LLMmap
Provides a ready-to-use pretrained model for open-set inference with PyTorch weights, configuration file, and behavioral templates.
GraphCanon updated 3w · GitHub synced 3w
Decision brief
LLMmap is a Python-based tool for quick inference using pretrained models without needing additional training. It includes PyTorch weights, configuration files, and behavioral templates tailored to 52 different LLMs.
Good fit when
- When you need immediate model deployment and don't want or can’t afford the time to train a custom model.
- For interactive applications where rapid setup with minimal code改动 is required because it provides preconfigured models.
Avoid when
- If your application requires fine-tuning on specific datasets as LLMmap offers only generic pretrained models without out-of-the-box support for further training.
- In scenarios needing advanced customization beyond the provided behavioral templates, since LLMmap’s framework might not accommodate extensive model modifications.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (376d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- 32 low (32 low)
- As of 1mo
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Install
pip install LLMmapSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
LLMmap is a Python-based tool that allows users to perform inference using a pretrained model without additional training. It supports both interactive and programmatic use cases.
Capability facts
- Languages
- python
Source: github.language · Aug 5, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 5, 2026)
Recommended: ```Python 3.11```Source link
Tags
README
Requirements
Recommended: Python 3.11
pip install -r requirements.txt
⚡ Quick Start -- Using the Pretrained Model
We provide a ready-to-use open-set inference model located at:
./data/pretrained_models/default
This model includes:
- Trained PyTorch weights
- Configuration file
- Behavioral templates for 52 LLMs
You can use it directly without any training, either interactively or programmatically.
✅ A. Use in Python Code You can load and query the model in your own Python pipeline:
from LLMmap.inference import load_LLMmap
---
### 2. Quick Start Command
python make_dataset.py
my_custom_dataset
./confs/LLMs/example.json
./confs/queries/default.json
--num_prompt_conf_train 150
--num_prompt_conf_test 20
--prompt_conf_path ./confs/prompt_configurations
--dataset_root ./data/datasets
--overwrite
This will produce ./data/datasets/my_custom_dataset.jsonl.
⸻
For agents
This page has a .md twin and JSON over the API.