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README.md
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---
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base_model: Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0
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datasets:
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- ravithejads/samvaad-hi-filtered
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- Telugu-LLM-Labs/telugu_teknium_GPTeacher_general_instruct_filtered_romanized
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- Telugu-LLM-Labs/telugu_alpaca_yahma_cleaned_filtered_romanized
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- Telugu-LLM-Labs/sindhi_alpaca_yahma_cleaned_filtered
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- Telugu-LLM-Labs/urdu_alpaca_yahma_cleaned_filtered
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- Telugu-LLM-Labs/marathi_alpaca_yahma_cleaned_filtered
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- Telugu-LLM-Labs/assamese_alpaca_yahma_cleaned_filtered
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- Telugu-LLM-Labs/konkani_alpaca_yahma_cleaned_filtered
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- Telugu-LLM-Labs/nepali_alpaca_yahma_cleaned_filtered
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- abhinand/tamil-alpaca
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- Tensoic/airoboros-3.2_kn
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- Tensoic/gpt-teacher_kn
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- VishnuPJ/Alpaca_Instruct_Malayalam
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- Tensoic/Alpaca-Gujarati
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- HydraIndicLM/punjabi_alpaca_52K
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- HydraIndicLM/bengali_alpaca_dolly_67k
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- OdiaGenAI/Odia_Alpaca_instructions_52k
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- yahma/alpaca-cleaned
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language:
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- te
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- en
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- ta
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- ml
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- mr
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- hi
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- kn
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- sd
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- ne
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- ur
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- as
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- gu
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- bn
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- pa
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- or
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library_name: transformers
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license: other
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license_name: gemma-terms-of-use
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license_link: https://ai.google.dev/gemma/terms
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pipeline_tag: text-generation
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tags:
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- llama-cpp
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- gguf-my-repo
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---
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# ar08/Indic-gemma-7b-finetuned-sft-Navarasa-2.0-IQ3_M-GGUF
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This model was converted to GGUF format from [`Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0`](https://huggingface.co/Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/Telugu-LLM-Labs/Indic-gemma-7b-finetuned-sft-Navarasa-2.0) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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### CLI:
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```bash
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llama-cli --hf-repo ar08/Indic-gemma-7b-finetuned-sft-Navarasa-2.0-IQ3_M-GGUF --hf-file indic-gemma-7b-finetuned-sft-navarasa-2.0-iq3_m-imat.gguf -p "The meaning to life and the universe is"
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```
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### Server:
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```bash
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llama-server --hf-repo ar08/Indic-gemma-7b-finetuned-sft-Navarasa-2.0-IQ3_M-GGUF --hf-file indic-gemma-7b-finetuned-sft-navarasa-2.0-iq3_m-imat.gguf -c 2048
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```
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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```
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Step 3: Run inference through the main binary.
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```
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./llama-cli --hf-repo ar08/Indic-gemma-7b-finetuned-sft-Navarasa-2.0-IQ3_M-GGUF --hf-file indic-gemma-7b-finetuned-sft-navarasa-2.0-iq3_m-imat.gguf -p "The meaning to life and the universe is"
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```
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or
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```
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./llama-server --hf-repo ar08/Indic-gemma-7b-finetuned-sft-Navarasa-2.0-IQ3_M-GGUF --hf-file indic-gemma-7b-finetuned-sft-navarasa-2.0-iq3_m-imat.gguf -c 2048
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```
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