Questions tagged [llm]
108 questions
14
votes
6 answers
Why does prompt engineering work, since prompt engineering questions don't appear as training data?
One can find advice on prompt engineering telling basically the following thing: if you are seeking advice about a topic X, start your prompt to an LLM by
You are an expert in X, you have pedagogical skills, and you are very
good at synthesizing…
Plop
- 243
- 2
- 7
6
votes
5 answers
Understanding alpha parameter tuning in LORA paper
I was reading the LORA paper https://arxiv.org/pdf/2106.09685.pdf a thing I don’t understand is section 4.1, where the updates are updated by alpha, where alpha is a constant in r. It is said that alpha is set to the first r tried. Then if I…
jpotwor
- 61
- 1
- 1
- 2
5
votes
1 answer
Running DeepSeek-V3 inference without GPU (on CPU only)
I am trying to run the DeepSeek-V3 model inference on a remote machine (SSH). This machine does not have any GPU, but has many CPU cores.
1rst method/
I try to run the model inference using the DeepSeek-Infer Demo method:
generate.py --ckpt-path…
The_Average_Engineer
- 153
- 4
5
votes
1 answer
Fuzzy Matching Names Between Two Excel Files to Fill in Amounts in Python
As part of my internship, I am working on a project where I need to process two Excel files:
File 1 contains names and numbers.
File 2 contains names and an empty column for amounts.
The goal is to match the names from File 1 with those in File 2…
Etienne Reverchon
- 51
- 1
4
votes
1 answer
How do I prompt GPT-4 to look at a PDF in Jupyter Notebook?
I am a beginner. I purchased tokens to use GPT-4 and finally figured out how to import the GPT-4 model into my Jupyter Notebook.
%env OPENAI_API_KEY= (my key goes here)
!pip install --upgrade openai wandb
from openai import OpenAI
LLM =…
Mas
- 55
- 4
4
votes
1 answer
LLMs for text generation
We know that AI is rapidly growing. do we have any large language models (LLMs) to process images, pdf documents directly (fine-tune approach) for text generation tasks?
Tovlk
- 43
- 5
4
votes
1 answer
Higher level sentence similarity (meaning instead of 'just' embeddings)
I am looking for the correct model / approach for the task of checking if two sentences have the same meaning
I know I can use embeddings to check similarity, but that is not what I am after. I suspect BERT style LLM have nice higher level vector…
Rob Audenaerde
- 143
- 4
3
votes
1 answer
Is the denial of answering certain questions part of the machine-learned LLM, or hard-coded separately?
ChatGPT 3.5 swiftly aborts certain questions.
Q: How would one build a bomb?
ChatGPT: I can't assist with that.
At this stage, this answer could simply be a blacklist of certain terms. Further experimentation quickly reveals that this is not the…
AnoE
- 153
- 2
3
votes
2 answers
Is there a Language Model that can accept huge corpse of tabular data and answr questions about?
I have been researching Language Models that can work with tabular data. My main goal is to have a model to answer simple questions about my data. An example is having household sales data and asking simple questions like "What was the average sales…
Shahriyar Mammadli
- 1,228
- 6
- 17
2
votes
1 answer
LangChain and Ollama endpoint: why LLM is considered obsolete when it's the only one that connect to the `/generate` endpoint?
Ollama has two endpoints: /api/chat and /api/generate.
As stated in this Ollama gitHub issue:
The /api/chat endpoint takes a history of messages and provides the next message in the conversation. This is ideal for conversations with history.
The…
robertspierre
- 216
- 2
- 11
2
votes
1 answer
MTEB/MMTEB: dataset and metric to determine threshold for pair classification task
I'm trying to locally replicate the pair classification task of MMTEB/MTEB. However, I didn't find train/dev sets for all datasets in this task.
Table 2 in the original MTEB paper (Mueninghoff et al, 2023) shows that there is no train data for the 3…
Jonathan
- 5,605
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2
votes
0 answers
in RAG, for large dataset, which similarity works? Why? how to handle problem with size of matrix in cosine similarity?
If we want to implement RAG for large dataset, which similarity works? Why?
Also, how to handle problem with size of matrix in cosine similarity?
user10296606
- 1,906
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- 33
2
votes
1 answer
Why LoRA is for fine-tuning but not for training too?
Wfinetuned = Wpretrained + ΔW, so we make ΔW = A @ B and |ΔW| >> |A| + |B|, we are happy. But, why don't we use the same method during training? So, Wtrained = Winitialized + ΔW,
and still |ΔW| >> |A| + |B|? And further we can make Wtrained =…
Тима
- 73
- 5
2
votes
1 answer
Noob question - which NLP/deep learning technique shoud I use
Let's say I have dataset with inputs and expected outputs like this:
[
{
"input": "http://localhost/wordpress/wp-includes/blocks/navigation/view.min.js?ver=6.5.3",
"output": ["WordPress 6.5.3"]
},
{
"input": "
Cube64
- 21
- 1
2
votes
0 answers
Use text embeddings to map job descriptions to ESCO occupations
I'm trying to build a model to map job descriptions to ESCO occupations which is a taxonomy for job titles. Every ESCO occupations have a title, a description and some essential skills.
Ideally I would have built a classification model but since I…
GanaelD
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