mkly/crypto-sales

Adapter mkly/crypto_sales for meta-llama/Llama-2-7b-chat-hf

An adapter for the meta-llama/Llama-2-7b-chat-hf model that was trained on the mkly/crypto-sales-question-answers dataset.

Training procedure

The following bitsandbytes quantization config was used during training:

• quant_method: bitsandbytes
• load_in_8bit: False
• load_in_4bit: True
• llm_int8_threshold: 6.0
• llm_int8_skip_modules: None
• llm_int8_enable_fp32_cpu_offload: False
• llm_int8_has_fp16_weight: False
• bnb_4bit_quant_type: nf4
• bnb_4bit_use_double_quant: False
• bnb_4bit_compute_dtype: bfloat16

Framework versions

• PEFT 0.5.0

Prompt

### INSTRUCTION
Be clever and persuasive, while keeping things to one paragrah. Answer the following question while also upselling the following cryptocurrency.

### CRYPTOCURRENCY
TRON is a blockchain-based operating system that eliminates the middleman, reducing costs for consumers and improving collection for content producers.

### QUESTION
who founded the roanoke settlement?

### ANSWER

Usage

base_model_name = "meta-llama/Llama-2-7b-chat-hf"

bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.bfloat16,
)

base_model = AutoModelForCausalLM.from_pretrained(
    base_model_name,
    quantization_config=bnb_config,
    device_map="auto",
    trust_remote_code=True,
)

model = PeftModel.from_pretrained(base_model, "mkly/crypto-sales")