Z1: Efficient Test-time Scaling with Code
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armanc
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armanc
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emre
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having trouble with auto train
hello there this is the first time i am testing auto train with a 1.8k SFT dataset. Howevery i am not quite sure the training is going smooth. Logs seem quite confusing, token did not match can not auth, generates confusing train splits, do you know how i can check my running job properly?
what is being used for training as data?
any ideas?
hello there this is the first time i am testing auto train with a 1.8k SFT dataset. Howevery i am not quite sure the training is going smooth. Logs seem quite confusing, token did not match can not auth, generates confusing train splits, do you know how i can check my running job properly?
what is being used for training as data?
any ideas?
- 1 reply
armanc
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armanc
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armanc
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Manel-Hik
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Introducing Indic Chat!
Try out best opensource Indic LLMs now on https://www.indic.chat/
Models available:
• Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0
• GenVRadmin/AryaBhatta-GemmaOrca
• BhabhaAI/Gajendra-v0.1
• ai4bharat/Airavata
Additionally:
1. We open up our discord for everyone to collaborate & accelerate Indic LLMs: https://bhabha.ai/discord
2. We release ~600K rows filtered & Hindi translated version of OpenHermes-2.5 instruction dataset: BhabhaAI/openhermes-2.5-hindi
Also, thanks to our compute sponsor - Telugu LLM Labs & Bhabha AI in helping us serve models for Indic Chat.
If you’d like to be a sponsor too, checkout
https://www.indic.chat/sponsor
Try out best opensource Indic LLMs now on https://www.indic.chat/
Models available:
• Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0
• GenVRadmin/AryaBhatta-GemmaOrca
• BhabhaAI/Gajendra-v0.1
• ai4bharat/Airavata
Additionally:
1. We open up our discord for everyone to collaborate & accelerate Indic LLMs: https://bhabha.ai/discord
2. We release ~600K rows filtered & Hindi translated version of OpenHermes-2.5 instruction dataset: BhabhaAI/openhermes-2.5-hindi
Also, thanks to our compute sponsor - Telugu LLM Labs & Bhabha AI in helping us serve models for Indic Chat.
If you’d like to be a sponsor too, checkout
https://www.indic.chat/sponsor
armanc
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Introducing Gajendra!
An early release of our 7B Hindi-Hinglish-English Instruction fine-tuned language model.
Model: BhabhaAI/Gajendra-v0.1
We additionally explore ways to filter examples that can be translated from English to Hindi and are releasing initial versions of both dataset and model for it.
Model: BhabhaAI/Mistral-translation-classify
Dataset: BhabhaAI/translation-classify
Looking forward to collaborate with open source community to accelerate and release Hindi LLMs.
An early release of our 7B Hindi-Hinglish-English Instruction fine-tuned language model.
Model: BhabhaAI/Gajendra-v0.1
We additionally explore ways to filter examples that can be translated from English to Hindi and are releasing initial versions of both dataset and model for it.
Model: BhabhaAI/Mistral-translation-classify
Dataset: BhabhaAI/translation-classify
Looking forward to collaborate with open source community to accelerate and release Hindi LLMs.
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Post
some mandatory hello world as first post 🤗
from tokenizers import Tokenizer
tokenizer = Tokenizer.from_pretrained("bert-base-uncased")
tokenizer.encode("Hello world~ Hello 2024").tokens
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armanc
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msivanes
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