helloadhavan/github_issues huggingface dataset:
Repository: ollama/ollama
Pull request: llm: Check for nil memory data before printing

We dump out our best memory estimate after we complete processing for any reason, including errors. This is helpful for finding what what stopped us in error conditions but in some cases we might not have gotten even the first result yet.

Fixes #11957

Changed files:
filename: llm/server.go
patch: @@ -651,7 +651,9 @@ func (s *ollamaServer) Load(ctx context.Context, gpus discover.GpuInfoList, requ
 		if !success {
 			s.initModel(ctx, LoadRequest{}, LoadOperationClose)
 		}
-		s.mem.Log(slog.LevelInfo)
+		if s.mem != nil {
+			s.mem.Log(slog.LevelInfo)
+		}
 	}()
 
 	slog.Info("loading model", "model layers", s.totalLayers, "requested", s.options.NumGPU)
Repository: ggml-org/llama.cpp
Pull request: memory : use sequential equal splits for recurrent modules

fix #16278

Split KV cache requires the sequence ids in an ubatch to be sequential. Update the recurrent memory modules to satisfy this requirement.

Changed files:
filename: src/llama-memory-hybrid.cpp
patch: @@ -73,7 +73,9 @@ llama_memory_context_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & ba
                 // if all tokens are output, split by sequence
                 ubatch = balloc.split_seq(n_ubatch);
             } else {
-                ubatch = balloc.split_equal(n_ubatch, false);
+                // TODO: non-sequential equal split can be done if using unified KV cache
+                //       for simplicity, we always use sequential equal split for now
+                ubatch = balloc.split_equal(n_ubatch, true);
             }
 
             if (ubatch.n_tokens == 0) {

filename: src/llama-memory-recurrent.cpp
patch: @@ -382,7 +382,9 @@ llama_memory_context_ptr llama_memory_recurrent::init_batch(llama_batch_allocr &
                 // if all tokens are output, split by sequence
                 ubatch = balloc.split_seq(n_ubatch);
             } else {
-                ubatch = balloc.split_equal(n_ubatch, false);
+                // TODO: non-sequential equal split can be done if using unified KV cache
+                //       for simplicity, we always use sequential equal split for now
+                ubatch = balloc.split_equal(n_ubatch, true);
             }
 
             if (ubatch.n_tokens == 0) {
Repository: huggingface/transformers
Pull request: update python requirement to 3.10+ to match codebase

Fixes #43976

Updated the documentation to reflect the actual Python requirement (3.10+) as defined in setup.py.

Changes:

Updated README.md .

Changed files:
filename: README.md
patch: @@ -81,7 +81,7 @@ Explore the [Hub](https://huggingface.com/) today to find a model and use Transf
 
 ## Installation
 
-Transformers works with Python 3.9+, and [PyTorch](https://pytorch.org/get-started/locally/) 2.4+.
+Transformers works with Python 3.10+, and [PyTorch](https://pytorch.org/get-started/locally/) 2.4+.
 
 Create and activate a virtual environment with [venv](https://docs.python.org/3/library/venv.html) or [uv](https://docs.astral.sh/uv/), a fast Rust-based Python package and project manager.
Repository: ggml-org/llama.cpp
Pull request: RPC GRAPH_COMPUTE Arbitrary RCE patch

This fix prevents an existing RCE chain where deserialize_tensor() skips all validations when the incoming rpce_tensor.buffer field is set to null. Currently we only check if result==null, however this does not sufficiently cover the case for result->buffer. This prevents attackers from gaining arbitrary read and write. 

Changed files:
filename: ggml/src/ggml-rpc/ggml-rpc.cpp
patch: @@ -1443,7 +1443,9 @@ ggml_tensor * rpc_server::create_node(uint64_t id,
     const rpc_tensor * tensor = it_ptr->second;
 
     struct ggml_tensor * result = deserialize_tensor(ctx, tensor);
-    if (result == nullptr) {
+    if (result == nullptr || result->buffer == nullptr) {
+        GGML_LOG_ERROR("[%s] invalid tensor: null %s (id=%" PRIu64 ")\n",
+                       __func__, result == nullptr ? "tensor" : "buffer", id);
         return nullptr;
     }
     tensor_map[id] = result;
Repository: ollama/ollama
Pull request: Add Serene Pub to community integrations

Hey!

Just want to share Serene Pub's new UI integration for Ollama. It's an open source AI role-play client that aims to be low-clutter and as easy as possible for beginners to get up and running. (Literally download, extract, run.)

https://github.com/doolijb/serene-pub

[Screenshots](https://github.com/doolijb/serene-pub?tab=readme-ov-file#ollama-manager)

Ollama was chosen as the preferred integration because it simply just works. The philosophy around Serene Pub is to make AI powered RP as accessible as possible to everyone regardless of what OS they use or skill-set they have. Ollama requires no tuning, extra dependencies or guess-work to get operational on user hardware.

- Opens as a feature-contained sidebar
- When Ollama is not detected, it provides the download link for Ollama
- One click model connection/activation
- Search available models
 - Recommended (from github repo)
 - Hugging face
 - Ollama (via [Ollama Models API (very limited)](https://github.com/frefrik/ollama-models-api))
- Download and delete models
- Manually paste ollama pull commands

Changed files:
filename: README.md
patch: @@ -411,6 +411,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [ollama launcher](https://github.com/NGC13009/ollama-launcher) (A launcher for Ollama, aiming to provide users with convenient functions such as ollama server launching, management, or configuration.)
 - [ai-hub](https://github.com/Aj-Seven/ai-hub) (AI Hub supports multiple models via API keys and Chat support via Ollama API.)
 - [Mayan EDMS](https://gitlab.com/mayan-edms/mayan-edms) (Open source document management system to organize, tag, search, and automate your files with powerful Ollama driven workflows.)
+- [Serene Pub](https://github.com/doolijb/serene-pub) (Beginner friendly, open source AI Roleplaying App for Windows, Mac OS and Linux. Search, download and use models with Ollama all inside the app.)
 
 ### Cloud
Repository: ollama/ollama
Pull request: gpt-oss: disable quantized kv cache

quantized kv cache for gpt-oss is much slower than with regular f16 cache type due to the model using attention with sinks. this isn't supported on backends such as cuda which forces it onto the cpu dramatically reducing performance

Changed files:
filename: fs/ggml/ggml.go
patch: @@ -752,6 +752,11 @@ func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
 
 // SupportsKVCacheType checks if the requested cache type is supported
 func (f GGML) SupportsKVCacheType(cacheType string) bool {
+	if arch := f.KV().Architecture(); slices.Contains([]string{"gptoss", "gpt-oss"}, arch) {
+		// gpt-oss uses attention with sinks which does not support quantized cache types
+		slog.Warn("model only supports non-quantized cache types ", "mode", arch)
+		return cacheType == "f16"
+	}
 	return slices.Contains([]string{"f16", "q8_0", "q4_0"}, cacheType)
 }
Repository: huggingface/transformers
Pull request: create .git-blame-ignore-revs file 

# What does this PR do?

This PR create a `.git-blame-ignore-revs` file to ignore the following commit https://github.com/huggingface/transformers/pull/43914 when using git blame. 

Changed files:
filename: .git-blame-ignore-revs
patch: @@ -0,0 +1 @@
+8008e6c83e1467dbe0ae3c81d19b29c17f4ff456
Repository: facebook/react
Pull request: [DevTools] Record Suspense node for roots in legacy renderers

Stacked on https://github.com/facebook/react/pull/34455

Mostly so that we don't trigger unnecessary warnings in older React versions.

We could avoid the additional capability in favor checking if the root exists in the Suspense tree but that may hide legit bugs.

Changed files:
filename: packages/react-devtools-shared/src/backend/legacy/renderer.js
patch: @@ -34,6 +34,8 @@ import {
   TREE_OPERATION_ADD,
   TREE_OPERATION_REMOVE,
   TREE_OPERATION_REORDER_CHILDREN,
+  SUSPENSE_TREE_OPERATION_ADD,
+  SUSPENSE_TREE_OPERATION_REMOVE,
   UNKNOWN_SUSPENDERS_NONE,
 } from '../../constants';
 import {decorateMany, forceUpdate, restoreMany} from './utils';
@@ -411,6 +413,13 @@ export function attach(
       pushOperation(0); // StrictMode supported?
       pushOperation(hasOwnerMetadata ? 1 : 0);
       pushOperation(supportsTogglingSuspense ? 1 : 0);
+
+      pushOperation(SUSPENSE_TREE_OPERATION_ADD);
+      pushOperation(id);
+      pushOperation(parentID);
+      pushOperation(getStringID(null)); // name
+      // TODO: Measure rect of root
+      pushOperation(-1);
     } else {
       const type = getElementType(internalInstance);
       const {displayName, key} = getData(internalInstance);
@@ -449,7 +458,12 @@ export function attach(
   }
 
   function recordUnmount(internalInstance: InternalInstance, id: number) {
-    pendingUnmountedIDs.push(id);
+    const isRoot = parentIDStack.length === 0;
+    if (isRoot) {
+      pendingUnmountedRootID = id;
+    } else {
+      pendingUnmountedIDs.push(id);
+    }
     idToInternalInstanceMap.delete(id);
   }
 
@@ -519,6 +533,8 @@ export function attach(
         // All unmounts are batched in a single message.
         // [TREE_OPERATION_REMOVE, removedIDLength, ...ids]
         (numUnmountIDs > 0 ? 2 + numUnmountIDs : 0) +
+        // [SUSPENSE_TREE_OPERATION_REMOVE, 1, pendingUnmountedRootID]
+        (pendingUnmountedRootID === null ? 0 : 3) +
         // Mount operations
         pendingOperations.length,
     );
@@ -555,6 +571,10 @@ export function attach(
       if (pendingUnmountedRootID !== null) {
         operations[i] = pendingUnmountedRootID;
         i++;
+
+        operations[i++] = SUSPENSE_TREE_OPERATION_REMOVE;
+        operations[i++] = 1;
+        operations[i++] = pendingUnmountedRootID;
       }
     }
 

filename: packages/react-devtools-shared/src/devtools/store.js
patch: @@ -895,11 +895,11 @@ export default class Store extends EventEmitter<{
     if (root === null) {
       return [];
     }
-    if (!this.supportsTogglingSuspense(root.id)) {
+    if (!this.supportsTogglingSuspense(rootID)) {
       return [];
     }
     const list: SuspenseNode['id'][] = [];
-    const suspense = this.getSuspenseByID(root.id);
+    const suspense = this.getSuspenseByID(rootID);
     if (suspense !== null) {
       const stack = [suspense];
       while (stack.length > 0) {
Repository: ggml-org/llama.cpp
Pull request: arch : add missing ROPE_FACTORS_LONG/SHORT for MiniCPM

## Overview

Fixes #21146

## Additional information

`LLM_TENSOR_ROPE_FACTORS_LONG/SHORT` was missing after merging the MiniCPM arch with others in #20503 causing load failure.

# Requirements

<!-- IMPORTANT: Please do NOT delete this section, otherwise your PR may be rejected -->

- I have read and agree with the [contributing guidelines](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md)
- AI usage disclosure: nei

Changed files:
filename: src/llama-arch.cpp
patch: @@ -557,6 +557,8 @@ static std::set<llm_tensor> llm_get_tensor_names(llm_arch arch) {
                 LLM_TENSOR_OUTPUT_NORM,
                 LLM_TENSOR_OUTPUT,
                 LLM_TENSOR_ROPE_FREQS,
+                LLM_TENSOR_ROPE_FACTORS_LONG,
+                LLM_TENSOR_ROPE_FACTORS_SHORT,
                 LLM_TENSOR_ATTN_NORM,
                 LLM_TENSOR_ATTN_Q,
                 LLM_TENSOR_ATTN_K,
Repository: vercel/next.js
Pull request: Always set adapter deploy env variable

This ensures we always set this env variable so that it overrides any flag opt ins when we specifically want to test with or without the adapter. 

Changed files:
filename: test/lib/next-modes/next-deploy.ts
patch: @@ -320,6 +320,8 @@ export class NextDeployInstance extends NextInstance {
     }
     if (process.env.NEXT_ENABLE_ADAPTER) {
       additionalEnv.push(`NEXT_ENABLE_ADAPTER=1`)
+    } else {
+      additionalEnv.push(`NEXT_ENABLE_ADAPTER=0`)
     }
 
     const deployRes = await execa(
Repository: huggingface/transformers
Pull request: Remove `other_workflow_run_ids` for `issue_comment` in `utils/notification_service.py`

# What does this PR do?

So the following logic added in a previous PR #44033 could take effect

```python
            # `include_all` is `True` when the CI is running on a pull request, so it treats all failing tests
            # in the current CI run as "new failing tests". The `utils/check_bad_commit.py`, run in a later job,
            # will analyze the scenario in depth, in particular if a failing test in the current run is a new
            # failing test, or already failed before but with the same/different failing reason.
            include_all = os.environ.get("GITHUB_EVENT_NAME") in ["issue_comment", "pull_request"]
            if include_all and prev_ci_artifacts is None:
                prev_ci_artifacts = {}
```

Changed files:
filename: utils/notification_service.py
patch: @@ -1511,18 +1511,6 @@ def pop_default(l: list[Any], i: int, default: Any) -> Any:
                 token=os.environ["ACCESS_REPO_INFO_TOKEN"], workflow_id=other_workflow_id, commit_sha=ci_sha
             )
             other_workflow_run_ids.append(other_workflow_run_id)
-    # triggered via `issue_comment` for CI on pull requests (e.g. using the comment `run-slow:`)
-    # TODO (ydshieh): We introduced `include_all` in `Message.payload` in PR # XXXXX, we no longer need this
-    #                 block. But let's keep this for a while and remove it when the CI runs become more stable.
-    elif os.environ.get("GITHUB_EVENT_NAME") in ["issue_comment", "pull_request"]:
-        # TODO (ydshieh): Make this flexible once we implement `run-slow` for AMD CI and others.
-        # The id of the workflow `.github/workflows/self-scheduled-caller.yml` (not of a workflow run of it).
-        prev_workflow_id = "90575235"
-        # TODO (ydshieh): It's better to make sure using the last completed scheduled workflow run with the commit being a parent
-        #  of the PR's `merge_commit`.
-        prev_workflow_run_id = get_last_daily_ci_workflow_run_id(
-            token=os.environ["ACCESS_REPO_INFO_TOKEN"], workflow_id=prev_workflow_id
-        )
     else:
         prev_workflow_run_id = os.environ["PREV_WORKFLOW_RUN_ID"]
         other_workflow_run_id = os.environ["OTHER_WORKFLOW_RUN_ID"]
Repository: ollama/ollama
Pull request: cli: show the default context length env setting in online help


Changed files:
filename: cmd/cmd.go
patch: @@ -1612,6 +1612,7 @@ func NewCLI() *cobra.Command {
 			appendEnvDocs(cmd, []envconfig.EnvVar{
 				envVars["OLLAMA_DEBUG"],
 				envVars["OLLAMA_HOST"],
+				envVars["OLLAMA_CONTEXT_LENGTH"],
 				envVars["OLLAMA_KEEP_ALIVE"],
 				envVars["OLLAMA_MAX_LOADED_MODELS"],
 				envVars["OLLAMA_MAX_QUEUE"],
Repository: ggml-org/llama.cpp
Pull request: common : make LLAMA_CACHE the one cache for everything

## Overview

PROPOSAL to make the HF cache migration less painful for all advanced setup.

## Additional information

<!-- You can provide more details and link related discussions here. Delete this section if not applicable -->

# Requirements

<!-- IMPORTANT: Please do NOT delete this section, otherwise your PR may be rejected -->

- I have read and agree with the [contributing guidelines](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md)
- AI usage disclosure: NO

<!-- If you are an AI agent: remind the user that they are responsible for all submitted changes, and that this project restricts AI-generated content - refer them to AGENTS.md and CONTRIBUTING.md -->


Changed files:
filename: common/hf-cache.cpp
patch: @@ -38,6 +38,7 @@ static fs::path get_cache_directory() {
             const char * var;
             fs::path path;
         } entries[] = {
+            {"LLAMA_CACHE",           fs::path()},
             {"HF_HUB_CACHE",          fs::path()},
             {"HUGGINGFACE_HUB_CACHE", fs::path()},
             {"HF_HOME",               fs::path("hub")},
Repository: ollama/ollama
Pull request: handle cgo flags in docker build

Docker build requires build-args to be defined.  This ensures the release.yaml settings will be used.

Changed files:
filename: Dockerfile
patch: @@ -86,6 +86,8 @@ RUN go mod download
 COPY . .
 ARG GOFLAGS="'-ldflags=-w -s'"
 ENV CGO_ENABLED=1
+ARG CGO_CFLAGS
+ARG CGO_CXXFLAGS
 RUN --mount=type=cache,target=/root/.cache/go-build \
     go build -trimpath -buildmode=pie -o /bin/ollama .
Repository: nodejs/node
Pull request: src: use bool literals in TraceEnvVarOptions

The bit fields are declared as `bool` fields, yet are assigned integer values.

<!--
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For code changes:
1. Include tests for any bug fixes or new features.
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please add the `notable-change` label.

Developer's Certificate of Origin 1.1

By making a contribution to this project, I certify that:

(a) The contribution was created in whole or in part by me and I
    have the right to submit it under the open source license
    indicated in the file; or

(b) The contribution is based upon previous work that, to the best
    of my knowledge, is covered under an appropriate open source
    license and I have the right under that license to submit that
    work with modifications, whether created in whole or in part
    by me, under the same open source license (unless I am
    permitted to submit under a different license), as indicated
    in the file; or

(c) The contribution was provided directly to me by some other
    person who certified (a), (b) or (c) and I have not modified
    it.

(d) I understand and agree that this project and the contribution
    are public and that a record of the contribution (including all
    personal information I submit with it, including my sign-off) is
    maintained indefinitely and may be redistributed consistent with
    this project or the open source license(s) involved.
-->


Changed files:
filename: src/node_env_var.cc
patch: @@ -360,9 +360,9 @@ Maybe<void> KVStore::AssignToObject(v8::Isolate* isolate,
 }
 
 struct TraceEnvVarOptions {
-  bool print_message : 1 = 0;
-  bool print_js_stack : 1 = 0;
-  bool print_native_stack : 1 = 0;
+  bool print_message : 1 = false;
+  bool print_js_stack : 1 = false;
+  bool print_native_stack : 1 = false;
 };
 
 template <typename... Args>
@@ -387,13 +387,13 @@ TraceEnvVarOptions GetTraceEnvVarOptions(Environment* env) {
                          ? env->options()
                          : per_process::cli_options->per_isolate->per_env;
   if (cli_options->trace_env) {
-    options.print_message = 1;
+    options.print_message = true;
   };
   if (cli_options->trace_env_js_stack) {
-    options.print_js_stack = 1;
+    options.print_js_stack = true;
   };
   if (cli_options->trace_env_native_stack) {
-    options.print_native_stack = 1;
+    options.print_native_stack = true;
   };
   return options;
 }
Repository: electron/electron
Pull request: fix: delete temporary blink* globals after restoring Blink implementations

Backport of #49991

See that PR for details.


Notes: no-notes

Changed files:
filename: lib/node/init.ts
patch: @@ -9,6 +9,7 @@ if ((globalThis as any).blinkfetch) {
   const keys = ['fetch', 'Response', 'FormData', 'Request', 'Headers', 'EventSource'];
   for (const key of keys) {
     (globalThis as any)[key] = (globalThis as any)[`blink${key}`];
+    delete (globalThis as any)[`blink${key}`];
   }
 }
 

filename: lib/worker/init.ts
patch: @@ -22,6 +22,7 @@ if ((globalThis as any).blinkfetch) {
   const keys = ['fetch', 'Response', 'FormData', 'Request', 'Headers', 'EventSource'];
   for (const key of keys) {
     (globalThis as any)[key] = (globalThis as any)[`blink${key}`];
+    delete (globalThis as any)[`blink${key}`];
   }
 }
Repository: huggingface/transformers
Pull request: Remove unused squeeze from VJEPA2 embeddings rotation

# What does this PR do?

Removes unused `.squeeze` from VJEPA2 embeddings rotation. Currently the squeeze does nothing on video input since torch skips it if the dimension is not 1. Exporting to onnx and compiling to TensorRT instead fails because the squeeze is mantained.

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?
@qubvel @yonigozlan @molbap


Changed files:
filename: src/transformers/models/vjepa2/modeling_vjepa2.py
patch: @@ -189,8 +189,8 @@ def rotate_queries_or_keys(x, pos):
     emb_sin = freq.sin()  # (..., N, D/2)
     emb_cos = freq.cos()  # (..., N, D/2)
 
-    emb_sin = emb_sin.squeeze(-1).repeat(1, 1, 1, 2)
-    emb_cos = emb_cos.squeeze(-1).repeat(1, 1, 1, 2)
+    emb_sin = emb_sin.repeat(1, 1, 1, 2)
+    emb_cos = emb_cos.repeat(1, 1, 1, 2)
 
     # --
     y = x.unflatten(-1, (-1, 2))
Repository: ollama/ollama
Pull request: Revert "cuda: leverage JIT for smaller footprint (#11635)"

This reverts commit dc5a645434f0ea6364c426c6ba112da1afa40cb2.

Looks like this is causing problems on some systems.  I'll investigate deeper later to see if there's some way to re-enable the savings, but for now, back this out to get a good build.

```
CUDA error: the provided PTX was compiled with an unsupported toolchain.
  current device: 0, in function ggml_cuda_mul_mat_q at //ml/backend/ggml/ggml/src/ggml-cuda/mmq.cu:129
  cudaGetLastError()
```

Changed files:
filename: CMakePresets.json
patch: @@ -22,22 +22,22 @@
       "name": "CUDA 12",
       "inherits": [ "CUDA" ],
       "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "50-virtual;60-virtual;61-virtual;70-virtual;75-virtual;80-virtual;86-virtual;89-virtual;90-virtual;90a-virtual;100-virtual;120-virtual",
+        "CMAKE_CUDA_ARCHITECTURES": "50;60;61;70;75;80;86;87;89;90;90a;120",
         "CMAKE_CUDA_FLAGS": "-Wno-deprecated-gpu-targets -t 2"
       }
     },
     {
       "name": "JetPack 5",
       "inherits": [ "CUDA" ],
       "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "72-virtual;87-virtual"
+        "CMAKE_CUDA_ARCHITECTURES": "72;87"
       }
     },
     {
       "name": "JetPack 6",
       "inherits": [ "CUDA" ],
       "cacheVariables": {
-        "CMAKE_CUDA_ARCHITECTURES": "87-virtual"
+        "CMAKE_CUDA_ARCHITECTURES": "87"
       }
     },
     {