LLMs
Collection
6 items
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Updated
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We created a model from other cool models to combine everything into one cool model.
Use the code below to get started with the model.
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "ehristoforu/Gixtral-100B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
messages = [
{"role": "user", "content": "What is your favourite condiment?"},
{"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
{"role": "user", "content": "Do you have mayonnaise recipes?"}
]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
outputs = model.generate(inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Base model: mistralai/Mixtral-8x22B-Instruct-v0.1 & mistralai/Mixtral-8x7B-Instruct-v0.1
Merge models:
Merge datasets: