JustVugg
1ae22a6135
Engine (c/glm.c): MLA attention with compressed KV, sigmoid noaux_tc router, int8/int4/int2 quant kernels (AVX2), per-layer LRU expert cache + pinned hot-store, batch-union MoE, native MTP speculative decoding (lossless), multi-stop + official chat template, RAM auto-budget from MemAvailable. Tokenizer: byte-level BPE in C. Tooling: coli CLI, disk-safe FP8→int4 converter, tiny-random oracle validation (TF 32/32, greedy 20/20). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
24 lines
371 B
Plaintext
24 lines
371 B
Plaintext
# ambienti python / cache
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c/mio_env/
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__pycache__/
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**/__pycache__/
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*.pyc
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# binari compilati (si rigenerano con make / coli build)
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c/glm
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c/olmoe
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c/iobench
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c/tok_test
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# oracoli tiny generati (make_glm_oracle.py) e dati benchmark scaricati
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c/glm_tiny/
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c/glm_tiny_i2/
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c/glm_tiny_i4/
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c/glm_tiny_mix/
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c/bench/
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# pesi modello / artefatti di run
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*.safetensors
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stats*.txt
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*.log
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