README.md

---
library_name: peft
license: mit
datasets:
- mkly/crypto-sales-question-answers
language:
- en
---

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

An adapter for the [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) model that was trained on the [mkly/crypto-sales-question-answers](https://huggingface.co/datasets/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

```python
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")
```