A framework for few-shot evaluation of language models.
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Updated
Jun 12, 2024 - Python
A framework for few-shot evaluation of language models.
Open language modeling toolkit based on PyTorch
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
Universal LLM Deployment Engine with ML Compilation
An animal can do training and inference every day of its existence until the day of its death. A forward pass is all you need.
Unify Efficient Fine-Tuning of 100+ LLMs
GPT-powered chat for documentation, chat with your documents
Build AI-powered applications with React, Svelte, Vue, and Solid
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
A Python client for Aeca database
MINERS ⛏️: The semantic retrieval benchmark for evaluating multilingual language models.
RuTaBERT is a model solving the problem of Column Type Annotation with pre-trained large language model (BERT), trained on the Russian corpus.
InternLM-XComposer2 is a groundbreaking vision-language large model (VLLM) excelling in free-form text-image composition and comprehension.
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
“通慧智教”-大模型赋能智能教学网站-通过虚拟教学助理,使用语音或文本,以自然语言方式与网站交互。
Tiny and simple implementation of multimodal models
DafnyBench: A Benchmark for Formal Software Verification
Implementation of the LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens Paper
A curated list for Efficient Large Language Models
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