Text Generation
Transformers
Safetensors
llama
model: vicuna
repo_name: vicuna_block_1_salient_translation_error_detection_Complete Random
file_name: vicuna_block_1_salient_translation_error_detection_Complete Random_5000_5.pt
pruning_style: block
community: 1
pruning_ratio: 20
dataset_label: salient_translation_error_detection
sparsity_ratio: 20
['tasksource/bigbench', 'salient_translation_error_detection']
finetune: Complete Random
modules_size: 13
modules: ['16_attn.o', '23_attn.q', '19_mlp.down', '22_gate', '29_attn.k', '19_attn.q', '8_attn.k', '11_attn.q', '21_mlp.up', '22_attn.v', '4_mlp.down', '29_mlp.down', '8_mlp.up']
rank: 3
tags: ['model: vicuna', 'repo_name: vicuna_block_1_salient_translation_error_detection_Complete Random', 'file_name: vicuna_block_1_salient_translation_error_detection_Complete Random_5000_5.pt', 'base_model: lmsys/vicuna-7b-v1.5', 'pruning_style: block', 'community: 1', 'pruning_ratio: 20', 'dataset_label: salient_translation_error_detection', 'sparsity_ratio: 20', "dataset: ['tasksource/bigbench', 'salient_translation_error_detection']", 'finetune: Complete Random', 'modules_size: 13', "modules: ['16_attn.o', '23_attn.q', '19_mlp.down', '22_gate', '29_attn.k', '19_attn.q', '8_attn.k', '11_attn.q', '21_mlp.up', '22_attn.v', '4_mlp.down', '29_mlp.down', '8_mlp.up']", 'rank: 3']
text-generation-inference
Instructions to use KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random") model = AutoModelForCausalLM.from_pretrained("KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random
- SGLang
How to use KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random with Docker Model Runner:
docker model run hf.co/KBhandari11/vicuna_block_1_salient_translation_error_detection_Complete_Random
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