Joshfcooper / jamba-chat-lora

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Total runs: 0
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Model's Last Updated: January 12 2025

Introduction of jamba-chat-lora

Model Details of jamba-chat-lora

Jamba Chat LoRA

This is a LoRA fine-tuned version of the Jamba model trained on chat conversations.

Model Description
  • Base Model: LaferriereJC/jamba_550M_trained
  • Training Data: UltraChat dataset
  • Task: Conversational AI
  • Fine-tuning Method: LoRA (Low-Rank Adaptation)
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel, PeftConfig

# Load the model
model = AutoModelForCausalLM.from_pretrained(
    "LaferriereJC/jamba_550M_trained",
    trust_remote_code=True
)
model = PeftModel.from_pretrained(model, "your-username/jamba-chat-lora")

# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained("LaferriereJC/jamba_550M_trained")

# Example usage
text = "User: How are you today?\nAssistant:"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
Training Details
  • Training Data: UltraChat dataset (subset)
  • LoRA Config:
    • Rank: 16
    • Alpha: 32
    • Target Modules: Last layer feed forward experts
    • Dropout: 0.1
  • Training Parameters:
    • Learning Rate: 5e-4
    • Optimizer: AdamW (32-bit)
    • LR Scheduler: Cosine
    • Warmup Ratio: 0.03

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https://huggingface.co/Joshfcooper/jamba-chat-lora

jamba-chat-lora install

jamba-chat-lora is an open source model from GitHub that offers a free installation service, and any user can find jamba-chat-lora on GitHub to install. At the same time, huggingface.co provides the effect of jamba-chat-lora install, users can directly use jamba-chat-lora installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

jamba-chat-lora install url in huggingface.co:

https://huggingface.co/Joshfcooper/jamba-chat-lora

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