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Showing 11 open source projects for "python instruction"
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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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Chinese-LLaMA-Alpaca-2 v2.0
Chinese LLaMA & Alpaca large language model + local CPU/GPU training
This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which... -
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Chinese-LLaMA-Alpaca 2
Chinese LLaMA-2 & Alpaca-2 Large Model Phase II Project
This project is developed based on the commercially available large model Llama-2 released by Meta. It is the second phase of the Chinese LLaMA&Alpaca large model project. The Chinese LLaMA-2 base model and the Alpaca-2 instruction fine-tuning large model are open-sourced. These models expand and optimize the Chinese vocabulary on the basis of the original Llama-2, use large-scale Chinese data for incremental pre-training, and further improve the basic semantics and command understanding... -
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Janus-Pro
Janus-Series: Unified Multimodal Understanding and Generation Models
Janus is a cutting-edge, unified multimodal model designed to advance both multimodal understanding and generation. It features a decoupled visual encoding approach that allows it to handle visual tasks separately from the generative tasks, resulting in enhanced flexibility and performance. With a singular transformer architecture, Janus outperforms previous models by surpassing specialized task-specific models in its ability to handle diverse multimodal inputs and generate high-quality... -
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GLM-4-32B-0414
Open Multilingual Multimodal Chat LMs
... with reinforcement learning and human preference alignment for improved instruction-following and function calling. Variants like GLM-Z1-32B-0414 offer deep reasoning and advanced mathematical problem-solving, while GLM-Z1-Rumination-32B-0414 specializes in long-form, complex research-style writing using scaled reinforcement learning and external search tools. Despite its large capacity, the model supports user-friendly local deployment and efficient fine-tuning with available scripts. -
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Meta-Llama-3-8B-Instruct
Instruction-tuned 8B LLM by Meta for helpful, safe English dialogue
Meta-Llama-3-8B-Instruct is an instruction-tuned large language model from Meta’s Llama 3 family, optimized for safe and helpful English dialogue. It uses an autoregressive transformer architecture with Grouped-Query Attention (GQA) and supports an 8k token context length. Fine-tuned using supervised learning and reinforcement learning with human feedback (RLHF), the model achieves strong results on benchmarks like MMLU, GSM8K, and HumanEval. Trained on over 15 trillion tokens of publicly... -
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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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Mistral-7B-Instruct-v0.2
Instruction-tuned 7B model for chat and task-oriented text generation
Mistral-7B-Instruct-v0.2 is a fine-tuned version of the Mistral-7B-v0.2 language model, designed specifically for following instructions in a conversational format. It supports a 32k token context window, enabling more detailed and longer interactions compared to its predecessor. The model is trained to respond to user prompts formatted with [INST] and [/INST] tags, and it performs well in instruction-following tasks like Q&A, summarization, and explanations. It can be used via the official... -
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Llama-3.1-8B-Instruct
Multilingual 8B-parameter chat-optimized LLM fine-tuned by Meta
Llama-3.1-8B-Instruct is a multilingual, instruction-tuned language model developed by Meta, designed for high-quality dialogue generation across eight languages, including English, Spanish, French, German, Italian, Portuguese, Hindi, and Thai. It uses a transformer-based, autoregressive architecture with Grouped-Query Attention and supports a 128k token context window. The model was fine-tuned using a combination of supervised fine-tuning (SFT), reinforcement learning with human feedback (RLHF... -
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Llama-3.3-70B-Instruct
Llama-3.3-70B-Instruct is a multilingual AI optimized for helpful chat
Llama-3.3-70B-Instruct is Meta's large, instruction-tuned language model designed for safe, multilingual, assistant-style conversations and text generation. With 70 billion parameters, it supports English, Spanish, French, German, Italian, Portuguese, Hindi, and Thai, offering state-of-the-art performance across a wide range of benchmarks including MMLU, HumanEval, and GPQA. The model is built on a transformer architecture with grouped-query attention, trained on over 15 trillion tokens... -
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starcoder
Code generation model trained on 80+ languages with FIM support
... natural language. While it is not an instruction-tuned model, it can act as a capable technical assistant when prompted appropriately. Developers can use it for general-purpose code generation, with fine control over prefix/middle/suffix tokens. The model has some limitations: generated code may contain bugs or licensing constraints, and attribution must be observed when output resembles training data. StarCoder is licensed under the BigCode OpenRAIL-M license.
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