| """Broad ecosystem screen: how many RELEASED Llama-3.1-8B derivatives have actually left the base |
| model's coordinate frame? Streams one model at a time (download -> screen -> delete) so the disk |
| footprint stays at one checkpoint.""" |
| import os, sys, json, time, gc, shutil, traceback |
| sys.path.insert(0, "/root/merge-accuracy") |
| import numpy as np, torch |
| from huggingface_hub import snapshot_download, hf_hub_download |
| import ma_common as C, gmap |
| from cheap_screen import screen |
| from mergeschool.core import alignment as AL |
|
|
| OUT = "/root/merge-accuracy/results/ecosystem_screen.json" |
| CACHE = "/root/hf_cache_mergeacc" |
| BASE = "meta-llama/Llama-3.1-8B" |
| CAND = [ |
| ("NousResearch/Hermes-3-Llama-3.1-8B", "instruct post-training", "Nous Research"), |
| ("allenai/Llama-3.1-Tulu-3-8B-SFT", "instruct SFT", "AI2"), |
| ("dphn/Dolphin3.0-Llama3.1-8B", "instruct post-training", "Dolphin"), |
| ("meta-llama/Llama-Guard-3-8B", "safety classifier", "Meta"), |
| ("fdtn-ai/Foundation-Sec-8B", "domain CPT (security)", "Foundation AI"), |
| ("OpenSciLM/Llama-3.1_OpenScholar-8B", "domain CPT (science)", "OpenSciLM"), |
| ("nvidia/OpenMath2-Llama3.1-8B", "domain SFT (maths)", "NVIDIA"), |
| ("NCSOFT/Llama-VARCO-8B-Instruct", "language CPT (Korean)", "NCSOFT"), |
| ("McGill-NLP/AfriqueLlama-8B", "language CPT (African)", "McGill NLP"), |
| ("Yiddish-NLP/MameLoshnLM", "language CPT (Yiddish)", "Yiddish-NLP"), |
| ("deepcogito/cogito-v1-preview-llama-8B", "instruct post-training", "Deep Cogito"), |
| ("tokyotech-llm/Llama-3.1-Swallow-8B-v0.2", "language CPT (Japanese)", "TokyoTech"), |
| ("aisingapore/Llama-SEA-LION-v3-8B", "language CPT (SEA)", "AI Singapore"), |
| ("microsoft/UserLM-8b", "role post-training", "Microsoft"), |
| ] |
| res = json.load(open(OUT)) if os.path.exists(OUT) else {} |
|
|
| mb = C.load_model(BASE, dev="cpu", dtype=torch.float32) |
| sd_base = C.sd_np(mb); cfg = mb.config |
| HID, NH, NKV, VOC = cfg.hidden_size, cfg.num_attention_heads, cfg.num_key_value_heads, cfg.vocab_size |
| del mb; gc.collect() |
| print(f"base ready HID={HID} NH={NH} NKV={NKV}", flush=True) |
|
|
| for repo, kind, group in CAND: |
| if repo in res: continue |
| d = None |
| try: |
| cfp = hf_hub_download(repo, "config.json", cache_dir=CACHE) |
| c = json.load(open(cfp)) |
| if (c.get("hidden_size") != HID or c.get("num_attention_heads") != NH |
| or c.get("num_key_value_heads") != NKV or c.get("vocab_size") != VOC |
| or c.get("num_hidden_layers") != cfg.num_hidden_layers): |
| res[repo] = {"kind": kind, "group": group, "status": "shape mismatch", |
| "config": {k: c.get(k) for k in ("hidden_size", "num_attention_heads", |
| "num_key_value_heads", "vocab_size", |
| "num_hidden_layers")}} |
| print(f"SKIP {repo}: shape mismatch", flush=True) |
| json.dump(res, open(OUT, "w"), indent=1); continue |
| t0 = time.time() |
| d = snapshot_download(repo, allow_patterns=["*.safetensors", "*.json", "tokenizer*"], |
| cache_dir=CACHE, max_workers=8) |
| dl = time.time() - t0 |
| m = C.load_model(repo, dev="cpu", dtype=torch.float32) |
| sd = C.sd_np(m); del m; gc.collect() |
| t = time.time(); f_id, pres = screen(sd, sd_base, HID); dt = time.time() - t |
| keys = C.shared_keys(sd_base, sd) |
| a = np.concatenate([sd_base[k].ravel() for k in keys]) |
| b = np.concatenate([sd[k].ravel() for k in keys]) |
| wc = float(a @ b / (np.linalg.norm(a) * np.linalg.norm(b))) |
| rd = float(np.linalg.norm(a - b) / np.linalg.norm(a)) |
| del a, b, sd; gc.collect() |
| res[repo] = {"kind": kind, "group": group, "status": "screened", |
| "identity_fraction_worst_layer": f_id, "screen_seconds": dt, |
| "download_seconds": dl, "layers_screened": len(pres), |
| "weight_cosine_vs_base": wc, "rel_drift": rd, |
| "frame_has_drifted": bool(f_id < 0.95)} |
| print(f"{repo:48s} id_frac={f_id:.4f} wcos={wc:.4f} drift={rd:.4f} " |
| f"-> {'DRIFTED' if f_id < 0.95 else 'same frame'} ({dt:.0f}s)", flush=True) |
| json.dump(res, open(OUT, "w"), indent=1) |
| except Exception: |
| res[repo] = {"kind": kind, "group": group, "status": "error", |
| "error": traceback.format_exc()[-400:]} |
| print(f"ERR {repo}: {traceback.format_exc()[-250:]}", flush=True) |
| json.dump(res, open(OUT, "w"), indent=1) |
| finally: |
| |
| keep = ("Llama-3.1-8B", "Llama-3.1-8B-Instruct", "Swallow-8B-v0.1", |
| "typhoon2", "sea-lionv3-base") |
| if not any(k in repo for k in keep): |
| p = f"{CACHE}/models--" + repo.replace("/", "--") |
| if os.path.isdir(p): |
| shutil.rmtree(p, ignore_errors=True) |
| gc.collect() |
| print("SWEEP_DONE", flush=True) |
|
|
