Aryabhata 2.0 Q4 K M GGUF
This model was converted to GGUF format from PhysicsWallahAI/Aryabhata-2.0 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.
Source du modèle
- Type
- Checkpoint, LoRA
- Taille du fichier
- 14,7 GB
- Modèle de base
- PhysicsWallahAI/Aryabhata-2.0
- Version
- vRevision d1272d3
- Mis à jour
- 3 oct. 2026
- Éditeur
- @PhysicsWallahAI
- Téléchargements
- 69
- Tâches
- Génération de texte
- Source
- Hugging Face
Description de la source
Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF
This model was converted to GGUF format from PhysicsWallahAI/Aryabhata-2.0 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
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).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -c 2048
Sources
1 source
Sources
1 sourceVérifié 3 oct.
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactExtraits de sources
3 extraits
Extraits de sources
3 extraits--- language: - en license: apache-2.0 tags: - reasoning - stem - mathematics - physics - chemistry - reinforcement-learning - jee - neet - education - lora - llama-cpp - gguf-my-repo base_model: PhysicsWallahAI/Aryabhata-2.0 model_type: mixture-of-experts pipeline_tag: text-generation --- # Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF This model was converted to GGUF format from [`PhysicsWallahAI/Aryabhata-2.0`](https://huggingface.co/PhysicsWallahAI/Aryabhata-2.0) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/PhysicsWallahAI/Aryabhata-2.0) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -c 2048 ``` 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. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` 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). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Ritvik19/Aryabhata-2.0-Q4_K_M-GGUF --hf-file aryabhata-2.0-q4_k_m.gguf -c 2048 ```
Source context: 69 downloads · 0 likes · Pipeline text-generation · Repo PhysicsWallahAI/Aryabhata-2.0-Q4_K_M-GGUF
Source context: 81 downloads · 0 likes · Pipeline text-generation · Repo PhysicsWallahAI/Aryabhata-2.0-Q4_K_M-GGUF
