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the-cramer-project/cpt-models-t3

sourceHugging Faceotherupdated 3mo agoView on Hugging Face
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CPT merged full models — run t3pilot (t3 cross-lingual experiment)

Standalone full models = base (meta-llama/Llama-3.1-8B) with the trained LoRA adapter merged in (r=64, lr=5e-5, 30% English mixed stream, 2 epochs, frozen embeddings/lmhead). Load directly with `AutoModelForCausalLM.frompretrained, no PEFT. Per-language eval losses are in manifest.json`.

Load

python
from transformers import AutoModelForCausalLM, AutoTokenizer
mid = "the-cramer-project/cpt-models-t3"
sub = "Llama-3.1-8B/FT-KY"
model = AutoModelForCausalLM.from_pretrained(mid, subfolder=sub, torch_dtype="bfloat16")
tok   = AutoTokenizer.from_pretrained(mid, subfolder=sub)

Models

SubfolderBaseLanguageLoRA rLRTarget eval loss
Llama-3.1-8B/FT-KYmeta-llama/Llama-3.1-8BKyrgyz645e-051.021923542022705
Llama-3.1-8B/FT-KZmeta-llama/Llama-3.1-8BKazakh645e-051.0028022527694702