Trying AutoProcessor for /home/fullofcaffeine/.cache/huggingface/hub/models--mlabonne--Meta-Llama-3.1-8B-Instruct-abliterated/snapshots/368c8ed94ce4c986e7b9ca5c159651ef753908ce Error processing tensor for shard Shard(model_id='mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated', start_layer=0, end...
This article codes the self-attention mechanisms used in transformer architectures and large language models (LLMs) such as GPT-4 and Llama from scratch in PyTorch.
The “magic” with the above code happens thanks to: model = DataParallel(model): the LLM model is wrapped with the methodDataParallel(), parallelizes the model across multiple GPUs. This means that the input data will be split and processed in parallel by different GPUs, speeding up the tr...
llm:model_type:llamamodel_path:./models/llama-2-7b-chat.ggmlv3.q3_K_L.bin#We recommend to predownload the files, but you can provide download URLs that will be used if the files are not present:model_download:https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/resolve/main/llama-...
embedding=GPT4AllEmbeddings(), ) retriever = vectorstore.as_retriever() ### Retrieval Grader from langchain.prompts import PromptTemplate from langchain_community.chat_models import ChatOllama from langchain_core.output_parsers import JsonOutputParser ...