Update README.md

README.md

@@ -8,198 +8,41 @@ base_model:
 - deepseek-ai/DeepSeek-R1
 ---
 
-# Model Card for Model ID
+# DeepTolkien
 
 This LLM is an OpenSeek R1 fine-tuned using the LoRA method on text extracted from JRR Tolkien's The Lord of the Rings. 
 
 ## Model Details
 
-### Model Description
-
 This LLM is an OpenSeek R1 fine-tuned using the LoRA method on text extracted from JRR Tolkien's The Lord of the Rings.  The model can be prompted with a stub, for example "Frodo looked up and saw", and will then generate a story in the style of Tolkien's writing that continues from this stub.  Have fun!
 
 If you have played with OpenSeek R1, you have almost certainly noticed that at times the reasoning model seems to get caught up in a loop.  This behavior is also seen here:  for example, two characters will get caught in a looping dialog.  I believe this is more of a property of DeepSeek R1 than this LoRA, and better results may yet be achieved through a model specific to prose and storytelling.  However, I wanted to get an idea of how the new DeepSeek models perform, and this has been a fantastic learning experience.  
 
+## Usage
+
+### Load the model:
+```
+# Import the model
+config = PeftConfig.from_pretrained("cwestbrook/lotrdata")
+model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=True, load_in_8bit=True, device_map='auto')
+tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
+# Load the Lora model
+model = PeftModel.from_pretrained(model, "cwestbrook/lotrdata")
+```
+
+### Run the model:
+```
+prompt = "Gandalf revealed his new iphone,"
+inputs = tokenizer(prompt, return_tensors="pt").to('cuda')
+tokens = model.generate(
+    **inputs,
+    max_new_tokens=100,
+    temperature=1,
+    eos_token_id=tokenizer.eos_token_id,
+    early_stopping=True
+)
+predictions = tokenizer.batch_decode(tokens, skip_special_tokens=True)
+print(predictions[0])
+```
 
 This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** Christian Westbrook
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
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-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-[More Information Needed]
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-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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-[More Information Needed]
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-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-[More Information Needed]
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-### Training Procedure
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-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
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-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-[More Information Needed]
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-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
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-<!-- This should link to a Dataset Card if possible. -->
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-[More Information Needed]
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-#### Factors
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-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-#### Metrics
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-### Results
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-[More Information Needed]
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-#### Summary
-
-
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-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
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-### Compute Infrastructure
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-[More Information Needed]
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-#### Hardware
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-[More Information Needed]
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-#### Software
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-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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-**BibTeX:**
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-[More Information Needed]
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-**APA:**
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-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-## More Information [optional]
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-## Model Card Authors [optional]
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-## Model Card Contact
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