Update clean backend-only project docs and eval

scripts/train_available.py

@@ -12,7 +12,7 @@ import argparse
 import json
 import os
 from pathlib import Path
-from typing import Any
+from typing import Any, cast
 
 import torch
 from datasets import Dataset
@@ -194,14 +194,14 @@ def load_model(model_name: str, quantization: str) -> tuple[Any, Any, bool]:
             quantization_config = BitsAndBytesConfig(
                 load_in_4bit=True,
                 bnb_4bit_quant_type="nf4",
-                bnb_4bit_compute_dtype=torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float16,
+                bnb_4bit_compute_dtype=cast(Any, torch).bfloat16 if torch.cuda.is_bf16_supported() else cast(Any, torch).float16,
                 bnb_4bit_use_double_quant=True,
             )
         except Exception as exc:
             print(f"[WARN] 4-bit config unavailable, falling back to 16-bit load: {exc}")
             use_4bit = False
 
-    dtype = torch.bfloat16 if torch.cuda.is_available() and torch.cuda.is_bf16_supported() else torch.float16
+    dtype = cast(Any, torch).bfloat16 if torch.cuda.is_available() and torch.cuda.is_bf16_supported() else cast(Any, torch).float16
     model_kwargs: dict[str, Any] = {
         "trust_remote_code": True,
         "device_map": "auto" if torch.cuda.is_available() else None,