Questions tagged [language-model]

For questions related to the concept of a language model, which is a probability distribution over sequences of words (for example, of a natural language, such as English).

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Was ChatGPT trained on Stack Overflow data?

Has ChatGPT used highly rated and upvoted questions/answers from Stack Overflow in its training data? For me it makes complete sense to take answers that have upwards of 100 upvotes and include them ...
Nicolas Zein's user avatar
36 votes
1 answer
39k views

What is the "temperature" in the GPT models?

What does the temperature parameter mean when talking about the GPT models? I know that a higher temperature value means more randomness, but I want to know how randomness is introduced. Does ...
Tom Dörr's user avatar
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24 votes
4 answers
11k views

How does ChatGPT know math?

ChatGPT is a language model. As far as I know and If I'm not wrong, it gets text as tokens and word embeddings. So, how can it do math? For example, I asked: ME: Which one is bigger 5 or 9. ChatGPT: ...
Peyman's user avatar
  • 564
16 votes
2 answers
7k views

Why does ChatGPT not give the answer text all at once?

When ChatGPT is generating an answer to my question, it generates it word by word. So I actually have to wait until I get the final answer. Is this just for show? Or is it really real-time generating ...
Sander van den Oord's user avatar
9 votes
1 answer
1k views

What causes ChatGPT to generate responses that refer to itself as a bot or LM?

ChatGPT occasionally generates responses to prompts that refer to itself as a "bot" or "language model." For instance, when given a certain input (the first paragraph of this ...
Obie 2.0's user avatar
  • 192
7 votes
2 answers
3k views

Why can't language models, like GPT-3, continuously learn once trained?

GPT-3 has a prompt limit of about ~2048 "tokens", which corresponds to about 4 characters in text. If my understanding is correct, a deep neural network is not learning after it is trained ...
MaiaVictor's user avatar
7 votes
1 answer
1k views

How to use BERT as a multi-purpose conversational AI?

I'm looking to make an NLP model that can achieve a dual purpose. One purpose is that it can hold interesting conversations (conversational AI), and another being that it can do intent classification ...
junfanbl's user avatar
  • 323
6 votes
1 answer
3k views

What are pros and cons of Bi-LSTM as compared to LSTM?

What are the pros and cons of LSTM vs Bi-LSTM in language modelling? What was the need to introduce Bi-LSTM?
DRV's user avatar
  • 1,683
6 votes
1 answer
2k views

How was ChatGPT trained?

I know that large language models like GPT-3 are trained simply to continue pieces of text that have been scraped from the web. But how was ChatGPT trained, which, while also having a good ...
HelloGoodbye's user avatar
6 votes
1 answer
739 views

How can a language model keep track of the provenance of the main knowledge/sources used to generate a given output?

One of the main criticisms against the use of ChatGPT on Stack Exchange is that it doesn't attribute the main knowledge/sources used to generate a given output. How can a language model keep track of ...
Franck Dernoncourt's user avatar
6 votes
2 answers
545 views

How does GPT-based language model like ChatGPT determine the n-th letter of a word?

I understand that GPT models process input text by converting words into tokens and then embedding vectors and do not process them letter by letter. Given this approach, I am curious to know how a ...
Peyman's user avatar
  • 564
5 votes
2 answers
7k views

What is the difference between a language model and a word embedding?

I am self-studying applications of deep learning on the NLP and machine translation. I am confused about the concepts of "Language Model", "Word Embedding", "BLEU Score". ...
Exploring's user avatar
  • 343
5 votes
2 answers
3k views

How is the next token predicted in transformers?

In the transformer (or GPT/decoder only), at the end of the decoder blocks but before the final linear layer you have X vectors (for the X tokens at the input of the decoder). We then want to compute ...
Miguel Carvalho's user avatar
5 votes
2 answers
2k views

Where can I find pre-trained language models in English and German? [closed]

Where can I find (more) pre-trained language models? I am especially interested in neural network-based models for English and German. I am aware only of Language Model on One Billion Word Benchmark ...
Lutz Büch's user avatar
4 votes
2 answers
486 views

What makes reproducing a model like GPT3/GPT3.5/ChatGPT difficult?

Is it difficult for other companies to train a model similar to ChatGPT, and what makes it difficult? What is challenging about reproducing the results obtained by OpenAI with ChatGPT/GPT3.5? Would it ...
Robin van Hoorn's user avatar
4 votes
3 answers
206 views

What would be a good internal language for an AI?

For an AI to represent the world, it would be good if it could translate human sentences into something more precise. We know, for example, that mathematics can be built up from set theory. So ...
zooby's user avatar
  • 2,206
4 votes
1 answer
145 views

What puts the "chat" in a system like ChatGPT?

So I read Wolfram's What Is ChatGPT Doing … and Why Does It Work? but it left one really big question in my mind. His summary [if it could be called that!] really emphasizes that the core model is ...
natevw's user avatar
  • 141
4 votes
2 answers
280 views

Are embeddings in multi-lingual language models comparable across languages?

Facebook has just pushed out a bigger version of their multi-lingual language model XLM, called XLM-R. My question is: do these kind of multi-lingual models imply, or even ensure, that their ...
Bram Vanroy's user avatar
3 votes
1 answer
94 views

How can I improve this toy Graph Neural Network Generative Language model [closed]

Background I'm an undergraduate student with research interests in a field of physics that has significant overlap with graph theory, and a functioning knowledge of how simple neural nets work and how ...
MomentumEigenstate's user avatar
3 votes
1 answer
193 views

Fundamentally, what is a perfect language model?

Suppose that we want to generate a sentence made of words according to language $L$: $$ W_1 W_2 \ldots W_n $$ Question: What is the perfect language model? I ask about perfect because I want to know ...
caveman's user avatar
  • 151
3 votes
0 answers
2k views

What is input (and shape) to K/V/Q of self-attention of EACH Decoder block of Language-translation model Transformer's tokens during Inference?

Transformer model of the original Attention paper has a decoder unit that works differently during Inference than Tranining. I'm trying to understand the shapes used during decoder (both self-...
Joe Black's user avatar
  • 181
2 votes
1 answer
161 views

Is beam search the actual obstacle that prevents GPT-style models from doing sophisticated math reasoning?

This is a rather soft question. Some people believe that GPT-style models can eventually solve very complex math problems if the models are large enough, but I'm skeptical about this. Suppose the GPT ...
Soha's user avatar
  • 21
2 votes
1 answer
2k views

Why do language models produce different outputs for same prompt?

For conventional 'Neural Networks', the weights simply act as a transformation in highly multi-dimensional space; for a forward pass, the output is always the same since there is no stochastic ...
neel g's user avatar
  • 146
2 votes
1 answer
59 views

NLP "small" model to improve "big" model

When training the model for NLP is it important to get rid of data which has "bad semantic" for learning process? My plan is to create a "small model" which can decide whether data ...
Milkmaid's user avatar
  • 135
2 votes
1 answer
149 views

Would a transformer trained on highly specific material be as usable as a commercial product like ChatGPT?

Soft question here. I was recently learning a bit about how it is feasible to train a transformer on a personal computer like an M1 Mac. I have been told that the model could have 1-3 million ...
Julius Hamilton's user avatar
2 votes
1 answer
99 views

Are training sequences for LMs sampled in an IID fashion?

If I understand correctly, when training language models, we take a document and then chunk the document into a sequences of k tokens. So if the document is of length 30 and k=10, then we'll have 20 ...
Opt's user avatar
  • 121
2 votes
1 answer
84 views

How do you build a language model to predict the contextual similarity between two documents?

How do you build a language model to predict the contextual similarity between two documents?
Sujeet Kumar Pandey's user avatar
2 votes
0 answers
106 views

How do I balance context and history when creating prompts for LLM's?

A conversation through the OpenAI API looks something like this ...
Ian Purton's user avatar
2 votes
1 answer
82 views

Is the problem of Language Modelling a Well-Posed Learning Problem?

Hadamard defines (Well-posed problem (Wikipedia)) a well-posed problem as one for which: a solution exists, the solution is unique, the solution depends continuously on the data (e.g. it is stable) ...
aren't eistert's user avatar
2 votes
0 answers
356 views

What's the most efficient way of performing batched training of Causal Language Models?

I have seen a number of ways to train (yes, train, not fine-tune) these models efficiently with batches. I will illustrate these techniques with the following example dataset and context window: ...
thesofakillers's user avatar
2 votes
0 answers
80 views

How can I generate a document from a single word using GPT or BERT?

I have a dataset of 100000 documents each labelled with a topic to it. I want to create a model such that, given a topic, the model can generate a document from it. I came across language models GPT,...
mayank agrawal's user avatar
1 vote
1 answer
139 views

Is there a limitation to the amount of data that a genAI model could be trained upon?

My friend says that genAI would become more human like, and perhaps even smarter than humans if it were simply trained on more and more data. I say that this would overtrain the models, and we would ...
tryst with freedom's user avatar
1 vote
1 answer
154 views

What background should I have before starting to fine tune a Large Language Model?

I want to know what things I should be learning before trying to fine-tune or for that matter working with a large language model. In my case, I am trying to fine-tune bloom (https://huggingface.co/...
kelly's user avatar
  • 23
1 vote
1 answer
865 views

What are the main differences between a language model and a machine translation model?

What are the main differences between a language model and a machine translation model?
DRV's user avatar
  • 1,683
1 vote
2 answers
88 views

What technique is used for training Large Language Models like GPT?

I'm learning about GenAI, such as GPT (Generative Pretrained Transformer), and I'm particularly interested in understanding the training techniques used for these models. Deep learning, generally, can ...
Exploring's user avatar
  • 343
1 vote
2 answers
52 views

Data preparation for NLP model

I have data from our ticketing system. Currently using OpenNLP to create different models. For simplicity I have a 10k ticket's text as category final queue of the ticket. My questions: Is it ...
Milkmaid's user avatar
  • 135
1 vote
1 answer
164 views

How to train a language model to write poem?

I am using some of the LLM applications, and all of them are better at provide formal, steady conversations, rather than writing texts with styles. So I wonder whether it is possible to train a LLM ...
Cabbage's user avatar
  • 11
1 vote
1 answer
190 views

If we prompt a large language model on a task, will its ability for other tasks be affected? How to recover?

For example, I guess that for some retrieval augmented LLMs, their generated contents may lack some creativity? Recent work has explored the inability of retrieval augmented methods to enhance the ...
Iris88's user avatar
  • 11
1 vote
1 answer
602 views

For specific tasks, is it better to fine-tune models on examples or just use prompting with the context of the task?

These days large language models cover a vast amount of topics and information, but I wanted to understand: For specific tasks, is it better to fine-tune models on examples or just use prompting with ...
Imran Q's user avatar
  • 113
1 vote
1 answer
77 views

What is the lowest possible loss for a language model?

Example: Suppose a character-level language model (three input letters to predict the next one), trained on a dataset which contains three instances of the sequence ...
ViniciusArruda's user avatar
1 vote
1 answer
962 views

Papers on Prompt Engineering

I am into AI in general and NLP in particular. Besides, I have a background in philosophy, and the new LLMs like GPT-3 seem to have exciting capabilities. I want to study prompt engineering (for ...
Mehdi Abbassi's user avatar
1 vote
1 answer
58 views

Appropriate metric and approach for natural language generation for small sentences

I am trying to create a language generation model to generate very short sentences/words, like a rapper name generator. The sentences in my dataset are anywhere between 1 word and 15 words (3-155 ...
SajanGohil's user avatar
1 vote
1 answer
29 views

publically available language models that can be used to train arbitrary language data?

I have sentence data in a language that is not widely in use and as such popular LLMs do not support the language. I want to train some language model such that given some question, it is able to ...
Neijal Kanderbalt's user avatar
1 vote
1 answer
95 views

Why do current language models no longer generate to long or short texts?

One of the biggest strengths of ChatGPT is that it generates fitting text with respect to the input query. It usually stays on topic, anwers the question completely and especially does not start ...
Ricu's user avatar
  • 11
1 vote
0 answers
43 views

Can I reduce computation by only predicting response tokens in a transformer and still get the same gradients?

I have been looking at the source code of the Stanford Alpaca model and I believe that during inference, the whole instruction + response data is fed into the model normally. Then the instruction part ...
Tianchen Zheng's user avatar
1 vote
0 answers
89 views

Coding a conversational AI which remembers previous context

I am trying to code a proper conversational AI which remembers previous context and answers accordingly (something like a micro ChatGPT). Additionally I want the AI to work on a custom knowledge base ...
JAYDEEP GHOSE's user avatar
1 vote
0 answers
760 views

How to best implement Accelerate for vary large models

This was pointed out to me: https://huggingface.co/blog/accelerate-large-models and seems it could be a great resource, but it is broken down into steps as a tutorial vs as out of the box solution ...
jmhead's user avatar
  • 111
1 vote
0 answers
85 views

How can i create a new language model for language other than english?

I have large set of corpus for all literature in 'Tamil' language, i am trying to create a document retrieval engine through simple natural language. Since the corpus is huge, its hard to do a ...
Thiyaga B's user avatar
  • 111
1 vote
0 answers
23 views

How can (pretrained) language models actively seek additional training data - possibly reference request?

I am reading the paper "Large Language Models Can Self-Improve" https://arxiv.org/abs/2210.11610 in which the authors consider that LLM can generate Chain-of-Thoughts sequences and even ...
TomR's user avatar
  • 843
1 vote
0 answers
27 views

Are custom tokens better than punctuation pseudo-tokens for LLMs?

I've seen two approaches for introducing custom tokens for transfer learning with large language models like Bert or GPT3. Some approaches introduce new tokens into the vocabulary and learn embeddings ...
A Tyshka's user avatar
  • 111