id stringlengths 7 11 | source stringclasses 1
value | category stringclasses 11
values | title stringlengths 15 214 | text stringlengths 70 30.5k | url stringlengths 57 160 | tags stringlengths 3 113 | created_at int64 1.22B 1.79B |
|---|---|---|---|---|---|---|---|
se_78015787 | stackoverflow | ARTIFICIAL_INTELLIGENCE | AttributeError: 'Collection' object has no attribute '__pydantic_private__'. Did you mean: '__pydantic_complete__'? | AttributeError: 'Collection' object has no attribute '__pydantic_private__'. Did you mean: '__pydantic_complete__'?
I am trying to create pdf chat using open source LLM. I get the below error when I run ingest.py
(my_venv) PS C:\GithubRepository\Chat-with-PDF-Chatbot> python ingest.py ... | https://stackoverflow.com/questions/78015787/attributeerror-collection-object-has-no-attribute-pydantic-private-did | python, pydantic, large-language-model, chromadb, pydantic-settings | 1,708,260,386 |
se_78885166 | stackoverflow | ARTIFICIAL_INTELLIGENCE | LangChain failure with long input texts | LangChain failure with long input texts
I am working with LangChain's LLMChain to process large documents. I see quite some problems when the input text exceeds the token limit of the language model. For long input text, it has significant slowdowns and can even sometimes fail due to overflow of tokens.
This is the sa... | https://stackoverflow.com/questions/78885166/langchain-failure-with-long-input-texts | python, openai-api, langchain, large-language-model, chatgpt-api | 1,723,999,560 |
se_78886747 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Langchain SQLDatabaseChain error due to SQL formatting | Langchain SQLDatabaseChain error due to SQL formatting
import os
from dotenv import load_dotenv
load_dotenv()
import google.generativeai as genai
from langchain_google_genai import GoogleGenerativeAI
# Ensure your GOOGLE_API_KEY is set in the .env file
api_key = os.getenv("GEMINI_API_KEY")
# Use GoogleGenerativeAI... | https://stackoverflow.com/questions/78886747/langchain-sqldatabasechain-error-due-to-sql-formatting | python, google-bigquery, chatbot, langchain, large-language-model | 1,724,052,304 |
se_78883642 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Llama3-8b-instruct returns value of "None" when using with_structure_output whereas Llama3-405b succeeds | Llama3-8b-instruct returns value of "None" when using with_structure_output whereas Llama3-405b succeeds
Comparing two of the Llama3 models, 8b and 405b.
8b I can load locally with docker.
405b is cloud-based. This should present no issues other than the model's capacity to answer questions.
I think I hit t... | https://stackoverflow.com/questions/78883642/llama3-8b-instruct-returns-value-of-none-when-using-with-structure-output-wher | langchain, large-language-model, llama | 1,723,949,243 |
se_78760514 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Preparing text data for raft implementation | Preparing text data for raft implementation
I want to use Raft Retrieval Augmented Fine Tuning to build a smart chatbot. My data consists of scraped text from multiple websites. Should I transform it all to QAD format? If so, is there a way to do it automatically?
considering that my dataset is very large and doing it... | https://stackoverflow.com/questions/78760514/preparing-text-data-for-raft-implementation | web-scraping, large-language-model, rag | 1,721,231,818 |
se_77909589 | stackoverflow | ARTIFICIAL_INTELLIGENCE | ValueError: You cannot perform fine-tuning on purely quantized models | ValueError: You cannot perform fine-tuning on purely quantized models
When trying to finetune a falcon 7b model on some training data of mine I am getting the following error:
ValueError: You cannot perform fine-tuning on purely quantized models. Please attach trainable adapters on top of the quantized model to correc... | https://stackoverflow.com/questions/77909589/valueerror-you-cannot-perform-fine-tuning-on-purely-quantized-models | large-language-model, huggingface | 1,706,651,072 |
se_78392959 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Where does anythingLLM desktop save its embedding database files | Where does anythingLLM desktop save its embedding database files
I have installed anythingLLM desktop (app) on my Windows 11 (Home) platform. I have used ollama (installed in WSL2 Ubuntu) to run LLMs. anythingLLM is running fine. I am unable to find out where its vector database (lancedb) files are stored. And also wh... | https://stackoverflow.com/questions/78392959/where-does-anythingllm-desktop-save-its-embedding-database-files | large-language-model, ollama | 1,714,165,267 |
se_78875558 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to get the full reasoning history of vertexai LangchainAgent | How to get the full reasoning history of vertexai LangchainAgent
How I can see the full reasoning history of a vertexai.preview.reasoning_engines.LangchainAgent after calling the query method - I have tried setting return_intermediate_steps to True in model_kwargs and agent_executor_kwargs, but this only prints the to... | https://stackoverflow.com/questions/78875558/how-to-get-the-full-reasoning-history-of-vertexai-langchainagent | python, large-language-model, agent, google-cloud-vertex-ai | 1,723,731,970 |
se_78443363 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Error while loading MISTRAL LLM for fine-tune. Qlora doesn't work but full works | Error while loading MISTRAL LLM for fine-tune. Qlora doesn't work but full works
if I try to load the model in this way :
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_use_double_quant=True)
model = AutoModelForCausalLM.from_pretrained(
"mistralai/Mistr... | https://stackoverflow.com/questions/78443363/error-while-loading-mistral-llm-for-fine-tune-qlora-doesnt-work-but-full-works | deep-learning, large-language-model, fine-tuning, mistral-7b | 1,715,093,452 |
se_78873329 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Understanding statistical significance | Understanding statistical significance
I have 16 birds (191978,191984, 191977, 191980, 191986, 201446, 191983, 201447, 211598, 211590, 211595, 191981, 211591, 201441, 201445, 211592). There are 6 males and 10 females. The dataset is called 'Gbirds_sex' I have the number of times they revisit their release site (visitI... | https://stackoverflow.com/questions/78873329/understanding-statistical-significance | statistics, glm, large-language-model, glmmtmb | 1,723,683,287 |
se_78873680 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to create a function call tool to analyse CSV in LLM Long-chain with all columns definition predefined | How to create a function call tool to analyse CSV in LLM Long-chain with all columns definition predefined
Context
I would like to create an GPT Agent. This Agent should be able to fetch data from 3 predefined CSV files. Hence I would like to create 3 function tools for each CSV file.
Expectation
AI Agent should under... | https://stackoverflow.com/questions/78873680/how-to-create-a-function-call-tool-to-analyse-csv-in-llm-long-chain-with-all-col | python, openai-api, langchain, large-language-model, gpt-4 | 1,723,697,711 |
se_78869859 | stackoverflow | ARTIFICIAL_INTELLIGENCE | ModuleNotFoundError: No module named 'transformers.models.phi3' | ModuleNotFoundError: No module named 'transformers.models.phi3'
When I try to run a LLM named ChatGLM3 in Aliyun, I run a python script to run a demo,but it comes out an error like this.enter image description here
How to solve it ?the LLM‘s github link is text，another py file named
streamlit run web_demo_stre... | https://stackoverflow.com/questions/78869859/modulenotfounderror-no-module-named-transformers-models-phi3 | python, large-language-model | 1,723,623,903 |
se_78870698 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Is it necessary for torch_dtype when loading a model and the precision for trainable weights to be different? If so, why? | Is it necessary for torch_dtype when loading a model and the precision for trainable weights to be different? If so, why?
According to this comment in the huggingface/peft package, if a model is loaded in fp16, the trainable weights must be cast to fp32. From this comment, I understand that generally, the torch_dtype ... | https://stackoverflow.com/questions/78870698/is-it-necessary-for-torch-dtype-when-loading-a-model-and-the-precision-for-train | python, pytorch, nlp, huggingface-transformers, large-language-model | 1,723,635,568 |
se_78861856 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How do I solve an AttributeError: 'str' object has no attribute 'page_content' error? | How do I solve an AttributeError: 'str' object has no attribute 'page_content' error?
I have a Json file which has Dictionary type structure. I want to get chunks of its information followed by create embeddings.
I am getting this error while I create Embeddings:
from langchain_community.vectorstores i... | https://stackoverflow.com/questions/78861856/how-do-i-solve-an-attributeerror-str-object-has-no-attribute-page-content-e | json, python-3.x, langchain, large-language-model, ollama | 1,723,468,068 |
se_78863385 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Recency-aware finetuning for question answering | Recency-aware finetuning for question answering
I am looking to fine-tune LLaMA 3 for a question-answering task using specific data that I have collected. Each question-answer pair in my dataset includes a timestamp (in the format MM/DD/YY) ranging from as far back as 2005 to as recent as 2024. While I intend to utili... | https://stackoverflow.com/questions/78863385/recency-aware-finetuning-for-question-answering | large-language-model, llama, fine-tuning, nlp-question-answering | 1,723,492,509 |
se_78808829 | stackoverflow | ARTIFICIAL_INTELLIGENCE | failed_generation with Groq LLM and llama index in Python | failed_generation with Groq LLM and llama index in Python
My code is the following:
from llama_parse import LlamaParse
from llama_index.llms.groq import Groq
from llama_parse.base import ResultType, Language
from llama_index.core.node_parser import MarkdownElementNodeParser
parser = LlamaParse(
api_key="xxx",
... | https://stackoverflow.com/questions/78808829/failed-generation-with-groq-llm-and-llama-index-in-python | python, large-language-model, llama-index, groq | 1,722,282,348 |
se_78519099 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Async Chain Invocation with Langchain Gets Stuck at await chain.invoke() in Python | Async Chain Invocation with Langchain Gets Stuck at await chain.invoke() in Python
I am working on a project using the Langchain library to process and query information from a PDF document. My setup involves loading the PDF, splitting it into chunks, adding these chunks to a vector database, and then setting up a ret... | https://stackoverflow.com/questions/78519099/async-chain-invocation-with-langchain-gets-stuck-at-await-chain-invoke-in-pyth | python, langchain, large-language-model, py-langchain, ollama | 1,716,397,884 |
se_76537855 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Finetuning Open LLMs | Finetuning Open LLMs
I am a newbie trying to learn fine tuning. Started with falcon 7B instruct LLM as my base LLM and want to fine tune this with open assistant instruct dataset. I have 2080 Ti with 11G VRAM. So I am using 4 bit quantization and Lora.
These are the experiments I did so far:
1> I trained with SFT trai... | https://stackoverflow.com/questions/76537855/finetuning-open-llms | huggingface, falcon, large-language-model | 1,687,504,558 |
se_78248012 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Failure running Apple MLX lora.py on 13B llms | Failure running Apple MLX lora.py on 13B llms
I am attempting to train my models on my own data. If I run the lora.py command using the 7b models from mistral or llama, it works fine. As soon as I upgrade to the larger models, I get an error File “/Users/conleysa/AI/MLX/mlx_venv/lib/python3.11/site-packages/mlx/nn/lay... | https://stackoverflow.com/questions/78248012/failure-running-apple-mlx-lora-py-on-13b-llms | large-language-model | 1,711,803,443 |
se_78838421 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Ollama with RAG for local utilization to chat with pdf | Ollama with RAG for local utilization to chat with pdf
I am trying to build ollama usage by using RAG for chatting with pdf on my local machine.
I followed this GitHub repo: https://github.com/tonykipkemboi/ollama_pdf_rag/tree/main
The issue is when I am running code, there is no error, but the code will stop at embed... | https://stackoverflow.com/questions/78838421/ollama-with-rag-for-local-utilization-to-chat-with-pdf | python, large-language-model, python-embedding, ollama, rag | 1,722,938,523 |
se_78857426 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Error when using inputs_embeds with generate method | Error when using inputs_embeds with generate method
I'm encountering a problem when trying to use inputs_embeds to pass the embedding to my model:
ValueError: You passed `inputs_embeds` to `.generate()`, but the model class LlamaForCausalLM doesn't have its forwarding implemented. See the GPT2 implementation for an ex... | https://stackoverflow.com/questions/78857426/error-when-using-inputs-embeds-with-generate-method | nlp, huggingface-transformers, large-language-model, embedding, word-embedding | 1,723,345,658 |
se_78091831 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to combine Parent Document Retriever with Self Query Retriever with Lang Chain framework | How to combine Parent Document Retriever with Self Query Retriever with Lang Chain framework
I have implemented a Self Query retriever (https://python.langchain.com/docs/modules/data_connection/retrievers/self_query) for my RAG model, and it works fine. I can retrieve specific chunks of documents based on metadata inf... | https://stackoverflow.com/questions/78091831/how-to-combine-parent-document-retriever-with-self-query-retriever-with-lang-cha | python, large-language-model, py-langchain, retrieval-augmented-generation | 1,709,365,569 |
se_78845956 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Use ajax to call php, to call python, and get the result | Use ajax to call php, to call python, and get the result
I have built a website with a fairly complex structure and lots of javascript and php functions. I avoided jquery to make it lighter.
I now want to add a python function that should return a value to it. Most people recommend Flask for this, but all the examples... | https://stackoverflow.com/questions/78845956/use-ajax-to-call-php-to-call-python-and-get-the-result | javascript, python, php, ajax, large-language-model | 1,723,071,087 |
se_78852760 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Getting HTTP Status code 429 while hitting OpenAI LLM API | Getting HTTP Status code 429 while hitting OpenAI LLM API
I am using Langchain 0.2 to create a conversation pipeline with OpenAI LLM. Following is the code that I have written:
chat_llm = ChatOpenAI(
model_name="gpt-4",
api_key=config\["api_key"\],
openai_api_base=platform_url,
default_headers=llm_headers,
)
history_... | https://stackoverflow.com/questions/78852760/getting-http-status-code-429-while-hitting-openai-llm-api | python, openai-api, langchain, large-language-model, py-langchain | 1,723,206,397 |
se_78843382 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Handling greet type of questions without llm in RAG | Handling greet type of questions without llm in RAG
I'm implementing a Retrieval-Augmented Generation (RAG) system for a chatbot that handles a variety of user queries. While RAG is primarily designed to provide informative responses by retrieving relevant documents and generating responses using a language model (LLM... | https://stackoverflow.com/questions/78843382/handling-greet-type-of-questions-without-llm-in-rag | machine-learning, artificial-intelligence, large-language-model | 1,723,029,471 |
se_78844205 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to develop a Generalized RAG Pipeline for Text, Images, and Structured Data | How to develop a Generalized RAG Pipeline for Text, Images, and Structured Data
I'm trying to find a general solution for RAG to solve problems involving both text, images, chart, tables,.., they are in many different formats such as .docx, .xlsx, .pdf.
The requirement for the answer:
Some answers are just images
Som... | https://stackoverflow.com/questions/78844205/how-to-develop-a-generalized-rag-pipeline-for-text-images-and-structured-data | python, langchain, large-language-model, python-embedding, rag | 1,723,040,568 |
se_77960745 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Error when attempting to add data source to Azure OpenAI api | Error when attempting to add data source to Azure OpenAI api
My code is working for a call to Azure OpenAI when I don't have a datasource added. However, when I do add my datasource with the following parameters I get an error:
response = client.chat.completions.create(
messages = [
{
"role": "... | https://stackoverflow.com/questions/77960745/error-when-attempting-to-add-data-source-to-azure-openai-api | azure-cognitive-services, large-language-model, azure-openai | 1,707,386,514 |
se_78820055 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Why is attn_mask in PyTorch' MultiheadAttention specified for each head separately? | Why is attn_mask in PyTorch' MultiheadAttention specified for each head separately?
PyTorch MultiheadAttention allows to specify the attention mask, either as 2D or as 3D. The former will be broadcasted over all N batches the latter allows one to specify specific masks for each example in the batch. All seems to m... | https://stackoverflow.com/questions/78820055/why-is-attn-mask-in-pytorch-multiheadattention-specified-for-each-head-separate | python, pytorch, large-language-model, transformer-model, multihead-attention | 1,722,503,243 |
se_77362103 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to Convert openai functions to PromptTemplate in langchain when using local llms? | How to Convert openai functions to PromptTemplate in langchain when using local llms?
Is is possible to Convert openai functions to PromptTemplate in langchain when using local llms and return final output similar to openai api function format
import langchain
functions = [
{
"name": "get_current_w... | https://stackoverflow.com/questions/77362103/how-to-convert-openai-functions-to-prompttemplate-in-langchain-when-using-local | python, openai-api, large-language-model, py-langchain | 1,698,258,834 |
se_78840242 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to return used context to answer using Langchain in Python | How to return used context to answer using Langchain in Python
I have built a RAG system like this:
loader = PyPDFLoader(pdf_file_name)
raw_documents = loader.load()
text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
documents = text_splitter.split_documents(raw_documents)
print(docume... | https://stackoverflow.com/questions/78840242/how-to-return-used-context-to-answer-using-langchain-in-python | python, langchain, large-language-model | 1,722,963,447 |
se_78838209 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Error When Using unstructured to Partition PDF Files | Error When Using unstructured to Partition PDF Files
I'm trying to use the unstructured, unstructured[pdf] library in Python to partition a .pdf file, but I'm encountering an error that I can't seem to resolve. The pdf file contains text, table, image,...
Here's a brief overview of what I'm doing:
from unstructured.pa... | https://stackoverflow.com/questions/78838209/error-when-using-unstructured-to-partition-pdf-files | python, python-3.x, large-language-model, rag | 1,722,935,646 |
se_78836094 | stackoverflow | ARTIFICIAL_INTELLIGENCE | LangChain Chat History | LangChain Chat History
I am struggling with passing context to conversational rag chain when using RunnableWithMessageHistory.
I have the following query function:
def query(query_text, prompt, session_id, metadata_context):
# History retrieval test
contextualize_q_prompt = ChatPromptTemplate.from_messages(
[
... | https://stackoverflow.com/questions/78836094/langchain-chat-history | python, langchain, large-language-model, rag | 1,722,885,154 |
se_78681454 | stackoverflow | ARTIFICIAL_INTELLIGENCE | why message content is alway empty when I create my own tool with retriever in langchain? | why message content is alway empty when I create my own tool with retriever in langchain?
I create a simpler retriever based on docs, after I create a tool and I want to bind it in LLM object, but when I make a question it return empty content.
This is the code:
llm = ChatOpenAI(temperature=0, model="gpt-4o",api_key =... | https://stackoverflow.com/questions/78681454/why-message-content-is-alway-empty-when-i-create-my-own-tool-with-retriever-in-l | large-language-model, agent, py-langchain, langchain-agents | 1,719,564,081 |
se_78826206 | stackoverflow | ARTIFICIAL_INTELLIGENCE | NameError: name '_LanguageModel' is not defined | NameError: name '_LanguageModel' is not defined
I am trying to initialize vertexai llm in langchain library.
from langchain_community.llms.vertexai import VertexAI
llm = VertexAI(
max_output_tokens=1024,
temperature=0.2,
top_p=0.8,
top_k=40,
verbose=True,
)
I g... | https://stackoverflow.com/questions/78826206/nameerror-name-languagemodel-is-not-defined | python, langchain, large-language-model, google-cloud-vertex-ai | 1,722,612,251 |
se_78835174 | stackoverflow | ARTIFICIAL_INTELLIGENCE | run a large language model (LLM) as a .so shared library on Android for Unity3D integration | run a large language model (LLM) as a .so shared library on Android for Unity3D integration
I'm developing a Unity3D application for Android, and I need to integrate a large language model (LLM). From what I understand, I would need to compile the LLM as a .so shared library to use it on Android.
Has anyone done this ... | https://stackoverflow.com/questions/78835174/run-a-large-language-model-llm-as-a-so-shared-library-on-android-for-unity3d | android, unity-game-engine, shared-libraries, large-language-model, unity3d-editor | 1,722,871,379 |
se_78504124 | stackoverflow | ARTIFICIAL_INTELLIGENCE | ModuleNotFoundError: No module named 'torch.distributed._functional_collectives' | ModuleNotFoundError: No module named 'torch.distributed._functional_collectives'
I'm trying to run databricks/dolly-v2-12b usage code in collab.
When I try their code:
%pip install "accelerate>=0.16.0,<1" "transformers[torch]>=4.28.1,<5" "torch>=1.13.1,<2"
import torch
import torch.distributed as dist
#import ... | https://stackoverflow.com/questions/78504124/modulenotfounderror-no-module-named-torch-distributed-functional-collectives | python, large-language-model, databricks-dolly | 1,716,159,214 |
se_78834171 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to do distributed batch inference using tensor parallelism with Ray? | How to do distributed batch inference using tensor parallelism with Ray?
I want to perform offline batch inference with a model that is too large to fit into one GPU. I want to use tensor parallelism for this. Previously I have used vLLM for batch inference. However, now I have a custom model that does not fit into vL... | https://stackoverflow.com/questions/78834171/how-to-do-distributed-batch-inference-using-tensor-parallelism-with-ray | large-language-model, ray, vllm | 1,722,856,727 |
se_78826381 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Why Langchain HuggingFaceEmbeddings model dimension is not the same as stated on HuggingFace | Why Langchain HuggingFaceEmbeddings model dimension is not the same as stated on HuggingFace
I was using langchain HuggingFaceEmbeddings model: dunzhang/stella_en_1.5B_v5.
When I look at https://huggingface.co/spaces/mteb/leaderboard, I can see that the model is 8192.
But when I do
len(embed_model.embed_query("hey you... | https://stackoverflow.com/questions/78826381/why-langchain-huggingfaceembeddings-model-dimension-is-not-the-same-as-stated-on | python, langchain, large-language-model, huggingface | 1,722,615,129 |
se_78662101 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Chroma DB using embedding values | Chroma DB using embedding values
I tried creating a chromadb using embedding values but its not working. I have my own embedding model that I want to deploy on the server. So here if I pass text as list I am getting its embedded values as output in list.
But how to create chromadb or faiss db from this embedded values... | https://stackoverflow.com/questions/78662101/chroma-db-using-embedding-values | langchain, large-language-model, huggingface, python-embedding, chromadb | 1,719,228,018 |
se_78827379 | stackoverflow | ARTIFICIAL_INTELLIGENCE | What is the max_tokens number I can put for OpenAI GPT generate function? | What is the max_tokens number I can put for OpenAI GPT generate function?
I've tried to use 100_000, 20_000 but seems like only 10_000 is possible:
from openai import OpenAI
client = OpenAI()
messages = {"role": "user", "content": "Hello"}
completion = client.chat.completions.create(
model="gpt-4o-mini", mes... | https://stackoverflow.com/questions/78827379/what-is-the-max-tokens-number-i-can-put-for-openai-gpt-generate-function | python, openai-api, large-language-model, gpt-4o-mini | 1,722,636,570 |
se_78823788 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Ollama not saving anything in context | Ollama not saving anything in context
I am messing around with ollama in C# coding, and managed to get it to give me output, and even interacting with my code, however, Using the example they provided, I am running into an issue where the LLM is not retaining the previous conversations, and i ended up with the sloppy ... | https://stackoverflow.com/questions/78823788/ollama-not-saving-anything-in-context | c#, console, large-language-model, llama, ollama | 1,722,573,138 |
se_77089465 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Sagemaker and LangChain: ValueError when calling InvokeEndpoint operation for Llama 2 model | Sagemaker and LangChain: ValueError when calling InvokeEndpoint operation for Llama 2 model
I am trying to deploy a Llama 2 model for text generation inference using Sagemaker and LangChain. I am writing code in Notebook instances and deploying SageMaker instances from the code.
I followed the documentation from https... | https://stackoverflow.com/questions/77089465/sagemaker-and-langchain-valueerror-when-calling-invokeendpoint-operation-for-ll | json, amazon-sagemaker, langchain, large-language-model, llama | 1,694,524,372 |
se_78824535 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to implement bind_tools function in custom chat model | How to implement bind_tools function in custom chat model
I am trying to build a agent which uses a custom LLM (eg llama-3) and have tool calling capability. I have build my own CustomChatModel class which inherits from BaseChatModel class. I have implemented my own _generate() function. For the bind_tools() function ... | https://stackoverflow.com/questions/78824535/how-to-implement-bind-tools-function-in-custom-chat-model | python, artificial-intelligence, langchain, large-language-model, llama | 1,722,588,004 |
se_78697403 | stackoverflow | ARTIFICIAL_INTELLIGENCE | system Requirements for the DeepSeek-Coder-V2-Instruct | system Requirements for the DeepSeek-Coder-V2-Instruct
I want to know the Windows system requirements of the below versions of DeepSeek Coder V2 (236 TB and 21B AP). https://github.com/deepseek-ai/DeepSeek-Coder-V2/tree/main. I am using the system with specifications mentioned below:
Device Name: ###
Full Device Name... | https://stackoverflow.com/questions/78697403/system-requirements-for-the-deepseek-coder-v2-instruct | python-3.x, operating-system, gpu, large-language-model, ollama | 1,719,926,988 |
se_78823603 | stackoverflow | ARTIFICIAL_INTELLIGENCE | OpenAI Connection Error when running Python Langchain on GCS | OpenAI Connection Error when running Python Langchain on GCS
I've deployed a flask application to Google Cloud Services. When I run Langchain's similarity_search_with_relevance_scores on my document/database set, it throws a vaugue openai.APIConnectionError: Connection error.
Which is strange because locally, it works... | https://stackoverflow.com/questions/78823603/openai-connection-error-when-running-python-langchain-on-gcs | python, langchain, large-language-model, py-langchain, chromadb | 1,722,565,887 |
se_78821995 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to load vectors from stored chroma db? | How to load vectors from stored chroma db?
I'm working on creating a RAG-based LLM. The system is working correctly, i.e., the vector embeddings are successfully created and stored in the respective directory. However, the issue i'm facing is loading back those vectors from the stored chroma db file. Following is my f... | https://stackoverflow.com/questions/78821995/how-to-load-vectors-from-stored-chroma-db | python, chatbot, large-language-model, llama, chromadb | 1,722,528,862 |
se_77844073 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Can I not add metadata to documents loaded using Chroma.from_documents() | Can I not add metadata to documents loaded using Chroma.from_documents()
I wanted to add additional metadata to the documents being embedded and loaded into Chroma.
I'm unable to find a way to add metadata to documents loaded using
Chroma.from_documents(documents, embeddings)
For example, imagine I have a text file ha... | https://stackoverflow.com/questions/77844073/can-i-not-add-metadata-to-documents-loaded-using-chroma-from-documents | python-3.x, large-language-model, py-langchain, chromadb | 1,705,644,982 |
se_78822037 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Guidance on Extracting Compliance Items from PDF documents by fine-tuning a LLM | Guidance on Extracting Compliance Items from PDF documents by fine-tuning a LLM
Need some guidance on extracting large compliance items from raw PDF documents. I have csv with these compliance items and I want to fine-tune a LLM such that if it reads any new PDF documents it can firstly identify the compliance items a... | https://stackoverflow.com/questions/78822037/guidance-on-extracting-compliance-items-from-pdf-documents-by-fine-tuning-a-llm | nlp, large-language-model, text-extraction | 1,722,529,399 |
se_78821544 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to implement bind_tools function for custom LLM in langchain | How to implement bind_tools function for custom LLM in langchain
I am very new to langchain. I am trying to build a agent that uses a custom or local llm, and should have the tool calling ability and memory. I am using create_tool_calling_agent() from langchain docs
But I am getting the error -
Traceback (most recent ... | https://stackoverflow.com/questions/78821544/how-to-implement-bind-tools-function-for-custom-llm-in-langchain | python, langchain, large-language-model, llama, langchain-agents | 1,722,523,107 |
se_78113510 | stackoverflow | ARTIFICIAL_INTELLIGENCE | In langserve, how to pass a configurable param to a langchain LLM chain using curl? | In langserve, how to pass a configurable param to a langchain LLM chain using curl?
I have a langchain LLM chain linked to a route of a FastAPI server. I used langserve add_route() method. As I have session_id passed as "configurable" param and everything works when I invoke the chain directly like:
chain.invoke({"que... | https://stackoverflow.com/questions/78113510/in-langserve-how-to-pass-a-configurable-param-to-a-langchain-llm-chain-using-cu | curl, parameters, langchain, large-language-model, configurable | 1,709,720,113 |
se_78808274 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Ollama llama 3.1 issue in mac with api call | Ollama llama 3.1 issue in mac with api call
I have setup Ollama in Mac with OS 14.5 (2.4 GHz 8-Core Intel Core i9), running llama 3.1 with terminal and asking question work fine. But when using api call its taking more than a minute to get response. Can there be any workaround for this as I see people have face issue ... | https://stackoverflow.com/questions/78808274/ollama-llama-3-1-issue-in-mac-with-api-call | large-language-model, llama, ollama | 1,722,272,310 |
se_78815544 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to correctly save a fine tuned model using apple MLX framework | How to correctly save a fine tuned model using apple MLX framework
We're using MLX to fine tune a model fetched from hugging face.
from transformers import AutoModel
model = AutoModel.from_pretrained('deepseek-ai/deepseek-coder-6.7b-instruct')
We fine tuned the model with command like python -m mlx_lm.lora --config l... | https://stackoverflow.com/questions/78815544/how-to-correctly-save-a-fine-tuned-model-using-apple-mlx-framework | python, machine-learning, deep-learning, large-language-model | 1,722,418,534 |
se_78812873 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Inconsistent Sum of Log Probabilities in PyTorch Causal Language Model | Inconsistent Sum of Log Probabilities in PyTorch Causal Language Model
I'm working on a project using the transformers library from Hugging Face and PyTorch to compute log probabilities from a causal language model. I have two inputs: a single sentence and a batch of two sentences. However, I'm encountering an issue w... | https://stackoverflow.com/questions/78812873/inconsistent-sum-of-log-probabilities-in-pytorch-causal-language-model | huggingface-transformers, large-language-model, huggingface-tokenizers | 1,722,357,975 |
se_78800797 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to view the final prompt in a MultiQueryRetriever pipeline using LangChain? | How to view the final prompt in a MultiQueryRetriever pipeline using LangChain?
I am currently working on a project using the LangChain library where I want to retrieve relevant documents from a vector database and then generate answers based on these documents using the Ollama LLM.
Below is my current implementation:... | https://stackoverflow.com/questions/78800797/how-to-view-the-final-prompt-in-a-multiqueryretriever-pipeline-using-langchain | python, langchain, large-language-model, ollama | 1,722,065,284 |
se_76476765 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Training LLM to perform text classification | Training LLM to perform text classification
I am trying to perform text classification using GPTNeo, using the tweet_eval dataset from huggingface. I am following this example https://huggingface.co/docs/transformers/tasks/sequence_classification, but there is some error. I am a beginner at LLMs and it will be very he... | https://stackoverflow.com/questions/76476765/training-llm-to-perform-text-classification | nlp, huggingface, large-language-model | 1,686,769,102 |
se_78813152 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Ask multiple queries in parallel with Langchain Python | Ask multiple queries in parallel with Langchain Python
I have managed to ask one query using langchain like this:
template = """Use the following pieces of context to answer the question at the end.
If you don't know the answer, just say that you don't know, don't try to make up an answer.
Answer questions using the i... | https://stackoverflow.com/questions/78813152/ask-multiple-queries-in-parallel-with-langchain-python | python, large-language-model, py-langchain | 1,722,363,097 |
se_78763914 | stackoverflow | ARTIFICIAL_INTELLIGENCE | 'LlamaForCausalLM' object has no attribute 'max_seq_length' | 'LlamaForCausalLM' object has no attribute 'max_seq_length'
I'm fine-tuning llama3 using unsloth , I trained my model and saved it successfully but when I tried loading using AutoPeftModelForCausalLM.from_pretrained ,then I used TextStreamer from transformer library for streaming the generated text , ... | https://stackoverflow.com/questions/78763914/llamaforcausallm-object-has-no-attribute-max-seq-length | python, large-language-model, llama, fine-tuning, llama3 | 1,721,299,632 |
se_78809281 | stackoverflow | ARTIFICIAL_INTELLIGENCE | ImportError: cannot import name 'pre_init' from 'langchain_core.utils' | ImportError: cannot import name 'pre_init' from 'langchain_core.utils'
When I want to install langchain libraries from requirements.txt I'm getting
ImportError: cannot import name 'pre_init' from 'langchain_core.utils'
I've tried to install libraries from terminal using these commands :
pip install g... | https://stackoverflow.com/questions/78809281/importerror-cannot-import-name-pre-init-from-langchain-core-utils | python, pip, nlp, langchain, large-language-model | 1,722,293,953 |
se_78598478 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Can't install causal-conv1d on Mac M1 - packaging module not found? | Can't install causal-conv1d on Mac M1 - packaging module not found?
I'm installing oython package causal-conv1d on Mac Ventura, M1 Silicon and I am getting an error about packaging module not found.
pip install causal-conv1d==1.1.1 # or any other version 1.2.1 etc
The resulting error message is:
kages/setup... | https://stackoverflow.com/questions/78598478/cant-install-causal-conv1d-on-mac-m1-packaging-module-not-found | python, large-language-model, state-space, mamba-ssm | 1,717,933,426 |
se_78723306 | stackoverflow | ARTIFICIAL_INTELLIGENCE | OpenWebUI + Pipelines (w/ langchain hopefully) | OpenWebUI + Pipelines (w/ langchain hopefully)
I'm currently at the last step of https://github.com/open-webui/pipelines, and I tried to start the server, but it says the image below as my error. I'm not sure if the server is already running nor how to run a pipeline (like one of the examples) to test. Any advice woul... | https://stackoverflow.com/questions/78723306/openwebui-pipelines-w-langchain-hopefully | python, localhost, artificial-intelligence, langchain, large-language-model | 1,720,486,997 |
se_78558492 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Unable to Load Phi3 Model in open-webui through WSL and Docker | Unable to Load Phi3 Model in open-webui through WSL and Docker
I want to run the phi3 model locally on my laptop using WSL, Ollama, Docker, and Open-webui. Here are the steps I have followed:
Installed WSL.
Installed Ollama.
Pulled the phi3 model using Ollama.
Installed Docker.
Installed Open-webui.
I can chat with th... | https://stackoverflow.com/questions/78558492/unable-to-load-phi3-model-in-open-webui-through-wsl-and-docker | localhost, windows-subsystem-for-linux, large-language-model, webui, ollama | 1,717,138,068 |
se_78734751 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How do I persist FAISS indexes? | How do I persist FAISS indexes?
In the langchain wiki of FAISS, https://python.langchain.com/v0.2/docs/integrations/vectorstores/faiss/, it only talks about saving indexes to files.
db.save_local("faiss_index")
new_db = FAISS.load_local("faiss_index", embeddings)
docs = new_db.similarity_search(query)
How can I sav... | https://stackoverflow.com/questions/78734751/how-do-i-persist-faiss-indexes | python, vectorization, langchain, large-language-model, faiss | 1,720,690,790 |
se_76300474 | stackoverflow | ARTIFICIAL_INTELLIGENCE | mT5 Question/Answering fine tuning is generating empty sentences during inference | mT5 Question/Answering fine tuning is generating empty sentences during inference
mT5-small Question Answering training is converging to high accuracy, high validation accuracy, near-zero low loss; however, when testing the model on trained questions, I am always receiving empty answers.
Experiment Language: Arabic
D... | https://stackoverflow.com/questions/76300474/mt5-question-answering-fine-tuning-is-generating-empty-sentences-during-inferenc | deep-learning, nlp-question-answering, fine-tuning, large-language-model | 1,684,680,564 |
se_78639204 | stackoverflow | ARTIFICIAL_INTELLIGENCE | SQLite query to chunk group_concat into groups that maximize a length constraint? | SQLite query to chunk group_concat into groups that maximize a length constraint?
I have data in a SQLite table that I'd like to process in "chunks" that include concatenated fields of multiple rows up to an overall limit of 10,000 chars per chunk. I can run queries multiple times and write temp tables, if it helps. B... | https://stackoverflow.com/questions/78639204/sqlite-query-to-chunk-group-concat-into-groups-that-maximize-a-length-constraint | python, sqlite, large-language-model, group-concat | 1,718,737,479 |
se_78788707 | stackoverflow | ARTIFICIAL_INTELLIGENCE | AzureChatOpenAI only uses one tool at a time | AzureChatOpenAI only uses one tool at a time
LangChain with AzureChatOpenAI is only ever calling one tool at a time.
When prompting the model to multiply and add two sets of numbers, I expect two tool calls, however only one tool is called, without an obvious pattern which of the tools is called.
I'm following this ex... | https://stackoverflow.com/questions/78788707/azurechatopenai-only-uses-one-tool-at-a-time | python, openai-api, langchain, large-language-model, python-3.12 | 1,721,828,317 |
se_77453943 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Local LLM as argument to initialize_agent function in langchain.agents | Local LLM as argument to initialize_agent function in langchain.agents
How to correctly load a local model LLM and use it in the initialize_agent function of the langchain library?
I have a LLM google/flan-t5-large (downloaded from HuggingFaces) stored in my computer that would like to load and use as the reasoning en... | https://stackoverflow.com/questions/77453943/local-llm-as-argument-to-initialize-agent-function-in-langchain-agents | langchain, large-language-model, py-langchain | 1,699,539,965 |
se_77867015 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to prompt engineer LLM using LangChain to give "unable to answer question" when asked a question | How to prompt engineer LLM using LangChain to give "unable to answer question" when asked a question
I am currently using LangChain and OpenAI to build a Natural Language to SQL model. The issue I am having is that I want the model to return "I don't know" or "Please provide more context" when answering a qu... | https://stackoverflow.com/questions/77867015/how-to-prompt-engineer-llm-using-langchain-to-give-unable-to-answer-question-w | prompt, langchain, large-language-model | 1,706,019,947 |
se_78788062 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Optimal hyperparameters for fine tuning LLM | Optimal hyperparameters for fine tuning LLM
could I ask you for help? I am doing fine tuning of LLM model Llama3 8b (with LoRA) for text classification. I am using Trainer from Huggingface. I am looking for the optimal learning_rate and per_device_train_batch_size.
I am using AdamW_torch op... | https://stackoverflow.com/questions/78788062/optimal-hyperparameters-for-fine-tuning-llm | large-language-model, hyperparameters, fine-tuning, batchsize, learning-rate | 1,721,820,716 |
se_77630319 | stackoverflow | ARTIFICIAL_INTELLIGENCE | safetensors_rust.SafetensorError: Error while deserializing header: HeaderTooLarge | safetensors_rust.SafetensorError: Error while deserializing header: HeaderTooLarge
When fine-tuning a Large Language model (Qwen), there is no .bin ending model files but only .safetensors. The following error occurs when importing this pre-trained model. The specific code and error information are as follows.
code:
d... | https://stackoverflow.com/questions/77630319/safetensors-rust-safetensorerror-error-while-deserializing-header-headertoolar | python, large-language-model, peft | 1,702,102,068 |
se_78787053 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Where should I store my model if I want it loaded while running my application on Magic Leap? | Where should I store my model if I want it loaded while running my application on Magic Leap?
I need my GGML model loaded when I open my app. But I used
params.model = "files\\gpt-2-117M";
std::ifstream file(params.model);
if (!file.good()) {
return "wrong";
}
It always returns "wrong", which means the fi... | https://stackoverflow.com/questions/78787053/where-should-i-store-my-model-if-i-want-it-loaded-while-running-my-application-o | android, path, large-language-model, magic-leap | 1,721,808,185 |
se_78786346 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Is it possible to train large models on multiple TPUs/GPUs on Google Colab? | Is it possible to train large models on multiple TPUs/GPUs on Google Colab?
I am working on training a (small-scale) large language model and would like to parallelize the training on Google Colab. Specifically, I want to know if it's possible to utilize multiple TPUs or GPUs to speed up the training and handle large ... | https://stackoverflow.com/questions/78786346/is-it-possible-to-train-large-models-on-multiple-tpus-gpus-on-google-colab | gpu, large-language-model, gnu-parallel, tpu | 1,721,794,022 |
se_77512794 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Does Positional Interpolation Change Llama's Architecture? | Does Positional Interpolation Change Llama's Architecture?
I'm currently exploring Meta's positional interpolation method, which aims to increase with minimal effort the context size of their large language model. This method extends the context length from n x n into n′ x n′. It achieves this by interpolating new... | https://stackoverflow.com/questions/77512794/does-positional-interpolation-change-llamas-architecture | large-language-model, llama | 1,700,434,142 |
se_78784562 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Script for streaming Mistral-7B LLM output only streams on server side. Client gets full output | Script for streaming Mistral-7B LLM output only streams on server side. Client gets full output
I designed a remote server - client pipeline, which is supposed to load the model on the server and stream the output of the model.
At the moment, the output is correctly streamed, but only inside the server, meaning that t... | https://stackoverflow.com/questions/78784562/script-for-streaming-mistral-7b-llm-output-only-streams-on-server-side-client-g | deep-learning, pytorch, large-language-model, mistral-7b | 1,721,751,414 |
se_78748344 | stackoverflow | ARTIFICIAL_INTELLIGENCE | GPT-2 model from hugging face always generate same result | GPT-2 model from hugging face always generate same result
Why were all the results I got from the GPT-2 model the same no matter what I fed into it?
The following are my operating details.
First I download the needed files from the official website. These files included config.json, merges.txt, pytorch_model.bin, toke... | https://stackoverflow.com/questions/78748344/gpt-2-model-from-hugging-face-always-generate-same-result | deep-learning, pytorch, huggingface-transformers, large-language-model, gpt-2 | 1,721,025,119 |
se_77406208 | stackoverflow | ARTIFICIAL_INTELLIGENCE | CUDA out of memory error during PEFT LoRA fine tuning | CUDA out of memory error during PEFT LoRA fine tuning
I'm trying to fine-tune the model weights from a FLAN-T5 model downloaded from hugging face. I'm trying to do this with PEFT and specifically LoRA. I'm using the Python 3 code below. I'm running this on ubuntu server 18.04LTS with an invidia gpu that has 8GB of ram... | https://stackoverflow.com/questions/77406208/cuda-out-of-memory-error-during-peft-lora-fine-tuning | pytorch, large-language-model, peft | 1,698,882,493 |
se_78095157 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Why we use return_tensors = "pt" during tokenization? | Why we use return_tensors = "pt" during tokenization?
So I am doing tokenization of my dataset, and created one function,
max_length = 1026
def generate_and_tokenize_prompt(prompt):
result = tokenizer(
prompt,
return_tensors="pt",
truncation=True,
max_length=max_length,
... | https://stackoverflow.com/questions/78095157/why-we-use-return-tensors-pt-during-tokenization | large-language-model, huggingface, huggingface-tokenizers | 1,709,441,618 |
se_78688150 | stackoverflow | ARTIFICIAL_INTELLIGENCE | I got a error while pip install flash-attn throwing error | I got a error while pip install flash-attn throwing error
enter code hereI am currently trying to install
'microsoft/Florence-2-large' model and following the documentation
provided here on its github page. When running pip install
flash-attn --no-build-isolation I am thrown this error:
Collecting flash_attn Using... | https://stackoverflow.com/questions/78688150/i-got-a-error-while-pip-install-flash-attn-throwing-error | python, windows, flash, model, large-language-model | 1,719,739,808 |
se_77737111 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Errors while running DeepMind's publicly available code regarding their recent mathematical breakthrough | Errors while running DeepMind's publicly available code regarding their recent mathematical breakthrough
I am trying to re-produce DeepMind's recent result, in which they found new examples of mathematical objects using LLM's.
I am trying to execute their publicly available code on GitHub. However, despite running... | https://stackoverflow.com/questions/77737111/errors-while-running-deepminds-publicly-available-code-regarding-their-recent-m | python, module, large-language-model | 1,703,963,067 |
se_78773889 | stackoverflow | ARTIFICIAL_INTELLIGENCE | TRL SFTTrainer clarification on truncation | TRL SFTTrainer clarification on truncation
I am currently finetuning LLama models using SFTTrainer in huggingface. However, I came up with a question, I can not answer through the documentations (atleast, it is a bit ambigious).
My dataset contains samples from 20 tokens to 5k tokens.
Currently I am using a max_seq_le... | https://stackoverflow.com/questions/78773889/trl-sfttrainer-clarification-on-truncation | python, large-language-model, huggingface, llama | 1,721,508,383 |
se_78750364 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Saving Fine-tune Falcon HuggingFace LLM Model | Saving Fine-tune Falcon HuggingFace LLM Model
I'm trying to save my model so it won't need to re-download the base model every time I want to use it but nothing seems to work for me, I would love your help with it.
The following parameters are used for the training:
hf_model_name = "tiiuae/falcon-7b-instruct"
dir_path... | https://stackoverflow.com/questions/78750364/saving-fine-tune-falcon-huggingface-llm-model | python, huggingface-transformers, large-language-model, inference, pre-trained-model | 1,721,053,236 |
se_77815754 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to run LangChain Ollama with ngrok url? | How to run LangChain Ollama with ngrok url?
I ran a script to get the ngrok url:
import asyncio
# Set LD_LIBRARY_PATH so the system NVIDIA library
os.environ.update({'LD_LIBRARY_PATH': '/usr/lib64-nvidia'})
async def run_process(cmd):
print('>>> starting', *cmd)
p = await asyncio.subprocess.create_subprocess_ex... | https://stackoverflow.com/questions/77815754/how-to-run-langchain-ollama-with-ngrok-url | python, ngrok, large-language-model, ollama | 1,705,248,710 |
se_78751682 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to get multimodal embeddings from CLIP model? | How to get multimodal embeddings from CLIP model?
I'm hoping to use CLIP to get a single embedding for rows of multimodal (image and text) data.
Say I have the following model:
from PIL import Image
import torch
from transformers import CLIPProcessor, CLIPModel
import torchvision.transforms as transforms
model = CLIP... | https://stackoverflow.com/questions/78751682/how-to-get-multimodal-embeddings-from-clip-model | machine-learning, conv-neural-network, openai-api, large-language-model, word-embedding | 1,721,073,198 |
se_78768979 | stackoverflow | ARTIFICIAL_INTELLIGENCE | RuntimeError: probability tensor contains either `inf`, `nan` or element < 0 | RuntimeError: probability tensor contains either `inf`, `nan` or element < 0
am trying to output the response of the llama2 model that i installed locally, but when i try to execute the following lines:
output = model.generate(**inputs, streamer=streamer,
use_cache=True, max_new_tokens=float('inf'))
1-I tried model... | https://stackoverflow.com/questions/78768979/runtimeerror-probability-tensor-contains-either-inf-nan-or-element-0 | large-language-model, llama, rag | 1,721,386,550 |
se_78763439 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Error when tracing llm calls with Langsmith (Failed to get info from https://eu.smith.langchain.com) (Failed to batch ingest runs: LangSmithError)) | Error when tracing llm calls with Langsmith (Failed to get info from https://eu.smith.langchain.com) (Failed to batch ingest runs: LangSmithError))
I have an issue with lansgmith setup. I tried to search on the web for this issue, but could not find a solution. I follow these steps:
Created a new fresh environment:
... | https://stackoverflow.com/questions/78763439/error-when-tracing-llm-calls-with-langsmith-failed-to-get-info-from-https-eu | openai-api, langchain, large-language-model, langsmith | 1,721,294,001 |
se_78758291 | stackoverflow | ARTIFICIAL_INTELLIGENCE | AnswerRelevancyMetric not showing results on LLM evaluation | AnswerRelevancyMetric not showing results on LLM evaluation
i've got this code :
from langchain_openai import AzureChatOpenAI
from deepeval.models.base_model import DeepEvalBaseLLM
class AzureOpenAI(DeepEvalBaseLLM):
def __init__(
self,
model
):
self.model = model
def load_model(s... | https://stackoverflow.com/questions/78758291/answerrelevancymetric-not-showing-results-on-llm-evaluation | metrics, large-language-model, azure-openai, gpt-3 | 1,721,203,162 |
se_77702325 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Persist VectorStoreIndex (LlamaIndex) locally | Persist VectorStoreIndex (LlamaIndex) locally
I am trying to run this
import logging
import sys
from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
import torch
from llama_index.llms import LlamaCPP
from llama_index.llms.llama_utils import messages_to_prompt, completion_to_prompt
from langc... | https://stackoverflow.com/questions/77702325/persist-vectorstoreindex-llamaindex-locally | large-language-model, llama-index, llamacpp | 1,703,231,173 |
se_76254947 | stackoverflow | ARTIFICIAL_INTELLIGENCE | OpenAi tokens consumed in generating response of a query from custom knowledge base | OpenAi tokens consumed in generating response of a query from custom knowledge base
I am using OpenAI API to build a chatbot based on data feed by me, its consuming more tokens as predicted by words count from query & response,what is the reason?
I provided the chatbot with file containing details about finals of fifa... | https://stackoverflow.com/questions/76254947/openai-tokens-consumed-in-generating-response-of-a-query-from-custom-knowledge-b | artificial-intelligence, openai-api, large-language-model | 1,684,159,685 |
se_76772509 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Llama-2 7B-hf repeats context of question directly from input prompt, cuts off with newlines | Llama-2 7B-hf repeats context of question directly from input prompt, cuts off with newlines
Context: I am trying to query Llama-2 7B, taken from HuggingFace (meta-llama/Llama-2-7b-hf). I give it a question and context (I would guess anywhere from 200-1000 tokens), and ask it to answer the question based on the contex... | https://stackoverflow.com/questions/76772509/llama-2-7b-hf-repeats-context-of-question-directly-from-input-prompt-cuts-off-w | python, artificial-intelligence, huggingface-transformers, large-language-model | 1,690,382,805 |
se_78706130 | stackoverflow | ARTIFICIAL_INTELLIGENCE | OpenAI API query for an input document | OpenAI API query for an input document
I could build and chat with openAI model but I wish to upload a document and try to ask questions based on that doc.
I check some discussions like this
My code likes
from langchain_community.document_loaders.csv_loader import CSVLoader
from langchain_openai import AzureChatOpenAI... | https://stackoverflow.com/questions/78706130/openai-api-query-for-an-input-document | openai-api, large-language-model, azure-openai | 1,720,084,166 |
se_78753293 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to improve response time of Phi-3-medium-128k serverless API? | How to improve response time of Phi-3-medium-128k serverless API?
I have deployed the Phi-3-medium-128k model using Azure AI Studio (serverless deployment). I am using the v1/chat/completions API to get chat completions and I am streaming the response. The time to first token is quite high, ~15 secs for an average inp... | https://stackoverflow.com/questions/78753293/how-to-improve-response-time-of-phi-3-medium-128k-serverless-api | python, azure, large-language-model, azure-ai | 1,721,116,413 |
se_78589104 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Why does with_structured_output ignore optional params in Pydantic models | Why does with_structured_output ignore optional params in Pydantic models
I am experimenting with Langchain's ability to take a Pydantic model and return a structured JSON-like output from an LLM. I guess I don't understand how Optional is being interpreted.
Example using the Pydantic model directly vs its JSON cousin... | https://stackoverflow.com/questions/78589104/why-does-with-structured-output-ignore-optional-params-in-pydantic-models | python, pydantic, langchain, large-language-model | 1,717,708,726 |
se_77287311 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Exceeding LLM's maximum context length even using llama_index PromptHelper | Exceeding LLM's maximum context length even using llama_index PromptHelper
I've been struggling with llama_index's PromptHelper and can't find a solution anywhere on the Internet.
But first let me talk about my use case:
I'm trying to use Azure OpenAI's GPT-3.5 model to ask the model to make a summary of comments ... | https://stackoverflow.com/questions/77287311/exceeding-llms-maximum-context-length-even-using-llama-index-prompthelper | prompt, langchain, large-language-model, llama-index | 1,697,195,732 |
se_78738829 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to use Google Vertex AI fine tuned model via Node.js | How to use Google Vertex AI fine tuned model via Node.js
I fine-tuned a model on Google Vertex AI. Before that, I was using regular models with this code(it works):
public static async SendMessage(prompt) {
const vertexAI = new VertexAI({project: GOOGLE_PROJECT_ID, location: 'us-central1', googleAuthOptions: {keyF... | https://stackoverflow.com/questions/78738829/how-to-use-google-vertex-ai-fine-tuned-model-via-node-js | node.js, google-cloud-platform, large-language-model, google-cloud-vertex-ai | 1,720,764,642 |
se_77684999 | stackoverflow | ARTIFICIAL_INTELLIGENCE | GooglePalm(). NotImplementedError: Need to determine which default deprecation schedule to use. within ?? minor releases | GooglePalm(). NotImplementedError: Need to determine which default deprecation schedule to use. within ?? minor releases
this code was working fine before, and now it raise this error when calling GooglePalm with langchain.
The error:
----> 8 llm = GooglePalm().
NotImplementedError: Need to determine which default dep... | https://stackoverflow.com/questions/77684999/googlepalm-notimplementederror-need-to-determine-which-default-deprecation-s | nlp, langchain, large-language-model, palm-pre | 1,702,986,818 |
se_78725722 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Passing Additional Information in LangChain abatch Calls | Passing Additional Information in LangChain abatch Calls
Given an abatch call for a LangChain chain, I need to pass additional information, beyond just the content, to the function so that this information is available in the callback, specifically in the on_chat_model_start method.
Here is the code:
from langchai... | https://stackoverflow.com/questions/78725722/passing-additional-information-in-langchain-abatch-calls | python, langchain, large-language-model | 1,720,529,633 |
se_78738619 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Dockerized OpenSearch not returning any hits for queries | Dockerized OpenSearch not returning any hits for queries
I recently tried to move the chatbot project that I am working on over to OpenSearch. At first, my search function was working, but after dockerizing OpenSearch, I've run into the issue where my queries are not returning any hits. I tried to manually push a test... | https://stackoverflow.com/questions/78738619/dockerized-opensearch-not-returning-any-hits-for-queries | python, large-language-model, opensearch | 1,720,759,070 |
se_77953302 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to retrieve the generated SQL query from create_sql_agent of Langchain? | How to retrieve the generated SQL query from create_sql_agent of Langchain?
I have used Langchain - create_sql_agent to generate SQL queries with a database and get the output result of the generated SQL query. Here is how my code looks like, it is working pretty well.
agent = create_sql_agent(
llm=llm,
db=db,... | https://stackoverflow.com/questions/77953302/how-to-retrieve-the-generated-sql-query-from-create-sql-agent-of-langchain | python, sql, python-3.x, langchain, large-language-model | 1,707,295,563 |
se_78688141 | stackoverflow | ARTIFICIAL_INTELLIGENCE | How to choose dataset_text_field in SFTTrainer hugging face for my LLM model | How to choose dataset_text_field in SFTTrainer hugging face for my LLM model
Note: Newbie to LLM's
Background of my problem
I am trying to train a LLM using LLama3 on stackoverflow c langauge dataset.
LLm - meta-llama/Meta-Llama-3-8B
Dataset - Mxode/StackOverflow-QA-C-Language-40k
My dataset structure looks like so
D... | https://stackoverflow.com/questions/78688141/how-to-choose-dataset-text-field-in-sfttrainer-hugging-face-for-my-llm-model | python, large-language-model, huggingface, huggingface-datasets | 1,719,739,557 |
se_78733386 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Convert Quantization to Onnx | Convert Quantization to Onnx
I am new and want to try converting models to Onnx format and I have the following issue. I have a model that has been quantized to 4-bit, and then I converted this model to Onnx. My quantized model has a weight size of 7GB, but when I run the conversion to Onnx, my resulting model.onnx_da... | https://stackoverflow.com/questions/78733386/convert-quantization-to-onnx | large-language-model, onnx, quantization | 1,720,667,037 |
se_78621007 | stackoverflow | ARTIFICIAL_INTELLIGENCE | Trouble importing DFFullProgram, DataFrame, and DataFrameRowsOnly from llama_index | Trouble importing DFFullProgram, DataFrame, and DataFrameRowsOnly from llama_index
I have installed the llama_index library correctly and when attempting to import DFFullProgram, DataFrame,and DataFrameRowsOnly I recevie the following error.
ImportError: cannot import name 'DFFullProgram' from 'llama_index.core.progr... | https://stackoverflow.com/questions/78621007/trouble-importing-dffullprogram-dataframe-and-dataframerowsonly-from-llama-ind | python, dataframe, large-language-model, llama-index | 1,718,338,643 |
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