yandex/YaLM-100B

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

3757 stars · 290 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

YaLM-100B is a GPT-like pretrained language model with 100 billion parameters, trained by Yandex on English and Russian text using DeepSpeed and Megatron-LM-style infrastructure. The repository provides inference code, download scripts, and Docker tooling for running the model on multi-GPU setups with roughly 200GB of GPU memory.

Use cases

• generate text with a large open language model
• run a 100B parameter GPT model on multiple GPUs
• do few-shot text generation in English and Russian
• download and deploy pretrained LLM weights locally
• experiment with conditional sampling and greedy decoding
• study training practices for large language models

When to choose

• you need a large open-weight GPT-style model, especially with strong Russian-language capability
• you have a multi-GPU cluster (~200GB VRAM) and want to run inference locally
• you want to study or reproduce large-scale LLM training with DeepSpeed

When to avoid

• you lack access to high-end GPUs or 200GB of disk space
• you need a small, lightweight model for CPU or single-GPU inference
• you need actively maintained code - the repo is a stock DeepSpeed example with minimal changes and updates have stalled

Facets

library · maturity maintenance

llm-inference llm-training machine-learning deep-learning large-language-models deep-learning artificial-intelligence python gpt-like 100b-parameters multilingual english-russian deepspeed megatron-lm tensor-parallelism text-generation pretrained-model yandex natural-language-processing gpu docker linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="yandex/YaLM-100B")