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gemma-2b-ForexAI - GGUF

• Model creator: https://huggingface.co/mjmanashti/
• Original model: https://huggingface.co/mjmanashti/gemma-2b-ForexAI/

Name	Quant method	Size
gemma-2b-ForexAI.Q2_K.gguf	Q2_K	1.08GB
gemma-2b-ForexAI.IQ3_XS.gguf	IQ3_XS	1.16GB
gemma-2b-ForexAI.IQ3_S.gguf	IQ3_S	1.2GB
gemma-2b-ForexAI.Q3_K_S.gguf	Q3_K_S	1.2GB
gemma-2b-ForexAI.IQ3_M.gguf	IQ3_M	1.22GB
gemma-2b-ForexAI.Q3_K.gguf	Q3_K	1.29GB
gemma-2b-ForexAI.Q3_K_M.gguf	Q3_K_M	1.29GB
gemma-2b-ForexAI.Q3_K_L.gguf	Q3_K_L	1.36GB
gemma-2b-ForexAI.IQ4_XS.gguf	IQ4_XS	1.4GB
gemma-2b-ForexAI.Q4_0.gguf	Q4_0	1.44GB
gemma-2b-ForexAI.IQ4_NL.gguf	IQ4_NL	1.45GB
gemma-2b-ForexAI.Q4_K_S.gguf	Q4_K_S	1.45GB
gemma-2b-ForexAI.Q4_K.gguf	Q4_K	1.52GB
gemma-2b-ForexAI.Q4_K_M.gguf	Q4_K_M	1.52GB
gemma-2b-ForexAI.Q4_1.gguf	Q4_1	1.56GB
gemma-2b-ForexAI.Q5_0.gguf	Q5_0	1.68GB
gemma-2b-ForexAI.Q5_K_S.gguf	Q5_K_S	1.68GB
gemma-2b-ForexAI.Q5_K.gguf	Q5_K	1.71GB
gemma-2b-ForexAI.Q5_K_M.gguf	Q5_K_M	1.71GB
gemma-2b-ForexAI.Q5_1.gguf	Q5_1	1.79GB
gemma-2b-ForexAI.Q6_K.gguf	Q6_K	1.92GB
gemma-2b-ForexAI.Q8_0.gguf	Q8_0	2.49GB

Original model description:

license: other tags:

• autotrain
• text-generation widget:
• text: 'I love AutoTrain because '

---

Model Trained Using AutoTrain

This model was trained using AutoTrain. For more information, please visit AutoTrain.

Usage

!pip install transformers

!pip install accelerate


from huggingface_hub import notebook_login
notebook_login()

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch


tokenizer = AutoTokenizer.from_pretrained("mjmanashti/gemma-2b-ForexAI")
torch.set_default_dtype(torch.float16)

model = AutoModelForCausalLM.from_pretrained("mjmanashti/gemma-2b-ForexAI", device_map="auto")

chat = [
    { "role": "user", "content": "Based on the following input data: [Time: 2024-01-29 23:00:00, Open: 1.0834, High: 1.0837, Low: 1.08334, Close: 1.08338, Volume: 722] what trading signal (BUY, SELL, or HOLD) should be executed to maximize profit? If the signal is BUY, what would be the entry price and If the signal is SELL, what would be the exit price for profit maximization? " },
]
prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
outputs = model.generate(input_ids=inputs.to(model.device), max_new_tokens=150)
print(tokenizer.decode(outputs[0]))