LLaMA: Open and Efficient Foundation Language Models 27 Feb 2023 57,772 Atom of Thoughts for Markov LLM Test-Time Scaling 17 Feb 2025 48,610 Data Interpreter: An LLM Agent For Data Science 28 Feb 2024 48,610 AFlow: Automating Agentic Workflow Generation 14 Oct 2024 48,610 Autonomous Data ...
Llama 2 Chat can generate and explain Python code quite well, right out of the box. Code Llama’s fine-tuned models offer even better capabilities for code generation.
COMPLETION_MODEL=groq/deepseek-r1-distill-llama-70b auto main OpenAI-Compatible Endpoints (e.g., Grok) set the OPENAI_API_KEY in the .env file. OPENAI_API_KEY=your_api_key_for_openai_compatible_endpoints run the following command to start Auto-Deep-Research. COMPLETION_MODEL=openai/grok-2...
In the new paper Interactive Code Generation via Test-Driven User-Intent Formalization, a team from Microsoft Research, the University of Pennsylvania, and the University of California, San Diego proposes a workflow for test-driven user-intent formalization that leverages user feedback to generate co...
hiyouga/llama-factory • • 31 Jul 2024 Based on our observations and the rationale about attention-based model dynamics, we propose a negative attention score (NAS) to systematically and quantitatively formulate negative bias. parameter-efficient fine-tuning 42...
“It’s the first time that machine-learning models have been really useful for a lot of people,” says Gabriel Synnaeve, who led the team behind Code Llama at Meta. “It’s not just nerding out—it’s actually useful.” With Microsoft and Google about to stir similar...
This model took my request for tests a little more seriously, and demonstrated how to use the Python Unit Test module. I wondered how different the output of the Python-tuned Code Llama 7B model would be: martinheller@Martins-M1-MBP ~ %ollama run codellama:7b-pythonpulling manifest ...
使用了 LLaMA Factory 的项目 协议 引用 致谢 项目特色 多种模型:LLaMA、LLaVA、Mistral、Mixtral-MoE、Qwen、Qwen2-VL、Yi、Gemma、Baichuan、ChatGLM、Phi 等等。 集成方法:(增量)预训练、(多模态)指令监督微调、奖励模型训练、PPO 训练、DPO 训练、KTO 训练、ORPO 训练等等。
from typing import Optional import fire from llama import Llama def main( ckpt_dir: str, tokenizer_path: str, temperature: float = 0.2, top_p: float = 0.95, max_seq_len: int = 512, max_batch_size: int = 8, max_gen_len: Optional[int] = None, ): generator = Llama.build( ckpt...
, "operationId": "UpdateUser", "parameters": [ { "$ref": "#/parameters/IdInPath" } ], "responses": { "201": { "description": "Accepted", "schema": { "$ref": "#/definitions/UserResponse" } } }, "deprecated": false, "x-ms-no-generic-test": true } }, }, // definitions...