FinGPT/fingpt-forecaster_dow30_llama2-7b_lora

Model

Training:

155

13 commits

1 linked in READMEs

updated Jun 11, 2024

See the code

README

Training:

Check out our github: https://github.com/AI4Finance-Foundation/FinGPT/tree/master/fingpt/FinGPT_Forecaster

Inference

from datasets import load_dataset
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel


base_model = AutoModelForCausalLM.from_pretrained(
    'meta-llama/Llama-2-7b-chat-hf',
    trust_remote_code=True,
    device_map="auto",
    torch_dtype=torch.float16,   # optional if you have enough VRAM
)
tokenizer = AutoTokenizer.from_pretrained('meta-llama/Llama-2-7b-chat-hf')

model = PeftModel.from_pretrained(base_model, 'FinGPT/fingpt-forecaster_dow30_llama2-7b_lora')
model = model.eval()
  • PEFT 0.5.0
peft
safetensors

Contributors

No1r97

6 commits

ByFinTech

3 commits

amayuelas

1 commits

gmittalg

1 commits

FinGPT/fingpt-forecaster_dow30_llama2-7b_lora

Model

Training:

155

13 commits

1 linked in READMEs

updated Jun 11, 2024

See the code

README

Training:

Check out our github: https://github.com/AI4Finance-Foundation/FinGPT/tree/master/fingpt/FinGPT_Forecaster

Inference

from datasets import load_dataset
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel


base_model = AutoModelForCausalLM.from_pretrained(
    'meta-llama/Llama-2-7b-chat-hf',
    trust_remote_code=True,
    device_map="auto",
    torch_dtype=torch.float16,   # optional if you have enough VRAM
)
tokenizer = AutoTokenizer.from_pretrained('meta-llama/Llama-2-7b-chat-hf')

model = PeftModel.from_pretrained(base_model, 'FinGPT/fingpt-forecaster_dow30_llama2-7b_lora')
model = model.eval()
  • PEFT 0.5.0
peft
safetensors

Contributors

No1r97

6 commits

ByFinTech

3 commits

amayuelas

1 commits

gmittalg

1 commits