# allenai/bilm-tf

Tensorflow implementation of contextualized word representations from bi-directional language models

Repository: https://github.com/allenai/bilm-tf
Canonical: https://ross.abutalabs.com/products/bilm-tf
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2023-03-04T16:01:44+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3260, "days_push": 1278, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1612, forks 447 (observed 2026-08-28T04:05:11.077366+00:00)

## What it is
A TensorFlow implementation of the bidirectional language model (biLM) used to compute ELMo deep contextualized word representations. It supports both training new biLMs and running pre-trained models to produce contextual embeddings for downstream NLP tasks.

## Use cases
- compute ELMo embeddings for text in TensorFlow
- train a bidirectional language model on my own corpus
- get contextualized word representations for a downstream NLP model
- precompute ELMo vectors for a fixed dataset
- use pretrained ELMo weights for prediction

## When to choose
- you need ELMo embeddings specifically in TensorFlow 1.x
- you want to train or fine-tune a bidirectional LM from the ELMo paper
- you need character-level input handling for arbitrary text

## When to avoid
- you want modern transformer embeddings like BERT or GPT
- you use TensorFlow 2.x or PyTorch (prefer TensorFlow Hub or AllenNLP)
- you need actively maintained software with recent dependency support

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, nlp, llm-training
- domain: machine-learning, deep-learning
- platform: python
- tags: elmo, embeddings, language-models, tensorflow, word-representations, bilstm, natural-language-processing, linux, gpu

## Member repositories
- allenai/bilm-tf (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:11.077366+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:51:08.945068+00:00, confidence not recorded.
  - readme: https://github.com/allenai/bilm-tf (fetched 2026-08-28T04:05:11.077366+00:00, sha fee75abed903)
- Data as of 2026-08-30T08:39:29.467469+00:00.