Real ChatGPT answer · index seedyHclnciHY1scompleteB2B software · AI and automation toolsinformational
Can you explain the exact process of fine-tuning an open source LLM on our proprietary customer support transcripts?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Can you explain the exact process of fine-tuning an open source LLM on our proprietary customer support transcripts?
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
Hugging Face TRL SFTTrainer conversational dataset documentation chat template PEFT LoRA QLoRA docs Google ↗
HAGGING FACE Datasets data processing documentation PII anonymization customer support transcripts machine learning privacy guidance Google ↗
- SFT Trainer · huggingface.co
- trl/docs/source/dataset_formats.md at main · huggingface/trl · github.com
- Model collection · huggingface.co
- Official website · llama.com
- Model collection · huggingface.co
- trl/docs/source/peft_integration.md at main · huggingface/trl · github.com
- SFT Trainer · huggingface.co
- Hugging Face PEFT – LoRA and QLoRA · huggingface.co
- Microsoft Presidio – Data anonymization · microsoft.github.io
- vLLM – Model serving · docs.vllm.ai
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Hugging Face TRL SFTTrainer conversational dataset documentation chat template PEFT LoRA QLoRA docs OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
HAGGING FACE Datasets data processing documentation PII anonymization customer support transcripts machine learning privacy guidance OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |