updated model card

README.md

@@ -0,0 +1,85 @@
+---
+language:
+- en
+tags:
+- text-generation-inference
+license: llama2
+---
+
+# Model Card for LLaMA 2 Spell Generation
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This model is a fine-tuned **llama-2-13b** model for the generation of *D&D 5th edition spells*
+
+- **Language(s) (NLP):** English
+- **Finetuned from model:** [llama-2-13b](https://huggingface.co/meta-llama/Llama-2-13b-hf)
+- **Dataset used for fine-tuning:** [m-elio/spell_generation](https://huggingface.co/datasets/m-elio/spell_generation)
+
+## Prompt Format
+
+This prompt format based on the Alpaca model was used for fine-tuning:
+
+```python
+"Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n" \
+f"### Instruction:\n{instruction}\n\n### Response:\n{response}"
+```
+
+It is recommended to use the same prompt in inference to obtain the best results!
+
+## Output Format
+
+The output format for a generated spell should be the following:
+
+```
+Name: 
+Level: 
+School: 
+Classes: 
+Casting time: 
+Range: 
+Duration:
+Components: [If no components are required, then this field has a None value]
+Material cost: [If there is no "M" character in the Components field, then this field is skipped]
+Description:
+```
+
+Example:
+
+```
+Name: The Shadow
+Level: 1
+School: Evocation
+Classes: Bard, Cleric, Druid, Ranger, Sorcerer, Warlock, Wizard
+Casting time: 1 Action
+Range: Self
+Duration: Concentration, Up To 1 Minute
+Components: V, S, M
+Material cost: a small piece of cloth
+Description: You touch a creature within range. The target must make a Dexterity saving throw. On a failed save, the target takes 2d6 psychic damage and is charmed by you. On a successful save, the target takes half as much damage.
+At Higher Levels. When you cast this spell using a spell slot of 4th level or higher, the damage increases by 1d6 for each slot level above 1st.
+```
+
+## Example use
+
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "m-elio/spell_generation_llama-2-13b"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+
+instruction = "Write a spell for the 5th edition of the Dungeons & Dragons game."
+
+prompt = "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n" \
+f"### Instruction:\n{instruction}\n\n### Response:\n"
+
+tokenized_input = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**tokenized_input, max_length=512)
+
+print(tokenizer.batch_decode(outputs.detach().cpu().numpy()[:, tokenized_input.input_ids.shape[1]:], skip_special_tokens=True)[0])
+```