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Kquant03/Triunvirato-7b-laser
Triunvirato-7b-laser is a text generation model from Kquant03. Use it when you need the model to write or continue text. It is set up for transformers.
Trinity-7b is a merge of the following models using LazyMergekit: mistralai/Mistral-7B-v0.1 Kukedlc/neuronal-7b-Mlab mlabonne/Monarch-7B
Downloads · 30 days
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19% of all-time downloads
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From the Hugging Face model README
Trinity-7b is a merge of the following models using LazyMergekit:
models:
- model: mistralai/Mistral-7B-v0.1
parameters:
density: [1, 0.7, 0.1] # density gradient
weight: 1.0
- model: Kukedlc/neuronal-7b-Mlab
parameters:
density: 0.5
weight: [0, 0.3, 0.7, 1] # weight gradient
- model: mlabonne/Monarch-7B
parameters:
density: 0.33
weight:
- filter: mlp
value: 0.5
- value: 0
merge_method: ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
normalize: true
int8_mask: true
dtype: float16
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Kukedlc/Triunvirato-7b"
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"])