---
license: apache-2.0
datasets:
- timdettmers/openassistant-guanaco
language:
- en
pipeline_tag: text-generation
---
## Anacondia
Anacondia-70m is a Pythia-70m-deduped model fine-tuned with QLoRA on [timdettmers/openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco)

## Usage
Anacondia is not intended for any downstream usage and was trained for educational purposes. Please consider more serious models for inference if this doesn't fall into your usage aim.

## Training procedure


The following `bitsandbytes` quantization config was used during training:
- 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: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions


- PEFT 0.4.0

## Inference

```python

#import necessary modules
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "UncleanCode/anacondia-70m"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

input= tokenizer("This is a sentence ",return_tensors="pt")
output= model.generate(**input)

tokenizer.decode(output[0])

```