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--- |
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license: apache-2.0 |
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datasets: |
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- timdettmers/openassistant-guanaco |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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## Anacondia |
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Anacondia-70m is a Pythia-70m-deduped model fine-tuned with QLoRA on [timdettmers/openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) |
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## Usage |
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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. |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- load_in_8bit: False |
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- load_in_4bit: True |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: nf4 |
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- bnb_4bit_use_double_quant: True |
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- bnb_4bit_compute_dtype: bfloat16 |
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### Framework versions |
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- PEFT 0.4.0 |
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## Inference |
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```python |
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#import necessary modules |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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model_id = "UncleanCode/anacondia-70m" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained(model_id) |
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input= tokenizer("This is a sentence ",return_tensors="pt") |
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output= model.generate(**input) |
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tokenizer.decode(output[0]) |
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``` |
