internlm/internlm3-8b-instruct-gguf
Text Generation
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Dr. Chad PhD
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Can't load the tokenizer
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#3 opened 1 day ago
by
echooooooooo
Requesting Support for GGUF Quantization of MiniMax-Text-01 through llama.cpp
#1 opened 2 days ago
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Doctor-Chad-PhD
fix architecture
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#3 opened 2 days ago
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TPM-28
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Why is Codestral 25.01 only local for enterprise?
#54 opened 3 days ago
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Doctor-Chad-PhD
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MoritzLaurer's
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3 days ago
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2873
FACTS is a great paper from
@GoogleDeepMind
on measuring the factuality of LLM outputs. You can now download their prompt templates from
@huggingface
to improve LLM-based fact-checking yourself!
📏 The paper introduces the FACTS Grounding benchmark for evaluating the factuality of LLM outputs.
🤖 Fact-checking is automated by an ensemble of LLM judges that verify if a response is fully grounded in a factual reference document.
🧪 The authors tested different prompt templates on held-out data to ensure their generalization.
📚 It's highly educational to read these templates to learn how frontier labs design prompts and understand their limitations.
💾 You can now download and reuse these prompt templates via the prompt-templates library!
🔄 The library simplifies sharing prompt templates on the HF hub or locally via standardized YAML files. Let’s make LLM work more transparent and reproducible by sharing more templates like this!
Links 👇
- prompt-templates docs: https://moritzlaurer.github.io/prompt_templates/
- all templates on the HF Hub: MoritzLaurer/facts-grounding-prompts
- FACTS paper: https://storage.googleapis.com/deepmind-media/FACTS/FACTS_grounding_paper.pdf
📏 The paper introduces the FACTS Grounding benchmark for evaluating the factuality of LLM outputs.
🤖 Fact-checking is automated by an ensemble of LLM judges that verify if a response is fully grounded in a factual reference document.
🧪 The authors tested different prompt templates on held-out data to ensure their generalization.
📚 It's highly educational to read these templates to learn how frontier labs design prompts and understand their limitations.
💾 You can now download and reuse these prompt templates via the prompt-templates library!
🔄 The library simplifies sharing prompt templates on the HF hub or locally via standardized YAML files. Let’s make LLM work more transparent and reproducible by sharing more templates like this!
Links 👇
- prompt-templates docs: https://moritzlaurer.github.io/prompt_templates/
- all templates on the HF Hub: MoritzLaurer/facts-grounding-prompts
- FACTS paper: https://storage.googleapis.com/deepmind-media/FACTS/FACTS_grounding_paper.pdf
qwen-turbo-1101
7
#1 opened about 2 months ago
by
LaferriereJC
I Don't Understand This Model
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#9 opened 8 days ago
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phil111
Feedback, Requests, Questions? We're here!
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#7 opened 9 days ago
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Clemo
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singhsidhukuldeep's
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9 days ago
Where is the paper?
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Post
1926
Fine-tune a SmolLM on domain-specific synthetic data from a LLM
Blog: https://huggingface.co/blog/davidberenstein1957/fine-tune-a-smollm-on-synthetic-data-of-llm
Blog: https://huggingface.co/blog/davidberenstein1957/fine-tune-a-smollm-on-synthetic-data-of-llm
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