Update README.md

README.md

@@ -4,44 +4,64 @@ base_model:
 - cognitivecomputations/dolphin-2.8-mistral-7b-v02
 library_name: transformers
 tags:
-- mergekit
-- merge
-
+- code
+- instruct
+- llm
+- 7b
+- dolphin
+license: apache-2.0
+datasets:
+- cognitivecomputations/dolphin
+language:
+- en
 ---
-# model
-
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
-
-## Merge Details
-### Merge Method
-
-This model was merged using the SLERP merge method.
-
-### Models Merged
-
-The following models were included in the merge:
-* [arcee-ai/sec-mistral-7b-instruct-1.6-epoch](https://huggingface.co/arcee-ai/sec-mistral-7b-instruct-1.6-epoch)
-* [cognitivecomputations/dolphin-2.8-mistral-7b-v02](https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02)
-
-### Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-slices:
-  - sources:
-      - model: arcee-ai/sec-mistral-7b-instruct-1.6-epoch
-        layer_range: [0, 32]
-      - model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
-        layer_range: [0, 32]
-merge_method: slerp
-base_model: cognitivecomputations/dolphin-2.8-mistral-7b-v02
-parameters:
-  t:
-    - filter: self_attn
-      value: [0, 0.5, 0.3, 0.7, 1]
-    - filter: mlp
-      value: [1, 0.5, 0.7, 0.3, 0]
-    - value: 0.5
-dtype: bfloat16
+  # Dolphin Mistral Instruct
+
+  This is a custom language model created using the "SLERP" method
+
+  ### Models based on
+
+  The following models were used to create this language model:
+
+  - [arcee-ai/sec-mistral-7b-instruct-1.6-epoch](https://huggingface.co/arcee-ai/sec-mistral-7b-instruct-1.6-epoch)
+  - [cognitivecomputations/dolphin-2.8-mistral-7b-v02](https://huggingface.co/cognitivecomputations/dolphin-2.8-mistral-7b-v02)
+
+  ### Configuration
+
+  The following configuration was used to produce this model:
+
+  ```yaml
+  base_model:
+  - arcee-ai/sec-mistral-7b-instruct-1.6-epoch
+  - cognitivecomputations/dolphin-2.8-mistral-7b-v02
+
+  library_name: transformers
+
+  dtype: bfloat16
+  ```
+
+## Usage
+This model uses SafeTensors files and can be loaded and used with the Transformers library. Here's an example of how to load and generate text with the model using Transformers and Python:
+```
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "path/to/model"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+
+input_text = "Write a short story about"
+input_ids = tokenizer.encode(input_text, return_tensors="pt").to(model.device)
+
+output_ids = model.generate(
+    input_ids,
+    max_length=200,
+    do_sample=True,
+    top_k=50,
+    top_p=0.95,
+    num_return_sequences=1,
+)
+
+output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+print(output_text)
 ```
+Make sure to replace "path/to/model" with the actual path to your model's directory.