Update README.md (#1)

- Update README.md (24a17449797bac71210a9d123a3299cdf18fb7f3)

README.md

@@ -4,10 +4,16 @@ library_name: peft
 tags:
 - axolotl
 - generated_from_trainer
+- mixtral
+- nous_hermes
+- wikihow
 base_model: NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT
 model-index:
 - name: Nous-Hermes-2-Mixtral-8x7B-SFT-Wikihow
   results: []
+datasets:
+- HuggingFaceTB/cosmopedia
+pipeline_tag: text-generation
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -23,21 +29,12 @@ model_type: MixtralForCausalLM
 tokenizer_type: LlamaTokenizer
 trust_remote_code: true
 
-# hub_model_id: MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Function-Calling
 hub_model_id: MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Wikihow
 hf_use_auth_token: true
 
 load_in_4bit: true
 strict: false
 
-# datasets:
-#   - path: Arist12/EABF-ShareGPT-Long-3.5k
-#     type: sharegpt
-#     conversation: chatml
-# datasets:
-#   - path: hypervariance/function-calling-sharegpt
-#     type: sharegpt
-#     conversation: chatml
 datasets:
   - path: HuggingFaceTB/cosmopedia
     name:
@@ -131,6 +128,36 @@ This model is a fine-tuned version of [NousResearch/Nous-Hermes-2-Mixtral-8x7B-S
 It achieves the following results on the evaluation set:
 - Loss: 0.4559
 
+## How to use
+
+**PEFT**
+```python
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM
+
+model_id = "MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Wikihow"
+
+config = PeftConfig.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT")
+model = PeftModel.from_pretrained(model, model_id)
+```
+
+**Transformers**
+```python
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+model_id = "MaziyarPanahi/Nous-Hermes-2-Mixtral-8x7B-SFT-Wikihow"
+
+pipe = pipeline("text-generation", model=model_id)
+
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+```
+
 ## Model description
 
 More information needed