Search Results for "python web crawler"
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Showing 6 open source projects for "python web crawler"
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MedicalGPT
MedicalGPT: Training Your Own Medical GPT Model with ChatGPT Training
MedicalGPT training medical GPT model with ChatGPT training pipeline, implementation of Pretraining, Supervised Finetuning, Reward Modeling and Reinforcement Learning. MedicalGPT trains large medical models, including secondary pre-training, supervised fine-tuning, reward modeling, and reinforcement learning training. -
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ERNIE-4.5-300B-A47B-FP8-Paddle
ERNIE 4.5 MoE model in FP8 for efficient high-performance inference
.... It is especially well-suited for production environments requiring high throughput and lower memory use, while maintaining high reasoning and generation quality. The model can be used with FastDeploy and integrates cleanly with Python APIs for prompt-based generation workflows. It supports long context lengths (up to 131,072 tokens) and includes both Chinese and English prompt templates for web search applications. -
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phi-2
Small, high-performing language model for QA, chat, and code tasks
Phi-2 is a 2.7 billion parameter Transformer model developed by Microsoft, designed for natural language processing and code generation tasks. It was trained on a filtered dataset of high-quality web content and synthetic NLP texts created by GPT-3.5, totaling 1.4 trillion tokens. Phi-2 excels in benchmarks for common sense, language understanding, and logical reasoning, outperforming most models under 13B parameters despite not being instruction-tuned or aligned via RLHF. It performs best... -
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MiniMax-M1
Open-weight, large-scale hybrid-attention reasoning model
MiniMax-M1 is the world’s first open-weight, large-scale hybrid-attention reasoning model designed for long-context and complex reasoning tasks. Powered by a hybrid Mixture-of-Experts (MoE) architecture combined with a lightning attention mechanism, it efficiently supports context lengths up to 1 million tokens—eight times larger than many contemporary models. MiniMax-M1 significantly reduces computational overhead at generation time, consuming only about 25% FLOPs compared to comparable... -
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ControlNet
Extension for Stable Diffusion using edge, depth, pose, and more
ControlNet is a neural network architecture that enhances Stable Diffusion by enabling image generation conditioned on specific visual structures such as edges, poses, depth maps, and segmentation masks. By injecting these auxiliary inputs into the diffusion process, ControlNet gives users powerful control over the layout and composition of generated images while preserving the style and flexibility of generative models. It supports a wide range of conditioning types through pretrained... -
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GPT-2
GPT-2 is a 124M parameter English language model for text generation
GPT-2 is a pretrained transformer-based language model developed by OpenAI for generating natural language text. Trained on 40GB of internet data from outbound Reddit links (excluding Wikipedia), it uses causal language modeling to predict the next token in a sequence. The model was trained without human labels and learns representations of English that support text generation, feature extraction, and fine-tuning. GPT-2 uses a byte-level BPE tokenizer with a vocabulary of 50,257 and handles...
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