Update README.md

README.md

@@ -72,7 +72,7 @@ If you are looking for the finetuned model, please use [DBRX Instruct](https://h
 Getting started with DBRX models is easy with the `transformers` library. The model requires ~264GB of RAM and the following packages:
 
 ```bash
-pip install transformers tiktoken
+pip install "transformers>=4.39.2" "tiktoken>=0.6.0"
 ```
 
 If you'd like to speed up download time, you can use the `hf_transfer` package as described by Huggingface [here](https://huggingface.co/docs/huggingface_hub/en/guides/download#faster-downloads).
@@ -81,13 +81,16 @@ pip install hf_transfer
 export HF_HUB_ENABLE_HF_TRANSFER=1
 ```
 
+You will need to request access to this repository to download the model. Once this is granted, 
+[obtain an access token](https://huggingface.co/docs/hub/en/security-tokens) with `read` permission, and supply the token below.
+
 ### Run the model on a CPU:
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-tokenizer = AutoTokenizer.from_pretrained("Undi95/dbrx-base", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("Undi95/dbrx-base", device_map="cpu", torch_dtype=torch.bfloat16, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("Undi95/dbrx-base", trust_remote_code=True, token="hf_YOUR_TOKEN")
+model = AutoModelForCausalLM.from_pretrained("Undi95/dbrx-base", device_map="cpu", torch_dtype=torch.bfloat16, trust_remote_code=True, token="hf_YOUR_TOKEN")
 
 input_text = "Databricks was founded in "
 input_ids = tokenizer(input_text, return_tensors="pt")
@@ -101,8 +104,8 @@ print(tokenizer.decode(outputs[0]))
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-tokenizer = AutoTokenizer.from_pretrained("Undi95/dbrx-base", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("Undi95/dbrx-base", device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained("Undi95/dbrx-base", trust_remote_code=True, token="hf_YOUR_TOKEN")
+model = AutoModelForCausalLM.from_pretrained("Undi95/dbrx-base", device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True, token="hf_YOUR_TOKEN")
 
 input_text = "Databricks was founded in "
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
@@ -170,4 +173,4 @@ Full evaluation details can be found in our [technical blog post](https://www.da
 ## Acknowledgements
 The DBRX models were made possible thanks in large part to the open-source community, especially:
 * The [MegaBlocks](https://arxiv.org/abs/2211.15841) library, which established a foundation for our MoE implementation.
-* [PyTorch FSDP](https://arxiv.org/abs/2304.11277), which we built on for distributed training.
+* [PyTorch FSDP](https://arxiv.org/abs/2304.11277), which we built on for distributed training.