Add dataset metadata

README.md

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+---
+tags:
+- lmprobe
+- activations
+- interpretability
+- meta-llama-llama-3.1-405b
+task_categories:
+- feature-extraction
+language:
+- en
+license: cc-by-4.0
+---
+
+# meta-llama/Llama-3.1-405B — Activation Dataset
+
+Cached activations extracted from [`meta-llama/Llama-3.1-405B`](https://huggingface.co/meta-llama/Llama-3.1-405B) (revision `b906e4dc842aa489c962f9db26554dcfdde901fe`).
+
+LateNet v0 activations for Llama 3.1 405B base (all layers, full sequence)
+
+## Contents
+
+| Tensor | Layers | Dim | Pooling | Shards | Row Bytes |
+|--------|--------|-----|---------|--------|-----------|
+| hidden_layers | 0-125 | 16384 | - | 20 | - |
+
+- **Prompts:** 23724
+- **Format version:** 2.0
+
+## Load with lmprobe
+
+```python
+from lmprobe import load_activations, Probe
+
+acts = load_activations("alliedtoasters/latenet-v0-activations-llama3.1-405b-base", layers=[0])
+probe = Probe(classifier="logistic_regression", random_state=42)
+probe.fit_from_activations(acts[0], labels)
+```
+
+## Load without lmprobe (standalone)
+
+```python
+import json
+import pyarrow.parquet as pq
+from safetensors import safe_open
+
+# Load the index — all metadata is embedded in the Parquet schema
+table = pq.read_table("index/train-00000-of-00001.parquet")
+df = table.to_pandas()
+meta = json.loads(table.schema.metadata[b"lmprobe:tensors"])
+
+# Get layer 0 activation for prompt 0
+row = df.iloc[0]
+pattern = meta["hidden_layers"]["file_pattern"]
+path = pattern.format(layer=0, shard=row["shard_index"])
+with safe_open(path, framework="pt") as f:
+    vec = f.get_tensor("hidden.layer_0")[row["row_offset"]]
+    # vec.shape: (16384,)
+```
+
+> **Full-sequence dataset:** The `shard_index` / `row_offset` columns always address the **last-token** pooled vector. For per-token access, use the `token_shard_ids` and `token_shard_offsets` list columns — see the `lmprobe:tensors` schema metadata for details.
+
+## Load with HF Datasets
+
+```python
+from datasets import load_dataset
+
+# Shows prompt text + labels in Dataset Viewer
+ds = load_dataset("alliedtoasters/latenet-v0-activations-llama3.1-405b-base")
+print(ds["train"][0])  # {"text": "...", "label": ..., ...}
+```
+
+## Provenance
+
+- **lmprobe version:** 0.9.2
+- **Extraction backend:** local
+- **Created:** 2026-04-04T16:35:14.904340+00:00
+- **PyTorch:** 2.11.0+cu130
+- **Transformers:** 5.4.0

index/train-00000-of-00001.parquet

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