The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
ip: string
models: string
response_ms: double
verified_at: double
-- schema metadata --
huggingface: '{"info": {"features": {"ip": {"dtype": "string", "_type": "' + 169
to
{'ip': Value('string'), 'model': Value('string'), 'tags': Value('string'), 'raw': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 209, in _generate_tables
yield Key(file_idx, batch_idx), self._cast_table(pa_table)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 147, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
ip: string
models: string
response_ms: double
verified_at: double
-- schema metadata --
huggingface: '{"info": {"features": {"ip": {"dtype": "string", "_type": "' + 169
to
{'ip': Value('string'), 'model': Value('string'), 'tags': Value('string'), 'raw': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
🛰️ Ollama Hosts Index (Latterworks)
A registry of reachable Ollama model endpoints scraped from the wild. This dataset contains 936 IP:PORT entries—mostly on port 11434—with raw /api/tags payloads included for inspection or parsing.
✨ Fields
ip: Host address, typically of the formIP_PORT(e.g.,45.41.94.28_11434)model: Extracted model name, e.g.,llama3:8b-instruct-q5_K_M(currently null, see note)tags: Optional user-provided tags (mostly empty)raw: Full JSON from/api/tags, includes model list and metadata (size, digest, quantization, etc.)
⚠️ Note on model field
The model column is currently null because parsing was deferred—but the model metadata is present inside the raw field. Most raw values are structured as:
{
"models": [
{
"name": "llama3.2:latest",
"model": "llama3.2:latest",
"modified_at": "2025-05-17T22:58:10.122Z",
...
}
]
}
To extract, parse raw as JSON and access .models[0].model.
📦 Example Use
import pandas as pd
import json
df = pd.read_parquet("data/train-00000-of-00001.parquet")
# Extract IP + first model name
df['parsed_model'] = df['raw'].apply(lambda r: json.loads(r).get("models", [{}])[0].get("model", None))
print(df[['ip', 'parsed_model']].dropna().head())
🔌 Connecting to Hosts
If a host is online, you can ping it with:
curl http://<IP>:11434/api/tags
Example:
curl http://45.41.94.28:11434/api/tags
Returns:
{"models":[{"name":"llama3.2:latest",...}]}
🛠️ Attribution
Collected by [latterworks] using passive scanning and broadcast Ollama introspection.
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