Text Generation
Transformers
Safetensors
mistral
Merge
mergekit
lazymergekit
teknium/OpenHermes-2.5-Mistral-7B
mistralai/Mistral-7B-v0.1
text-generation-inference
MistGem-7B-slerp
MistGem-7B-slerp is a merge of the following models using LazyMergekit:
π§© Configuration
models:
# - model: google/gemma-7b
# # no parameters necessary for base model
- model: teknium/OpenHermes-2.5-Mistral-7B
parameters:
density: 0.5
weight: 0.5
- model: mistralai/Mistral-7B-v0.1
parameters:
density: 0.5
weight: 0.3
merge_method: ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
normalize: true
dtype: float16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "codegood/MistGem-7B-slerp"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
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Install from pip and serve model
# Install vLLM from pip: pip install vllm# Start the vLLM server: vllm serve "codegood/MistHermes"# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codegood/MistHermes", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'