Text Generation
Transformers
Safetensors
llama
Merge
mergekit
lazymergekit
codellama/CodeLlama-7b-Python-hf
NousResearch/Llama-2-7b-chat-hf
text-generation-inference
Instructions to use safassfa/my-merged-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use safassfa/my-merged-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="safassfa/my-merged-model")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("safassfa/my-merged-model") model = AutoModelForCausalLM.from_pretrained("safassfa/my-merged-model") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use safassfa/my-merged-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "safassfa/my-merged-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "safassfa/my-merged-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/safassfa/my-merged-model
- SGLang
How to use safassfa/my-merged-model 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 "safassfa/my-merged-model" \ --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": "safassfa/my-merged-model", "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 "safassfa/my-merged-model" \ --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": "safassfa/my-merged-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use safassfa/my-merged-model with Docker Model Runner:
docker model run hf.co/safassfa/my-merged-model
my-merged-model
my-merged-model is a merge of the following models using mergekit:
🧩 Configuration
slices:
- sources:
- model: codellama/CodeLlama-7b-Python-hf
layer_range: [0, 32]
- model: NousResearch/Llama-2-7b-chat-hf
layer_range: [0, 32]
merge_method: slerp
base_model: codellama/CodeLlama-7b-Python-hf
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
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