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WEIGHTS BF16 · UNMODIFIED | ARCH QWEN3 DENSE · 36L | CONTEXT 256K NATIVE | LICENSE MIT |
Microsoft open-sourced FastContext under MIT, then deleted it from both HuggingFace and GitHub about two weeks later (verified: 404 on both, 2026-07-02). MIT means preservation is legal — so here it is, unmodified. Own your AI: a model on your disk can't be sunset by a quarterly review.
READ / GLOB / GREP) across a repo and returns only the file paths + line ranges that matter, as compact context. Your frontier coding agent stops wasting its context window (and your bill) crawling the file tree.Qwen3ForCausalLM dense 4B — 36 layers, 256K native context. No exotic modules; loads with standard transformers.1from transformers import AutoModelForCausalLM, AutoTokenizer
2m = AutoModelForCausalLM.from_pretrained("KikoCis/FastContext-1.0-4B-SFT", torch_dtype="bfloat16", device_map="auto")
3tok = AutoTokenizer.from_pretrained("KikoCis/FastContext-1.0-4B-SFT")ShaunGves/FastContext-1.0-4B-SFT re-upload after microsoft/FastContext-1.0-4B-SFT was removed. Nothing modified. Quantized companion + validation: KikoCis.