Update README.md

README.md

@@ -1,3 +1,63 @@
 ---
 license: cc-by-sa-3.0
+inference: false
+language:
+- en
+library_name: transformers
+pipeline_tag: text2text-generation
+datasets:
+- pszemraj/dolly_hhrlhf-text2text
+tags:
+- instruct
 ---
+
+# bart-base-instruct: dolly_hhrlhf
+
+This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the pszemraj/dolly_hhrlhf-text2text dataset.
+
+## Model description
+
+text2text models fine-tuned on a [modified dataset for text2text generation](https://huggingface.co/datasets/pszemraj/dolly_hhrlhf-text2text)  based on the relatively more permissive  [mosaicml/dolly_hhrlhf](https://huggingface.co/datasets/mosaicml/dolly_hhrlhf) dataset.
+
+Basic usage in Python:
+
+```python
+# pip install -q transformers accelerate
+from transformers import pipeline, GenerationConfig
+
+model_name = "pszemraj/bart-base-instruct-dolly_hhrlhf"
+assistant = pipeline(
+    "text2text-generation",
+    model_name,
+    device_map="auto"
+)
+cfg = GenerationConfig.from_pretrained(model_name)
+
+# pass an 'instruction' as the prompt to the pipeline
+prompt = "Write a guide on how to become a ninja while working a 9-5 job."
+result = assistant(prompt, generation_config=cfg)[0]["generated_text"]
+print(result)
+```
+> using the generation config is optional, can subsitute with other generation params.
+
+## Intended uses & limitations
+
+- this is **not** tuned with RLHF etc, and may output offensive results
+- this model is rather small (~600 MB) and therefore it's "cognition" abilities are rather limited.
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 4e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 3.0