chore: fix precommit

crates/ggml/src/format/gguf/metadata.rs

@@ -79,13 +79,13 @@ impl Metadata {
     // TODO: consider finding a way to automate getting with traits
     pub fn get_str(&self, key: &str) -> Result<&str, MetadataError> {
         let metadata_value = self.get(key)?;
-        Ok(metadata_value
+        metadata_value
             .as_string()
             .ok_or_else(|| MetadataError::InvalidType {
                 key: key.to_string(),
                 expected_type: MetadataValueType::String,
                 actual_type: metadata_value.value_type(),
-            })?)
+            })
     }
 
     pub fn get_countable(&self, key: &str) -> Result<usize, MetadataError> {
@@ -460,6 +460,10 @@ impl MetadataArrayValue {
             _ => None,
         }
     }
+
+    pub fn is_empty(&self) -> bool {
+        self.len() == 0
+    }
 }
 
 // Shared

crates/ggml/src/format/gguf/mod.rs

@@ -253,7 +253,7 @@ impl TensorInfo {
             util::write_length(writer, ctx.use_64_bit_length, *dimension)?;
         }
 
-        util::write_u32(writer, ggml_type::from(self.element_type) as u32)?;
+        util::write_u32(writer, ggml_type::from(self.element_type))?;
         util::write_u64(writer, self.offset)?;
 
         Ok(())

crates/llm-base/src/loader.rs

@@ -39,8 +39,7 @@ impl TryFrom<llama_ftype> for FileType {
     type Error = llama_ftype;
 
     fn try_from(value: llama_ftype) -> Result<Self, Self::Error> {
-        let format =
-            FileTypeFormat::try_from(((value as u32) % ggml::QNT_VERSION_FACTOR) as llama_ftype)?;
+        let format = FileTypeFormat::try_from((value % ggml::QNT_VERSION_FACTOR) as llama_ftype)?;
 
         Ok(Self {
             format,
@@ -360,7 +359,7 @@ pub trait ModelFactory {
 /// This method returns a [`Box`], which means that the model will have single ownership.
 /// If you'd like to share ownership (i.e. to use the model in multiple threads), we
 /// suggest using [`Arc::from(Box<T>)`](https://doc.rust-lang.org/std/sync/struct.Arc.html#impl-From%3CBox%3CT,+Global%3E%3E-for-Arc%3CT%3E)
-/// to convert the [`Box`] into an [`Arc`](std::sync::Arc) after loading.
+/// to convert the [`Box`] into an [`Arc`] after loading.
 pub fn load(
     path: &Path,
     tokenizer_source: TokenizerSource,

crates/llm-base/src/tokenizer/embedded.rs

@@ -497,6 +497,7 @@ fn unescape_whitespace(text: &[u8]) -> Vec<u8> {
     let mut buffer: Vec<u8> = vec![];
 
     for &b in text {
+        #[allow(clippy::if_same_then_else)]
         if b == 0xE2 {
             // If the current byte is 0xE2, start buffering and check for the sequence.
             buffer.push(b);

crates/llm-base/src/tokenizer/mod.rs

@@ -118,7 +118,7 @@ impl TokenizerSource {
                         tokenizer_source: HuggingFaceTokenizerErrorSource::Remote(
                             identifier.clone(),
                         ),
-                        error: error.into(),
+                        error,
                     }
                 })?,
             )
@@ -128,7 +128,7 @@ impl TokenizerSource {
                 tokenizers::Tokenizer::from_file(&path).map_err(|error| {
                     TokenizerLoadError::HuggingFaceTokenizerError {
                         tokenizer_source: HuggingFaceTokenizerErrorSource::File(path.clone()),
-                        error: error.into(),
+                        error,
                     }
                 })?,
             )
@@ -139,20 +139,18 @@ impl TokenizerSource {
             Self::Embedded => {
                 if let Ok(hf) = gguf.metadata.get_str("tokenizer.huggingface.json") {
                     Ok(Self::load_huggingface_json(hf)?)
-                } else {
-                    if EmbeddedTokenizer::is_present_in_metadata(&gguf.metadata) {
-                        if EMBEDDED_TOKENIZER_ENABLED {
-                            Ok(EmbeddedTokenizer::from_metadata(&gguf.metadata)?.into())
-                        } else {
-                            Err(TokenizerLoadError::NoSupportedTokenizersFound {
-                                unsupported_tokenizers: vec!["embedded".to_owned()],
-                            })
-                        }
+                } else if EmbeddedTokenizer::is_present_in_metadata(&gguf.metadata) {
+                    if EMBEDDED_TOKENIZER_ENABLED {
+                        Ok(EmbeddedTokenizer::from_metadata(&gguf.metadata)?.into())
                     } else {
                         Err(TokenizerLoadError::NoSupportedTokenizersFound {
-                            unsupported_tokenizers: vec![],
+                            unsupported_tokenizers: vec!["embedded".to_owned()],
                         })
                     }
+                } else {
+                    Err(TokenizerLoadError::NoSupportedTokenizersFound {
+                        unsupported_tokenizers: vec![],
+                    })
                 }
             }
         }
@@ -163,7 +161,7 @@ impl TokenizerSource {
             HuggingFaceTokenizer::new(tokenizers::Tokenizer::from_str(tokenizer_json).map_err(
                 |error| TokenizerLoadError::HuggingFaceTokenizerError {
                     tokenizer_source: HuggingFaceTokenizerErrorSource::String,
-                    error: error.into(),
+                    error,
                 },
             )?)
             .into(),

crates/llm/Cargo.toml

@@ -36,7 +36,7 @@ default = ["models", "tokenizers-remote"]
 
 tokenizers-remote = ["llm-base/tokenizers-remote"]
 
-models = ["llama", "gptneox"] #, "gpt2", "gptj", "bloom", "mpt", "bert"]
+models = ["llama", "gptneox", "gpt2", "gptj", "bloom", "mpt", "bert"]
 llama = ["dep:llm-llama"]
 gpt2 = ["dep:llm-gpt2"]
 gptj = ["dep:llm-gptj"]

crates/llm/examples/embeddings.rs

@@ -104,7 +104,7 @@ fn main() {
 
 fn get_embeddings(
     model: &dyn llm::Model,
-    inference_parameters: &llm::InferenceParameters,
+    _inference_parameters: &llm::InferenceParameters,
     query: &str,
 ) -> Vec<f32> {
     let mut session = model.start_session(Default::default());

crates/llm/src/lib.rs

@@ -7,6 +7,7 @@
 //! - [GPT-NeoX](llm_gptneox)
 //! - [LLaMA](llm_llama)
 //! - [MPT](llm_mpt)
+//! - [BERT](llm_bert)
 //! - Falcon (currently disabled due to incompleteness)
 //!
 //! At present, the only supported backend is [GGML](https://github.com/ggerganov/ggml), but this is expected to
@@ -19,7 +20,7 @@
 //! use llm::Model;
 //!
 //! // load a GGML model from disk
-//! let llama = llm::load::<llm::models::Llama>(
+//! let llama = llm::load(
 //!     // path to GGML file
 //!     std::path::Path::new("/path/to/model"),
 //!     // llm::TokenizerSource
@@ -35,7 +36,7 @@
 //! let mut session = llama.start_session(Default::default());
 //! let res = session.infer::<std::convert::Infallible>(
 //!     // model to use for text generation
-//!     &llama,
+//!     llama.as_ref(),
 //!     // randomness provider
 //!     &mut rand::thread_rng(),
 //!     // the prompt to use for text generation, as well as other
@@ -94,7 +95,7 @@ pub use loader::{load, load_progress_callback_stdout, LoadError, LoadProgress};
 use serde::Serialize;
 
 macro_rules! define_models {
-    ($(($model_lowercase:ident, $model_lowercase_str:literal, $model_pascalcase:ident, $krate_ident:ident, $display_name:literal)),*) => {
+    ($(($model_lowercase:ident, $model_lowercase_str:literal, $model_pascalcase:ident, $krate_ident:ident, $display_name:literal),)*) => {
         /// All available models.
         pub mod models {
             $(
@@ -173,14 +174,14 @@ macro_rules! define_models {
 }
 
 define_models!(
-    (bert, "bert", Bert, llm_bert, "Bert"),
-    (bloom, "bloom", Bloom, llm_bloom, "BLOOM"),
-    (gpt2, "gpt2", Gpt2, llm_gpt2, "GPT-2"),
-    (gptj, "gptj", GptJ, llm_gptj, "GPT-J"),
+    // (bert, "bert", Bert, llm_bert, "Bert"),
+    // (bloom, "bloom", Bloom, llm_bloom, "BLOOM"),
+    // (gpt2, "gpt2", Gpt2, llm_gpt2, "GPT-2"),
+    // (gptj, "gptj", GptJ, llm_gptj, "GPT-J"),
     (gptneox, "gptneox", GptNeoX, llm_gptneox, "GPT-NeoX"),
     (llama, "llama", Llama, llm_llama, "LLaMA"),
-    (mpt, "mpt", Mpt, llm_mpt, "MPT"),
-    (falcon, "falcon", Falcon, llm_falcon, "Falcon")
+    // (mpt, "mpt", Mpt, llm_mpt, "MPT"),
+    // (falcon, "falcon", Falcon, llm_falcon, "Falcon"),
 );
 
 /// Used to dispatch some code based on the model architecture.

crates/llm/src/loader.rs

@@ -23,13 +23,13 @@ pub fn load(
     params: ModelParameters,
     load_progress_callback: impl FnMut(LoadProgress),
 ) -> Result<Box<dyn Model>, LoadError> {
-    Ok(llm_base::loader::load(
+    llm_base::loader::load(
         path,
         tokenizer_source,
         params,
         VisitorModelFactory,
         load_progress_callback,
-    )?)
+    )
 }
 
 struct VisitorModelFactory;