diff --git a/src/batchview.jl b/src/batchview.jl
index a26bd5b..2529206 100644
--- a/src/batchview.jl
+++ b/src/batchview.jl
@@ -95,7 +95,7 @@ struct BatchView{TElem,TData,TCollate} <: AbstractDataContainer
     batchsize::Int
     count::Int
     partial::Bool
-    collate::TCollate
+    collate::TCollate # either Val(nothing), Val(false), or a function
 end
 
 function BatchView(data::T; batchsize::Int=1, partial::Bool=true, collate=Val(nothing)) where {T}
diff --git a/src/eachobs.jl b/src/eachobs.jl
index b8e908d..3c582e2 100644
--- a/src/eachobs.jl
+++ b/src/eachobs.jl
@@ -60,7 +60,7 @@ The original data is preserved in the `data` field of the DataLoader.
   containing `batchsize` observations. Default `1`.
 - **`buffer`**: If `buffer=true` and supported by the type of `data`,
   a buffer will be allocated and reused for memory efficiency.
-  You can also pass a preallocated object to `buffer`. Default `false`.
+  May want to set `partial=false` to avoid size mismatch. Default `false`. 
 - **`collate`**: Defines the batching behavior. Default `nothing`. 
   - If `nothing` , a batch is `getobs(data, indices)`. 
   - If `false`, each batch is `[getobs(data, i) for i in indices]`. 
@@ -147,15 +147,14 @@ end
 
 function DataLoader(
         data;
-        buffer = false,
-        parallel = false,
-        shuffle = false,
+        buffer::Bool = false,
+        parallel::Bool = false,
+        shuffle::Bool = false,
         batchsize::Int = 1,
         partial::Bool = true,
         collate = Val(nothing),
         rng::AbstractRNG = Random.default_rng())
 
-    buffer = buffer isa Bool ? buffer : true
     if collate isa Bool || collate === nothing
         collate = Val(collate)
     end