diff --git a/3p-integrations/aws/getting_started_llama_3_on_amazon_bedrock.ipynb b/3p-integrations/aws/getting_started_llama_3_on_amazon_bedrock.ipynb index b84ae9e55..1a3d07f98 100644 --- a/3p-integrations/aws/getting_started_llama_3_on_amazon_bedrock.ipynb +++ b/3p-integrations/aws/getting_started_llama_3_on_amazon_bedrock.ipynb @@ -8,8 +8,7 @@ "source": [ "# Using Amazon Bedrock with Llama\n", "\n", - "Open this notebook in \"Open\n", - "\n", + "\"Open\n", "\n", "Use this notebook to quickly get started with Llama on Bedrock. You can access the Amazon Bedrock API using the AWS Python SDK.\n", "\n", diff --git a/3p-integrations/aws/prompt_engineering_with_llama_2_on_amazon_bedrock.ipynb b/3p-integrations/aws/prompt_engineering_with_llama_2_on_amazon_bedrock.ipynb index df8b61126..23d71253f 100644 --- a/3p-integrations/aws/prompt_engineering_with_llama_2_on_amazon_bedrock.ipynb +++ b/3p-integrations/aws/prompt_engineering_with_llama_2_on_amazon_bedrock.ipynb @@ -7,8 +7,7 @@ "source": [ "# Prompt Engineering with Llama 2 - Using Amazon Bedrock + LangChain\n", "\n", - "Open this notebook in \"Open\n", - "\n", + "\"Open\n", "\n", "Prompt engineering is using natural language to produce a desired response from a large language model (LLM).\n", "\n", diff --git a/3p-integrations/aws/react_llama_3_bedrock_wk.ipynb b/3p-integrations/aws/react_llama_3_bedrock_wk.ipynb index 2e4245ed6..67117adf8 100644 --- a/3p-integrations/aws/react_llama_3_bedrock_wk.ipynb +++ b/3p-integrations/aws/react_llama_3_bedrock_wk.ipynb @@ -7,7 +7,7 @@ "# Advanced Techniques\n", "## 1. ReAct\n", "\n", - "Open this notebook in \"Open\n", + "\"Open\n", "\n", "LLMs abilities for reasoning (e.g. chain-of-thought CoT prompting) and acting have primarily been studied as separate topics. **ReAct** [Shunyu Yao et al. ICLR 2023](https://arxiv.org/pdf/2210.03629.pdf) (Reason and Act) is a method to generate both reasoning traces and task-specific actions in an interleaved manner.\n", "\n", diff --git a/3p-integrations/e2b-ai-analyst/README.md b/3p-integrations/e2b-ai-analyst/README.md index 9d519ae59..9e793076f 100644 --- a/3p-integrations/e2b-ai-analyst/README.md +++ b/3p-integrations/e2b-ai-analyst/README.md @@ -1,8 +1,6 @@ # AI Analyst with Llama and E2B This is an AI-powered code and data analysis tool powered by Meta Llama and the [E2B SDK](https://e2b.dev/docs). -![Preview](https://private-user-images.githubusercontent.com/33395784/382129362-3bc8b017-4a09-416c-b55c-ce53da7e5560.gif?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.Kaab1leGbgBiQhfh6bV1VHTc8QfinP7ufqwmn7Ra57c) - → Try on [ai-analyst.e2b.dev](https://ai-analyst.e2b.dev/) ## Features @@ -54,4 +52,4 @@ In `.env.local`, add an API key for at least one LLM provider: For Ollama, provide the base URL instead of the API key: -- Ollama: `OLLAMA_BASE_URL` \ No newline at end of file +- Ollama: `OLLAMA_BASE_URL` diff --git a/3p-integrations/groq/llama3_cookbook_groq.ipynb b/3p-integrations/groq/llama3_cookbook_groq.ipynb index 6b5ba785d..5556e1f47 100644 --- a/3p-integrations/groq/llama3_cookbook_groq.ipynb +++ b/3p-integrations/groq/llama3_cookbook_groq.ipynb @@ -7,7 +7,8 @@ "source": [ "# Llama 3 Cookbook with LlamaIndex and Groq\n", "\n", - "\"Open\n", + "\"Open\n", + "\n", "\n", "Meta developed and released the Meta [Llama 3](https://ai.meta.com/blog/meta-llama-3/) family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks.\n", "\n", diff --git a/3p-integrations/langchain/langgraph_rag_agent.ipynb b/3p-integrations/langchain/langgraph_rag_agent.ipynb index 1cf10c434..aa6940627 100644 --- a/3p-integrations/langchain/langgraph_rag_agent.ipynb +++ b/3p-integrations/langchain/langgraph_rag_agent.ipynb @@ -5,7 +5,7 @@ "id": "6912ab05-f66a-40a9-a4a5-4deb80d2e0d9", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/3p-integrations/langchain/langgraph_rag_agent_local.ipynb b/3p-integrations/langchain/langgraph_rag_agent_local.ipynb index 1f322fa9f..38617ac4b 100644 --- a/3p-integrations/langchain/langgraph_rag_agent_local.ipynb +++ b/3p-integrations/langchain/langgraph_rag_agent_local.ipynb @@ -5,7 +5,7 @@ "id": "1f53f753-12c6-4fac-b910-6e96677d8a49", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/3p-integrations/langchain/langgraph_tool_calling_agent.ipynb b/3p-integrations/langchain/langgraph_tool_calling_agent.ipynb index c9fb71edb..882f73812 100644 --- a/3p-integrations/langchain/langgraph_tool_calling_agent.ipynb +++ b/3p-integrations/langchain/langgraph_tool_calling_agent.ipynb @@ -5,7 +5,7 @@ "id": "8ac4ba3b-c438-4f2e-8f52-39846beb5642", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L2_Tool_Calling.ipynb b/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L2_Tool_Calling.ipynb index 4aec4d415..8b5632ef0 100644 --- a/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L2_Tool_Calling.ipynb +++ b/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L2_Tool_Calling.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "\"Open\n", + "\"Open\n", "\n", "This notebook ports the DeepLearning.AI short course [Building Agentic RAG with Llamaindex Lesson 2 Tool Calling](https://learn.deeplearning.ai/courses/building-agentic-rag-with-llamaindex/lesson/3/tool-calling) to using Llama 3. It shows how to use Llama 3 to not only pick a function to execute, but also infer an argument to pass through the function.\n", "\n", diff --git a/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L3_Building_an_Agent_Reasoning_Loop.ipynb b/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L3_Building_an_Agent_Reasoning_Loop.ipynb index c4d9c6944..2e2c426b4 100644 --- a/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L3_Building_an_Agent_Reasoning_Loop.ipynb +++ b/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L3_Building_an_Agent_Reasoning_Loop.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "\"Open\n", + "\"Open\n", "\n", "This notebook ports the DeepLearning.AI short course [Building Agentic RAG with Llamaindex Lesson 3 Building an Agent Reasoning Loop](https://learn.deeplearning.ai/courses/building-agentic-rag-with-llamaindex/lesson/4/building-an-agent-reasoning-loop) to using Llama 3. It shows how to define a complete agent reasoning loop to reason over tools and multiple steps on a complex question the user asks about a single document while maintaining memory.\n", "\n", diff --git a/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L4_Building_a_Multi-Document_Agent.ipynb b/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L4_Building_a_Multi-Document_Agent.ipynb index 38c3ba07d..88099daee 100644 --- a/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L4_Building_a_Multi-Document_Agent.ipynb +++ b/3p-integrations/llamaindex/dlai_agentic_rag/Building_Agentic_RAG_with_Llamaindex_L4_Building_a_Multi-Document_Agent.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "\"Open\n", + "\"Open\n", "\n", "This notebook ports the DeepLearning.AI short course [Building Agentic RAG with Llamaindex Lesson 4 Building a Multi-Document Agent](https://learn.deeplearning.ai/courses/building-agentic-rag-with-llamaindex/lesson/5/building-a-multi-document-agent) to using Llama 3. It shows how to use an agent to handle multiple documents and increasing degrees of complexity.\n", "\n", diff --git a/3p-integrations/togetherai/knowledge_graphs_with_structured_outputs.ipynb b/3p-integrations/togetherai/knowledge_graphs_with_structured_outputs.ipynb index fb153fab6..c6dbcb0ff 100644 --- a/3p-integrations/togetherai/knowledge_graphs_with_structured_outputs.ipynb +++ b/3p-integrations/togetherai/knowledge_graphs_with_structured_outputs.ipynb @@ -5,7 +5,7 @@ "metadata": {}, "source": [ "# Generating Knowledge Graphs with LLMs and Structured Outputs\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-llama/llama-recipes/blob/main/recipes/3p_integrations/togetherai/knowledge_graphs_with_structured_outputs.ipynb)" + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-llama/llama-cookbook/blob/main/3p-integrations/togetherai/knowledge_graphs_with_structured_outputs.ipynb)" ] }, { @@ -30,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -38,52 +38,7 @@ "id": "DFAjay1FZVrn", "outputId": "d4b17b31-c125-4de5-ad54-6d4d08d81eaa" }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: together in /Users/jeffxtang/anaconda3/envs/llama-recipes/lib/python3.10/site-packages (1.3.3)\n", - "Requirement already satisfied: aiohttp<4.0.0,>=3.9.3 in /Users/jeffxtang/anaconda3/envs/llama-recipes/lib/python3.10/site-packages (from together) (3.10.10)\n", - "Requirement already satisfied: click<9.0.0,>=8.1.7 in /Users/jeffxtang/anaconda3/envs/llama-recipes/lib/python3.10/site-packages (from together) (8.1.7)\n", - "Requirement already satisfied: eval-type-backport<0.3.0,>=0.1.3 in /Users/jeffxtang/anaconda3/envs/llama-recipes/lib/python3.10/site-packages (from together) (0.2.0)\n", - "Requirement already satisfied: filelock<4.0.0,>=3.13.1 in /Users/jeffxtang/anaconda3/envs/llama-recipes/lib/python3.10/site-packages (from together) (3.16.1)\n", - 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"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-llama/llama-recipes/blob/main/recipes/3p_integrations/togetherai/pdf_to_podcast_using_llama_on_together.ipynb)" + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-llama/llama-cookbook/blob/main/3p-integrations/togetherai/pdf_to_podcast_using_llama_on_together.ipynb)" ] }, { diff --git a/README.md b/README.md index 207364c50..f13fdc139 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,7 @@ This repository covers the most popular community approaches, use-cases and the > * [Text to SQL](./end-to-end-use-cases/coding/text2sql/) -> Note: We recently did a refactor of the repo, [archive-main](https://github.com/meta-llama/llama-recipes/tree/archive-main) is a snapshot branch from before the refactor +> Note: We recently did a refactor of the repo, [archive-main](https://github.com/meta-llama/llama-cookbook/tree/archive-main) is a snapshot branch from before the refactor ## Repository Structure: @@ -44,7 +44,7 @@ A: Checkout the Fine-Tuning FAQ [here](./src/docs/) - Q: Some links are broken/folders are missing: -A: We recently did a refactor of the repo, [archive-main](https://github.com/meta-llama/llama-recipes/tree/archive-main) is a snapshot branch from before the refactor +A: We recently did a refactor of the repo, [archive-main](https://github.com/meta-llama/llama-cookbook/tree/archive-main) is a snapshot branch from before the refactor - Where can we find details about the latest models? diff --git a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agentic_Design_Patterns_with_AutoGen_L4_Tool_Use_and_Conversational_Chess.ipynb b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agentic_Design_Patterns_with_AutoGen_L4_Tool_Use_and_Conversational_Chess.ipynb index d692ef744..507e0ac8c 100644 --- a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agentic_Design_Patterns_with_AutoGen_L4_Tool_Use_and_Conversational_Chess.ipynb +++ b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agentic_Design_Patterns_with_AutoGen_L4_Tool_Use_and_Conversational_Chess.ipynb @@ -5,7 +5,7 @@ "id": "7a4b75bb-d60a-41e3-abca-1ca0f0bf1201", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agents_in_LangGraph_L1_Build_an_Agent_from_Scratch.ipynb b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agents_in_LangGraph_L1_Build_an_Agent_from_Scratch.ipynb index 7e7c834fd..b3809e278 100644 --- a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agents_in_LangGraph_L1_Build_an_Agent_from_Scratch.ipynb +++ b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/AI_Agents_in_LangGraph_L1_Build_an_Agent_from_Scratch.ipynb @@ -5,7 +5,7 @@ "id": "de56ee05-3b71-43c9-8cbf-6ad9b3233f38", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Building_Agentic_RAG_with_Llamaindex_L1_Router_Engine.ipynb b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Building_Agentic_RAG_with_Llamaindex_L1_Router_Engine.ipynb index 2e0ae2a9b..35e3e1d72 100644 --- a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Building_Agentic_RAG_with_Llamaindex_L1_Router_Engine.ipynb +++ b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Building_Agentic_RAG_with_Llamaindex_L1_Router_Engine.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Functions_Tools_and_Agents_with_LangChain_L1_Function_Calling.ipynb b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Functions_Tools_and_Agents_with_LangChain_L1_Function_Calling.ipynb index a8d521bfa..2dc0828ae 100644 --- a/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Functions_Tools_and_Agents_with_LangChain_L1_Function_Calling.ipynb +++ b/end-to-end-use-cases/agents/DeepLearningai_Course_Notebooks/Functions_Tools_and_Agents_with_LangChain_L1_Function_Calling.ipynb @@ -5,7 +5,7 @@ "id": "2ba1b4ef-3b96-4e7e-b5d0-155b839db73c", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/end-to-end-use-cases/coding/text2sql/quickstart.ipynb b/end-to-end-use-cases/coding/text2sql/quickstart.ipynb index 1bf90efca..89fe6b796 100644 --- a/end-to-end-use-cases/coding/text2sql/quickstart.ipynb +++ b/end-to-end-use-cases/coding/text2sql/quickstart.ipynb @@ -5,7 +5,7 @@ "id": "e8cba0b6", "metadata": {}, "source": [ - "\"Open \n", + "\"Open \n", "\n", "## Quick Demo of Text2SQL Using Llama 3.3\n", "\n", diff --git a/end-to-end-use-cases/live_data.ipynb b/end-to-end-use-cases/live_data.ipynb index 2eb198b58..38cfb5a0e 100644 --- a/end-to-end-use-cases/live_data.ipynb +++ b/end-to-end-use-cases/live_data.ipynb @@ -5,7 +5,7 @@ "id": "30eb1704-8d76-4bc9-9308-93243aeb69cb", "metadata": {}, "source": [ - "\"Open\n", + "\"Open\n", "\n", "## This demo app shows:\n", "* How to use LlamaIndex, an open source library to help you build custom data augmented LLM applications\n", diff --git a/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_customization_via_prompting_and_fine_tuning.ipynb b/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_customization_via_prompting_and_fine_tuning.ipynb index 6517d88c9..6f93abcb8 100644 --- a/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_customization_via_prompting_and_fine_tuning.ipynb +++ b/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_customization_via_prompting_and_fine_tuning.ipynb @@ -15,7 +15,7 @@ "source": [ "# Llama Guard 3 Customization: Taxonomy Customization, Zero/Few-shot prompting, Evaluation and Fine Tuning \n", "\n", - "\n", + "\n", " \"Open\n", "\n", "\n", diff --git a/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_text_and_vision_inference.ipynb b/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_text_and_vision_inference.ipynb index 7aa3a50ae..7b9a8753b 100644 --- a/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_text_and_vision_inference.ipynb +++ b/end-to-end-use-cases/responsible_ai/llama_guard/llama_guard_text_and_vision_inference.ipynb @@ -7,7 +7,7 @@ "source": [ "# Llama Guard 3 Text & Vision update\n", "\n", - "\"Open\n", + "\"Open\n", "\n", "In this notebook we show simple inference scripts using the [transformers](https://github.com/huggingface/transformers) library, from HuggingFace. We showcase how to load the 1B text only and 11B vision models and run inference on simple inputs. For details on the models, refer to their corresponding model cards:\n", "* [Llama Guard 3 1B](https://github.com/meta-llama/PurpleLlama/blob/main/Llama-Guard3/1B/MODEL_CARD.md)\n", diff --git a/end-to-end-use-cases/video_summary.ipynb b/end-to-end-use-cases/video_summary.ipynb index c2de08d05..ad5270bde 100644 --- a/end-to-end-use-cases/video_summary.ipynb +++ b/end-to-end-use-cases/video_summary.ipynb @@ -5,7 +5,7 @@ "id": "30b1235c-2f3e-4628-9c90-30385f741550", "metadata": {}, "source": [ - "\"Open\n", + "\"Open\n", "\n", "## This demo app shows:\n", "* How to use LangChain's YoutubeLoader to retrieve the caption in a YouTube video\n", diff --git a/getting-started/Prompt_Engineering_with_Llama.ipynb b/getting-started/Prompt_Engineering_with_Llama.ipynb index bab120bf7..cbe8c5d0e 100644 --- a/getting-started/Prompt_Engineering_with_Llama.ipynb +++ b/getting-started/Prompt_Engineering_with_Llama.ipynb @@ -5,7 +5,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "\"Open\n", + "\"Open\n", "\n", "# Prompt Engineering with Llama\n", "\n", diff --git a/getting-started/RAG/hello_llama_cloud.ipynb b/getting-started/RAG/hello_llama_cloud.ipynb index 2cd8ce2e7..164c521c1 100644 --- a/getting-started/RAG/hello_llama_cloud.ipynb +++ b/getting-started/RAG/hello_llama_cloud.ipynb @@ -5,7 +5,7 @@ "id": "1c1ea03a-cc69-45b0-80d3-664e48ca6831", "metadata": {}, "source": [ - "\"Open\n", + "\"Open\n", "\n", "## This demo app shows:\n", "* How to run Llama 3.1 in the cloud hosted on Replicate\n", @@ -37,7 +37,7 @@ "!pip install sentence-transformers\n", "!pip install faiss-cpu\n", "!pip install bs4\n", - "!pip install replicate", + "!pip install replicate\n", "!pip install langchain-community" ] }, diff --git a/getting-started/build_with_Llama_3_2.ipynb b/getting-started/build_with_Llama_3_2.ipynb index f50dbaa90..7e2acae42 100644 --- a/getting-started/build_with_Llama_3_2.ipynb +++ b/getting-started/build_with_Llama_3_2.ipynb @@ -5,7 +5,7 @@ "id": "42939a0f", "metadata": {}, "source": [ - "\"Open" + "\"Open" ] }, { diff --git a/getting-started/finetuning/quickstart_peft_finetuning.ipynb b/getting-started/finetuning/quickstart_peft_finetuning.ipynb index df2674d53..560cc1729 100644 --- a/getting-started/finetuning/quickstart_peft_finetuning.ipynb +++ b/getting-started/finetuning/quickstart_peft_finetuning.ipynb @@ -8,7 +8,7 @@ "Copyright (c) Meta Platforms, Inc. and affiliates.\n", "This software may be used and distributed according to the terms of the Llama 2 Community License Agreement.\n", "\n", - "\"Open" + "\"Open" ] }, { @@ -217,19 +217,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ubuntu/llama-recipes/src/llama_recipes/model_checkpointing/checkpoint_handler.py:17: DeprecationWarning: `torch.distributed._shard.checkpoint` will be deprecated, use `torch.distributed.checkpoint` instead\n", - " from torch.distributed._shard.checkpoint import (\n", - "Preprocessing dataset: 100%|██████████| 14732/14732 [00:02<00:00, 5872.02it/s]\n" - ] - } - ], + "outputs": [], "source": [ "from llama_recipes.configs.datasets import samsum_dataset\n", "from llama_recipes.utils.dataset_utils import get_dataloader\n", @@ -283,45 +273,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/ubuntu/llama-recipes/src/llama_recipes/utils/train_utils.py:92: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.\n", - " scaler = torch.cuda.amp.GradScaler()\n", - "/home/ubuntu/miniconda3/envs/llama/lib/python3.11/site-packages/torch/cuda/memory.py:343: FutureWarning: torch.cuda.reset_max_memory_allocated now calls torch.cuda.reset_peak_memory_stats, which resets /all/ peak memory stats.\n", - " warnings.warn(\n", - "Training Epoch: 1: 0%|\u001b[34m \u001b[0m| 0/319 [00:00