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birgermoell
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oellm-9b-128k-theta32m-v3

Text Generation
Transformers
PyTorch
qwen3
long-context
rope
abf
niah
openeurollm
base-model
128k
text-generation-inference
Model card Files
xet
 Community
birgermoell commited on
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Files changed (9) hide show
  1. .gitattributes +1 -0
  2. README.md +16 -0
  3. added_tokens.json +3 -0
  4. config.json +68 -0
  5. pytorch_model.bin +3 -0
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  7. tokenizer.json +3 -0
  8. tokenizer.model +3 -0
  9. tokenizer_config.json +1043 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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+ ---
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+ license: apache-2.0
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+ tags: [long-context, rope, abf, niah, qwen3, openeurollm, base-model]
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # OELLM baby 9B — 128K context (ABF, θ=32M) — v3 (full training)
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+
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+ Fully-trained production version of [oellm-9b-128k-theta32m](https://huggingface.co/birgermoell/oellm-9b-128k-theta32m).
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+ Same θ=32M / 128K config, but **2B tokens** of 128K continued-pretraining (vs the 0.3B
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+ sweep-arm of the original). Base model, multilingual, Qwen3 dense 9B.
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+
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+ θ=32M fixes the far-position (depth-0) retrieval failure that uniform low-θ ABF suffers from
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+ (RoPE high-dimension OOD; critical θ doubles per length-octave: 64K→8M, 128K→16M, and 32M
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+ gives perfect 128K with headroom). Base model — not instruction-tuned. Config: rope_theta=32000000,
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+ max_position_embeddings=131072.
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