models:-model:danish-foundation-models/munin-7b-alpha# No parameters necessary for base model-model:mlabonne/NeuralBeagle14-7Bparameters:density:0.53weight:0.6merge_method:dare_tiesbase_model:danish-foundation-models/munin-7b-alphaparameters:int8_mask:truedtype:bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "birgermoell/swedish-gpt-merged"
model = "birgermoell/gpt-sw3-6.7b-v2-instruct-merge"
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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swedish-gpt-merged is an open source model from GitHub that offers a free installation service, and any user can find swedish-gpt-merged on GitHub to install. At the same time, huggingface.co provides the effect of swedish-gpt-merged install, users can directly use swedish-gpt-merged installed effect in huggingface.co for debugging and trial. It also supports api for free installation.