modules: ['25_attn.q', '29_mlp.down', '30_attn.q', '8_gate', '12_mlp.up', '5_attn.o', '29_attn.o', '29_attn.q', '7_attn.v', '21_mlp.down', '23_gate', '26_attn.k', '19_mlp.up', '4_mlp.down', '9_mlp.up', '3_mlp.down', '13_attn.q', '27_attn.q', '6_mlp.down', '11_attn.o', '23_attn.q', '21_attn.k', '10_attn.k', '11_mlp.up', '8_attn.k', '23_attn.k', '8_mlp.up', '20_attn.k', '10_gate', '17_attn.v', '21_mlp.up', '16_mlp.up', '20_gate', '7_attn.o', '14_mlp.up', '30_mlp.down']

tags: ['model: llama_chat', 'repo_name: llama_chat_block_0_virology_Complete Random', 'file_name: llama_chat_block_0_virology_Complete Random_5000_5.pt', 'base_model: meta-llama/Llama-2-7b-chat-hf', 'pruning_style: block', 'community: 0', 'pruning_ratio: 20', 'dataset_label: virology', 'sparsity_ratio: 20', "dataset: ['tasksource/mmlu', 'virology']", 'finetune: Complete Random', 'modules_size: 36', "modules: ['25_attn.q', '29_mlp.down', '30_attn.q', '8_gate', '12_mlp.up', '5_attn.o', '29_attn.o', '29_attn.q', '7_attn.v', '21_mlp.down', '23_gate', '26_attn.k', '19_mlp.up', '4_mlp.down', '9_mlp.up', '3_mlp.down', '13_attn.q', '27_attn.q', '6_mlp.down', '11_attn.o', '23_attn.q', '21_attn.k', '10_attn.k', '11_mlp.up', '8_attn.k', '23_attn.k', '8_mlp.up', '20_attn.k', '10_gate', '17_attn.v', '21_mlp.up', '16_mlp.up', '20_gate', '7_attn.o', '14_mlp.up', '30_mlp.down']", 'rank: 2']

Model card Files Files and versions

xet

Community

Instructions to use KBhandari11/llama_chat_block_0_virology_Complete_Random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

Transformers

How to use KBhandari11/llama_chat_block_0_virology_Complete_Random with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="KBhandari11/llama_chat_block_0_virology_Complete_Random")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("KBhandari11/llama_chat_block_0_virology_Complete_Random")
model = AutoModelForCausalLM.from_pretrained("KBhandari11/llama_chat_block_0_virology_Complete_Random")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use KBhandari11/llama_chat_block_0_virology_Complete_Random with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KBhandari11/llama_chat_block_0_virology_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/llama_chat_block_0_virology_Complete_Random",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/KBhandari11/llama_chat_block_0_virology_Complete_Random

SGLang

How to use KBhandari11/llama_chat_block_0_virology_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/llama_chat_block_0_virology_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/llama_chat_block_0_virology_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/llama_chat_block_0_virology_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/llama_chat_block_0_virology_Complete_Random",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use KBhandari11/llama_chat_block_0_virology_Complete_Random with Docker Model Runner:
```
docker model run hf.co/KBhandari11/llama_chat_block_0_virology_Complete_Random
```

llama_chat_block_0_virology_Complete_Random

Commit History

Upload LlamaForCausalLM

09749d3
verified

KBhandari11 commited on Jun 2, 2025

initial commit

d4850d0
verified

KBhandari11 commited on Jun 2, 2025

Commit History

Upload LlamaForCausalLM 09749d3 verified

initial commit d4850d0 verified

Upload LlamaForCausalLM

09749d3
verified

initial commit

d4850d0
verified