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Outputs may reflect biases in training data
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Avoid using for harmful instructions or sensitive personal data
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Human review recommended for real deployments
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Thanks & attribution (explicit thanks by username + dataset/model name)
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WithIn Us AI proudly gives thanks and respect to the original creators whose work makes this ecosystem possible:
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Base model foundation (no ownership claimed):
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Thank you to the creators and maintainers of openai-community/gpt2-medium.
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Third-party datasets used (no remixing, no ownership claimed):
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Thank you TeichAI for TeichAI/gpt-5.1-codex-max-1000x.
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Thank you TeichAI for TeichAI/gpt-5.1-high-reasoning-1000x.
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WithIn Us AI original dataset:
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WithinUsAI/GPT-2-to-GPT-5-5k (created by WithIn Us AI)
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WithIn Us AI is excited about collaboration, research, experiments, and breakthrough discovery.
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License
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Licensed under the WithIn Us AI Custom License.
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See LICENSE.
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Citation
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@misc{withinusai_gpt252_high_reasoning_codex_04b,
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title = {WithinUsAI/GPT2.5.2-high-reasoning-codex-0.4B},
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author = {WithIn Us AI},
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year = {2026},
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url = {https://huggingface.co/WithinUsAI/GPT2.5.2-high-reasoning-codex-0.4B}
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}
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Changelog
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v2.5.2: GPT-2 Medium enhanced toward GPT-5.2 twin target (reasoning + codex tuning)
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