TechQA.

Question

Is it possible to fine tune or use RAG on the CoreML version of Llama2?

score 250 · Answer 1 · 2023-10-13 16:11:26

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Answer

250

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Is it possible to fine tune or use RAG on the CoreML version of Llama2?

250 views Asked by Mike Ike At 13 October 2023 at 16:11

score 1757 · Answer 2 · 2023-10-17 14:37:12

Compare two strings by meaning using LLMs

1.7k views Asked by root At 17 October 2023 at 14:37

score 364 · Answer 3 · 2023-10-14 11:16:29

Implementation (and working) differences between AutoModelForCausalLMWithValueHead vs AutoModelForCausalLM?

364 views Asked by Deshwal At 14 October 2023 at 11:16

score 152 · Answer 4 · 2023-10-18 07:09:33

How do I know the right data format for different LLMs finetuning？

152 views Asked by John At 18 October 2023 at 07:09

score 72 · Answer 5 · 2023-10-16 07:55:20

I am trying to make a product which will reformat the answer using the question and Sql_answer as data

72 views Asked by S_K At 16 October 2023 at 07:55

score 328 · Answer 6 · 2023-10-10 06:39:16

CUDA OutOfMemoryError but free memory is always half of required memory in error message

328 views Asked by olivarb At 10 October 2023 at 06:39

score 835 · Answer 7 · 2023-10-17 07:04:56

Query with my own data using langchain and pinecone

835 views Asked by javascript-wtf At 17 October 2023 at 07:04

score 420 · Answer 8 · 2023-10-18 12:28:45

Could not find a version that satisfies the requirement python-magic-bin

420 views Asked by Debrup Paul At 18 October 2023 at 12:28

score 599 · Answer 9 · 2023-10-14 21:28:49

Any possibility to increase performance of querying chromadb persisted locally

599 views Asked by mlee_jordan At 14 October 2023 at 21:28

score 102 · Answer 10 · 2023-10-12 11:23:02

Grid based decision making with Llama 2

102 views Asked by skvp At 12 October 2023 at 11:23

TechQA.

List Question

Is it possible to fine tune or use RAG on the CoreML version of Llama2?

Compare two strings by meaning using LLMs

Implementation (and working) differences between AutoModelForCausalLMWithValueHead vs AutoModelForCausalLM?

How do I know the right data format for different LLMs finetuning？

I am trying to make a product which will reformat the answer using the question and Sql_answer as data

CUDA OutOfMemoryError but free memory is always half of required memory in error message

Query with my own data using langchain and pinecone

Could not find a version that satisfies the requirement python-magic-bin

Any possibility to increase performance of querying chromadb persisted locally

Grid based decision making with Llama 2

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