A 32B experimental reasoning model for advanced text generation and robust instruction following. <metadata> gpu: A100 | collections: ["vLLM"] </metadata>

Smaug-72B topped the Hugging Face LLM leaderboard and it’s the first model with an average score of 80, making it the world’s best open-source foundation model. <metadata> gpu: A100 | collections: ["vLLM"] </metadata>

A distilled DeepSeek-R1 variant built on Qwen2.5-32B, fine-tuned with curated data for enhanced performance and efficiency. <metadata> gpu: A100 | collections: ["vLLM"] </metadata>

Generate novel text - novel finetuned from skt KoGPT2 base v2 - 한국어

A variant of the BART model designed specifically for natural language summarization. It was pre-trained on a large corpus of English text and later fine-tuned on the CNN/Daily Mail dataset. <metadata> gpu: T4 | collections: ["HF Transformers"] </metadata>

A GPTQ‑quantized version of Eric Hartford’s Dolphin 2.5 Mixtral 8x7B model, fine‑tuned for coding and conversational tasks. <metadata> gpu: A100 | collections: ["vLLM","GPTQ"] </metadata>

A quantized model fine-tuned for rapid, efficient, and robust conversational and instruction tasks. <metadata> gpu: A100 | collections: ["vLLM"] </metadata>

In this notebook, I'll construct a character-level LSTM with PyTorch. The network will train character by character on some text, then generate new text character by character. As an example, I will train on Anna Karenina. This model will be able to generate new text based on the text from the book!

A 7B autoregressive language model by Mistral AI, optimized for efficient text generation and robust reasoning. <metadata> gpu: A100 | collections: ["vLLM"] </metadata>

A GPTQ-quantized variant of the Mixtral 8x7B model, fine-tuned for efficient text generation and conversational applications. <metadata> gpu: A100 | collections: ["vLLM","GPTQ"] </metadata>

A robust 8B parameter base model for diverse language tasks, offering strong performance in multilingual scenarios. <metadata> gpu: A100 | collections: ["vLLM"] </metadata>

35B model delivering high performance in reasoning, summarization, and question answering. <metadata> gpu: A100 | collections: ["HF Transformers"] </metadata>

Deploy GGUF quantized version of Tinyllama-1.1B GGUF vLLM for efficient inference. <metadata> gpu: A100 | collections: ["Using NFS Volumes", "vLLM"] </metadata>

Implementing Hidden MarkovModel to generate new text and complete sentences

Shopify AI blogger. Generate blog posts with ChatGPT!

Advanced multimodal language model developed by Mistral AI with enhanced text performance, robust vision capabilities, and an expanded context window of up to 128,000 tokens. <metadata> gpu: A100 | collections: ["HF Transformers"] </metadata>

A fine-tuned, conversational variant of the Llama3-70B model. It uses Direct Preference Optimization (DPO) with the UltraFeedback dataset for alignment and is optimized for multi-turn chat interactions. <metadata> gpu: A100 | collections: ["HF Transformers"] </metadata>

A 7B parameter model fine-tuned for dialogue, utilizing supervised learning and RLHF, supports a context length of up to 4,000 tokens. <metadata> gpu: A10 | collections: ["HF Transformers"] </metadata>

2B instruct-tuned model for delivering coherent and instruction-following responses across a wide range of tasks. <metadata> gpu: A100 | collections: ["vLLM"] </metadata>

A chat model fine-tuned on TinyLlama, a compact 1.1B Llama model pretrained on 3 trillion tokens. <metadata> gpu: T4 | collections: ["vLLM"] </metadata>