student-abdullah/BigPharma_Generic_Q-A_Format_Augemented_Dataset
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How to use student-abdullah/Llama3.2_Trial-9_32-bit_gguf with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("student-abdullah/Llama3.2_Trial-9_32-bit_gguf", device_map="auto")How to use student-abdullah/Llama3.2_Trial-9_32-bit_gguf with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32 # Run inference directly in the terminal: llama cli -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32 # Run inference directly in the terminal: llama cli -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32 # Run inference directly in the terminal: ./llama-cli -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32 # Run inference directly in the terminal: ./build/bin/llama-cli -hf student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
docker model run hf.co/student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
How to use student-abdullah/Llama3.2_Trial-9_32-bit_gguf with Ollama:
ollama run hf.co/student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
How to use student-abdullah/Llama3.2_Trial-9_32-bit_gguf with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for student-abdullah/Llama3.2_Trial-9_32-bit_gguf to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for student-abdullah/Llama3.2_Trial-9_32-bit_gguf to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for student-abdullah/Llama3.2_Trial-9_32-bit_gguf to start chatting
How to use student-abdullah/Llama3.2_Trial-9_32-bit_gguf with Docker Model Runner:
docker model run hf.co/student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
How to use student-abdullah/Llama3.2_Trial-9_32-bit_gguf with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull student-abdullah/Llama3.2_Trial-9_32-bit_gguf:F32
lemonade run user.Llama3.2_Trial-9_32-bit_gguf-F32
lemonade list
This model is fine-tuned from the meta-llama/Llama-3.2-1B base model to enhance its capabilities in generating relevant and accurate responses related to generic medications under the PMBJP scheme. The fine-tuning process included the following hyperparameters:
32-bit
Base model
meta-llama/Llama-3.2-1B