How to Use

from unsloth import FastLanguageModel
    model, tokenizer = FastLanguageModel.from_pretrained(
        model_name = "Chimmyy/Llama3.1-8B-Finance",
        max_seq_length = 1024,
        dtype = None,
        load_in_4bit = True,
    )
    FastLanguageModel.for_inference(model)
inputs = tokenizer(
[
    prompt.format(
        "What are the advantages of investing in bonds?", # instruction
        "", # input
        "", # output - leave empty for model
    )
], return_tensors = "pt").to("cuda")

outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True) # Change max_new_tokens as needed
result = tokenizer.batch_decode(outputs)
print(result)

Uploaded model

  • Developed by: Chimmyy
  • License: apache-2.0
  • Finetuned from model : unsloth/Meta-Llama-3.1-8B-bnb-4bit

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for Chimmyy/Llama3.1-8B-Finance

Finetuned
(588)
this model