README: add concrete How-to-use (stdlib header read + safetensors load)

README.md

@@ -67,6 +67,29 @@ architecture without touching the 753B weights.
 the build environment), and whether `GlmMoeDsaForCausalLM` accepts this reduced geometry without
 extra fields. Treat those as open until run against a real install.
 
+## How to use
+Read the tensors with the standard library (no torch needed, matching how this was built):
+
+```python
+import json, struct
+with open("model.safetensors", "rb") as f:
+    n = struct.unpack("<Q", f.read(8))[0]
+    header = json.loads(f.read(n))
+    # header[name] = {"dtype", "shape", "data_offsets"}; data starts at byte 8+n
+```
+
+Or with the `safetensors` package:
+
+```python
+from safetensors.torch import load_file
+tensors = load_file("model.safetensors")   # {name: tensor}
+```
+
+To exercise a real loader, build a config from `config.json` (the `glm_moe_dsa`
+model type; use `AutoConfig.from_pretrained(..., trust_remote_code=True)` where
+needed) and feed these weights in. There is no `lm_head` tensor and the tokenizer
+files are placeholders, so supply your own head/tokenizer.
+
 ## License
 MIT, unchanged from the base model per its Hub metadata. See `LICENSE`.