Support for slerp merging models (#455)

* support for slerp merging models

* docs

* update docs

* format'

llms/README.md

@@ -14,9 +14,11 @@ pip install mlx-lm
 conda install -c conda-forge mlx-lm
 ```
 
-The `mlx-lm` package also supports LoRA and QLoRA fine-tuning. For more details
-on this see the [LoRA
-documentation](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/LORA.md).
+The `mlx-lm` package also has:
+
+- [LoRA and QLoRA fine-tuning](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/LORA.md)
+- [Merging models](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/MERGE.md)
+- [HTTP model serving](https://github.com/ml-explore/mlx-examples/blob/main/llms/mlx_lm/SERVER.md)
 
 ### Python API
 
@@ -25,7 +27,7 @@ You can use `mlx-lm` as a module:
 ```python
 from mlx_lm import load, generate
 
-model, tokenizer = load("mistralai/Mistral-7B-v0.1")
+model, tokenizer = load("mistralai/Mistral-7B-Instruct-v0.1")
 
 response = generate(model, tokenizer, prompt="hello", verbose=True)
 ```
@@ -44,7 +46,7 @@ You can convert models in the Python API with:
 ```python
 from mlx_lm import convert
 
-upload_repo = "mlx-community/My-Mistral-7B-v0.1-4bit"
+upload_repo = "mistralai/Mistral-7B-Instruct-v0.1"
 
 convert("mistralai/Mistral-7B-v0.1", quantize=True, upload_repo=upload_repo)
 ```
@@ -64,7 +66,7 @@ To see a description of all the arguments you can do:
 You can also use `mlx-lm` from the command line with:
 
 ```
-python -m mlx_lm.generate --model mistralai/Mistral-7B-v0.1 --prompt "hello"
+python -m mlx_lm.generate --model mistralai/Mistral-7B-Instruct-v0.1 --prompt "hello"
 ```
 
 This will download a Mistral 7B model from the Hugging Face Hub and generate
@@ -79,7 +81,7 @@ python -m mlx_lm.generate --help
 To quantize a model from the command line run:
 
 ```
-python -m mlx_lm.convert --hf-path mistralai/Mistral-7B-v0.1 -q
+python -m mlx_lm.convert --hf-path mistralai/Mistral-7B-Instruct-v0.1 -q
 ```
 
 For more options run: