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- README.md +22 -0
AlterEgo.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:47159676f1811c733d28c52cc96f871e4bdf58ba89302761178482fd8a46801b
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README.md
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license: apache-2.0
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- from-scratch
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- raw-checkpoint
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datasets:
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- HuggingFaceFW/fineweb-edu
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- HuggingFaceH4/ultrachat_200k
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# AlterEgo-373M - raw checkpoint
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This repository holds the **original** AlterEgo checkpoint, in the model's **own from-scratch architecture** - i.e. the model exactly as it was trained, before any format conversion.
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- **Want to just use the model?** Use the Hugging Face / `transformers`-native version instead: **[`J-bom/AlterEgo`](https://huggingface.co/J-bom/AlterEgo)**. It's a **numerically-lossless conversion** of this checkpoint to `LlamaForCausalLM` (verified, max logit difference ~1e-6), and works out of the box with `transformers`, vLLM, and GGUF tooling. Full architecture, training details, benchmarks, and usage are documented on that model card.
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- **Want the raw weights / the original architecture?** That's this repo. The checkpoint is a PyTorch state dict saved under the `"model"` key. Load and run it with the model definition and inference code in the training repo: **[github.com/J-bom/AlterEgo](https://github.com/J-bom/AlterEgo)**.
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In short: **`alterego_raw` is the original; [`J-bom/AlterEgo`](https://huggingface.co/J-bom/AlterEgo) is the converted, ready-to-use version.**
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## Model summary
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A 373M-parameter, decoder-only transformer (Llama-style: GQA, RoPE, SwiGLU, RMSNorm) pre-trained from scratch on ~10B tokens of FineWeb-Edu and instruction-tuned on UltraChat-200K (ChatML). See the [main model card](https://huggingface.co/J-bom/AlterEgo) for architecture, training curves, hyperparameters, evaluation, and limitations.
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