Create README.md

README.md

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+
+
+
+## FP8 Compress
+
+```python
+
+# ============================================================================
+# MIXTRAL 8x7B — FP8 COMPRESSION WITH LLMCOMPRESSOR
+# ============================================================================
+# INSTRUCTIONS — run these cells IN ORDER in a fresh Colab session:
+#
+# CELL 1 (installs — run first, then RESTART RUNTIME):
+# -------------------------------------------------------
+# !pip uninstall torchvision -y
+# !pip install llmcompressor==0.4.2 -q
+# !pip install torch==2.4.1 torchvision==0.19.1 --index-url https://download.pytorch.org/whl/cu121 -q
+#
+# CELL 2 (compression — run after restart):
+# -------------------------------------------------------
+# [paste everything below this line]
+# ============================================================================
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from llmcompressor import oneshot
+from llmcompressor.modifiers.quantization import QuantizationModifier
+import torch, os
+
+print(f"torch={torch.__version__}")
+
+MODEL_ID = "mistralai/Mixtral-8x7B-v0.1"
+SAVE_DIR = "/content/mixtral-8x7b-fp8-topo2026"
+HF_REPO  = "frankmorales2020/mixtral-8x7b-fp8-topo2026"
+
+# ── Load ─────────────────────────────────────────────────────────────────────
+print(f"\n[COMPRESS] Loading {MODEL_ID}...")
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_ID,
+    device_map="auto",
+    torch_dtype="auto",
+    trust_remote_code=True,
+)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
+if tokenizer.pad_token is None:
+    tokenizer.pad_token = tokenizer.eos_token
+print("[COMPRESS] Loaded.")
+
+# ── Recipe ───────────────────────────────────────────────────────────────────
+# re:.*embed.* excluded → embedding matrix stays BF16 — CRITICAL for TOPO-2026
+# re:.*gate.*  excluded → MoE routers stay BF16
+recipe = QuantizationModifier(
+    targets="Linear",
+    scheme="FP8",
+    ignore=["lm_head", "re:.*gate.*", "re:.*embed.*"]
+)
+
+print("\n[COMPRESS] Recipe: FP8 | ignore: lm_head, gates, embeddings")
+
+# ── Compress ─────────────────────────────────────────────────────────────────
+print("\n[COMPRESS] Running oneshot (512 calibration samples)...")
+oneshot(
+    model=model,
+    recipe=recipe,
+    tokenizer=tokenizer,
+    dataset="open_platypus",
+    num_calibration_samples=512,
+    max_seq_length=2048,
+)
+print("[COMPRESS] Done.")
+
+# ── Save ─────────────────────────────────────────────────────────────────────
+os.makedirs(SAVE_DIR, exist_ok=True)
+model.save_pretrained(SAVE_DIR, save_compressed=True)
+tokenizer.save_pretrained(SAVE_DIR)
+print(f"[COMPRESS] Saved to {SAVE_DIR}")
+
+# ── Push to Hub ───────────────────────────────────────────────────────────────
+from huggingface_hub import login, create_repo, upload_folder
+try:
+    from google.colab import userdata
+    HF_TOKEN = userdata.get('HF_TOKEN')
+except Exception:
+    HF_TOKEN = None
+
+login(token=HF_TOKEN, add_to_git_credential=True)
+create_repo(repo_id=HF_REPO, repo_type="model", exist_ok=True,
+            private=False, token=HF_TOKEN)
+upload_folder(
+    repo_id=HF_REPO, folder_path=SAVE_DIR, repo_type="model",
+    token=HF_TOKEN,
+    commit_message=(
+        "Mixtral-8x7B FP8 TOPO-2026 | "
+        "Embeddings BF16 | MoE gates BF16 | LLMCompressor"
+    )
+)
+print(f"\n✨ https://huggingface.co/{HF_REPO}")
+
+```