Update README.md

README.md

@@ -1,30 +1,60 @@
 ---
+inference: false
 tags:
 - generated_from_trainer
 model-index:
 - name: no-robots-lora-out
   results: []
+license: cc-by-nc-4.0
+datasets:
+- HuggingFaceH4/no_robots
+- Doctor-Shotgun/no-robots-sharegpt
+language:
+- en
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
-# no-robots-lora-out
+# no-robots-y34b-lora
+
+This model is a Yi-34B-Llama training on the [HuggingFaceH4/no_robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots). It uses my converted dataset in ShareGPT format with a few minor corrections (https://huggingface.co/datasets/Doctor-Shotgun/no-robots-sharegpt).
 
-This model was trained from scratch on the None dataset.
+The [Yi-34B-Llama](https://huggingface.co/chargoddard/Yi-34B-Llama) model is a modified [01-ai/Yi-34B](https://huggingface.co/01-ai/Yi-34B) with keys renamed to match those used in Llama models, eliminating the need for remote code and ensuring compatibility with existing training and inference repositories. Architecturally this is similar to a Llama 2 34B model with an expanded vocab size of 64000.
 
 ## Model description
 
-More information needed
+No Robots is a high-quality dataset of 10,000 instructions and demonstrations created by skilled human annotators. This data can be used for supervised fine-tuning (SFT) to make language models follow instructions better. No Robots was modelled after the instruction dataset described in OpenAI's [InstructGPT paper](https://huggingface.co/papers/2203.02155), and is comprised mostly of single-turn instructions across the following categories:
 
-## Intended uses & limitations
+| Category   |   Count |
+|:-----------|--------:|
+| Generation |    4560 |
+| Open QA    |    1240 |
+| Brainstorm |    1120 |
+| Chat       |     850 |
+| Rewrite    |     660 |
+| Summarize  |     420 |
+| Coding     |     350 |
+| Classify   |     350 |
+| Closed QA  |     260 |
+| Extract    |     190 |
+
+This lora was trained using a modified multi-turn Alpaca prompt format:
+
+```
+### Instruction:
+Below is a message that describes a task. Write a response that appropriately completes the request.
+
+### Input:
+{human prompt}
 
-More information needed
+### Response:
+{bot response}
+```
 
-## Training and evaluation data
+Some chat examples have alternate system prompts that differ from the default provided above.
 
-More information needed
+## Intended uses & limitations
+
+The intended use is to add instruction-following capabilities to the base model based on curated human examples. Outputs may exhibit biases observed in the base model, and have not been filtered for explicit or harmful content and hallucinations.
 
 ## Training procedure
 
@@ -42,13 +72,22 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_steps: 10
 - num_epochs: 3
 
-### Training results
-
-
-
 ### Framework versions
 
 - Transformers 4.34.1
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.6
 - Tokenizers 0.14.1
+
+### Citation data
+
+```
+@misc{no_robots,
+  author = {Nazneen Rajani and Lewis Tunstall and Edward Beeching and Nathan Lambert and Alexander M. Rush and Thomas Wolf},
+  title = {No Robots},
+  year = {2023},
+  publisher = {Hugging Face},
+  journal = {Hugging Face repository},
+  howpublished = {\url{https://huggingface.co/datasets/HuggingFaceH4/no_robots}}
+}
+```