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--- |
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license: other |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: conversational |
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--- |
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## Model Card for Model ID |
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Finetuned depacoda-research/llamma-13b-hf on conversations |
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## Model Details |
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### Model Description |
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The depacoda-research/llamma-13b-hf model was finetuned on conversations and question answering prompts |
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**Developed by:** [More Information Needed] |
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**Shared by:** [More Information Needed] |
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**Model type:** Causal LM |
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**Language(s) (NLP):** English, multilingual |
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**License:** Research |
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**Finetuned from model:** depacoda-research/llamma-13b-hf |
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## Model Sources [optional] |
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**Repository:** [More Information Needed] |
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**Paper:** [More Information Needed] |
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**Demo:** [More Information Needed] |
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## Uses |
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The model can be used for prompt answering |
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### Direct Use |
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The model can be used for prompt answering |
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### Downstream Use |
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Generating text and prompt answering |
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## Recommendations |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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``` |
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from transformers import LlamaTokenizer, LlamaForCausalLM |
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from peft import PeftModel |
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MODEL_NAME = "decapoda-research/llama-13b-hf" |
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tokenizer = LlamaTokenizer.from_pretrained(MODEL_NAME, add_eos_token=True) |
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tokenizer.pad_token_id = 0 |
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model = LlamaForCausalLM.from_pretrained(MODEL_NAME, load_in_8bit=True, device_map="auto") |
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model = PeftModel.from_pretrained(model, "Sandiago21/public-ai-model") |
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``` |
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## Training Details |
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### Training Data |
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The decapoda-research/llama-13b-hf was finetuned on conversations and question answering data |
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### Training Procedure |
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The decapoda-research/llama-13b-hf model was further trained and finetuned on question answering and prompts data |
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## Model Architecture and Objective |
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The model is based on decapoda-research/llama-13b-hf model and finetuned adapters on top of the main model on conversations and question answering data. |
