helloadhavan/github_issues huggingface dataset:
Repository: huggingface/transformers
Pull request: Fix failing `MarianIntegrationTests`

# What does this PR do?
Fixes these failing [MarianIntegrationTests](https://github.com/huggingface/transformers/actions/runs/22606636929/job/65500458014#step:14:6186)

<img width="2378" height="657" alt="image" src="https://github.com/user-attachments/assets/6ed0bf99-8e1f-422d-a69f-29f2963c0804" />



## 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?
@Rocketknight1 @vasqu

Changed files:
filename: tests/models/marian/test_modeling_marian.py
patch: @@ -404,8 +404,9 @@ def eos_token_id(self) -> int:
     def model(self):
         model: MarianMTModel = MarianMTModel.from_pretrained(self.model_name).to(torch_device)
         c = model.config
-        self.assertListEqual(c.bad_words_ids, [[c.pad_token_id]])
-        self.assertEqual(c.max_length, 512)
+        generation_config = model.generation_config
+        self.assertListEqual(generation_config.bad_words_ids, [[c.pad_token_id]])
+        self.assertEqual(generation_config.max_length, 512)
         self.assertEqual(c.decoder_start_token_id, c.pad_token_id)
 
         if torch_device == "cuda":
Repository: ollama/ollama
Pull request: jetpack: require exact match or skip cuda_jetpack*

The cuda_jetpack libs will enumerate discrete GPUs on SBSA systems which leads to runtime failures of missing kernels.  This fix requires an exact match to enable jetpacks instead of relying on enumeration to filter out supported libraries.

Fixes #13169 

Changed files:
filename: discover/runner.go
patch: @@ -98,6 +98,9 @@ func GPUDevices(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.
 					continue
 				} else if jetpack != "" && filepath.Base(dir) != "cuda_"+jetpack {
 					continue
+				} else if jetpack == "" && strings.Contains(filepath.Base(dir), "cuda_jetpack") {
+					slog.Debug("jetpack not detected (set JETSON_JETPACK or OLLAMA_LLM_LIBRARY to override), skipping", "libDir", dir)
+					continue
 				} else if !envconfig.EnableVulkan() && strings.Contains(filepath.Base(dir), "vulkan") {
 					slog.Info("experimental Vulkan support disabled.  To enable, set OLLAMA_VULKAN=1")
 					continue
Repository: facebook/react
Pull request: [eprh] Update changelog for 7.0.1


Add changelog entry for 7.0.1

---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed with [ReviewStack](https://reviewstack.dev/facebook/react/pull/34964).
* #34965
* __->__ #34964

Changed files:
filename: packages/eslint-plugin-react-hooks/CHANGELOG.md
patch: @@ -1,3 +1,10 @@
+## 7.0.1
+
+- Disallowed passing inline `useEffectEvent` values as JSX props to guard against accidental propagation. ([#34820](https://github.com/facebook/react/pull/34820) by [@jf-eirinha](https://github.com/jf-eirinha))
+- Switch to `export =` so eslint-plugin-react-hooks emits correct types for consumers in Node16 ESM projects. ([#34949](https://github.com/facebook/react/pull/34949) by [@karlhorky](https://github.com/karlhorky))
+- Tightened the typing of `configs.flat` so the `configs` export is always defined. ([#34950](https://github.com/facebook/react/pull/34950) by [@poteto](https://github.com/poteto))
+- Fix named import runtime errors. ([#34951](https://github.com/facebook/react/pull/34951), [#34953](https://github.com/facebook/react/pull/34953) by [@karlhorky](https://github.com/karlhorky))
+
 ## 7.0.0
 
 This release slims down presets to just 2 configurations (`recommended` and `recommended-latest`), and all compiler rules are enabled by default.
Repository: ollama/ollama
Pull request: .gitattributes: add app/webview to linguist-vendored

This is largely vendor webview code

Changed files:
filename: .gitattributes
patch: @@ -19,6 +19,8 @@ ml/backend/**/*.comp linguist-vendored
 ml/backend/**/*.glsl linguist-vendored
 ml/backend/**/CMakeLists.txt linguist-vendored
 
+app/webview linguist-vendored
+
 llama/build-info.cpp linguist-generated
 ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-embed.s linguist-generated
Repository: huggingface/transformers
Pull request: Fix continuous batching for multimodal models

Fixes #44423

`continuous_batching_chat_completion` was missing input preprocessing and `tokenize=True` in `apply_chat_template`, causing `'str' object has no attribute 'to'` for multimodal models.

Added the same `get_model_modality` + `get_processor_inputs_from_inbound_messages` preprocessing already used in `generate_chat_completion`.


Changed files:
filename: src/transformers/cli/serve.py
patch: @@ -807,6 +807,14 @@ def continuous_batching_chat_completion(self, req: dict, request_id: str) -> Str
                 self.running_continuous_batching_manager = None
 
         model, processor = self.load_model_and_processor(model_id_and_revision)
+
+        # Continuous batching only supports text-only models
+        if self.get_model_modality(model, processor=processor) != Modality.LLM:
+            logger.warning_once(
+                "Continuous batching is not supported for non-text-only models. Falling back to regular generate."
+            )
+            return self.generate_chat_completion(req)
+
         tokenizer = processor.tokenizer if hasattr(processor, "tokenizer") else processor
 
         generation_config = create_generation_config_from_req(
Repository: huggingface/transformers
Pull request: fix pin_memory for contiguous batching

Check if accelerator exists before using `pin_memory`.

reproduce it on a CPU only node:
`python examples/pytorch/continuous_batching_simple.py`
output:
```
  File "/home/jiqingfe/transformers/src/transformers/generation/continuous_batching/input_outputs.py", line 142, in _setup_static_ten
sors
    self._bulk_input_tensor = torch.empty(
                              ^^^^^^^^^^^^
RuntimeError: pin_memory=True requires a CUDA or other accelerator backend; no pinned memory allocator is available on this system.
Generation thread terminated unexpectedly.                                                                                           
```

@remi-or . Please review this PR. Thanks!

Changed files:
filename: src/transformers/generation/continuous_batching/input_outputs.py
patch: @@ -20,6 +20,7 @@
 
 from transformers.configuration_utils import PretrainedConfig
 
+from ...utils import get_available_devices
 from ...utils.metrics import traced
 from .cache import PagedAttentionCache
 from .requests import TMP_TOKEN_ID, FutureRequestState
@@ -134,7 +135,8 @@ def _setup_static_tensors(self) -> None:
         num_groups = self.cache.num_groups
         max_batch_tokens = self.cache.max_batch_tokens
         num_pages = self.cache.num_blocks * self.cache.block_size
-        pin_memory = self.device.type == "cpu"
+        # Pin memory on CPU only when an accelerator is available, to speed up H2D transfers
+        pin_memory = self.device.type == "cpu" and len(get_available_devices()) > 1
 
         # Small inputs are allocated as slices in a larget tensor aligned to 128 bytes (32 * 4b). This reduces the
         # reduces fragmentation, so it lowers the number of D2H transfers and speeds up transfers.
Repository: ollama/ollama
Pull request: app/cmd: update ollama help to navigate to ollama doc


Changed files:
filename: app/cmd/app/app_darwin.m
patch: @@ -247,7 +247,7 @@ - (void)aboutOllama {
 }
 
 - (void)openHelp:(id)sender {
-    NSURL *url = [NSURL URLWithString:@"https://github.com/ollama/ollama/tree/main/docs"];
+    NSURL *url = [NSURL URLWithString:@"https://docs.ollama.com/"];
     [[NSWorkspace sharedWorkspace] openURL:url];
 }
Repository: huggingface/transformers
Pull request: Fix KeyError in _parse_type_hint when Union contains Any

## Summary

Fixes a `KeyError` crash in `_parse_type_hint` in `chat_template_utils.py` (line 117).

When processing Union types, the code accesses `subtype["type"]` without checking the key exists. `_get_json_schema_type(Any)` returns `{}` (empty dict with no "type" key), so Union types containing `Any` (e.g., `Union[str, Any]`) crash with a `KeyError`.

```python
# Before:
elif all(isinstance(subtype["type"], str) for subtype in subtypes):

# After:
elif all("type" in subtype and isinstance(subtype["type"], str) for subtype in subtypes):
```

This guard ensures the code falls through to the `anyOf` branch for types that don't have a simple "type" key.

## Test plan
- [x] Verified `_get_json_schema_type(Any)` returns `{}` with no "type" key
- [x] Verified the fix correctly falls through to the `anyOf` branch
- [ ] Existing tests should continue to pass


Changed files:
filename: src/transformers/utils/chat_template_utils.py
patch: @@ -114,7 +114,7 @@ def _parse_type_hint(hint: str) -> dict:
         if len(subtypes) == 1:
             # A single non-null type can be expressed directly
             return_dict = subtypes[0]
-        elif all(isinstance(subtype["type"], str) for subtype in subtypes):
+        elif all("type" in subtype and isinstance(subtype["type"], str) for subtype in subtypes):
             # A union of basic types can be expressed as a list in the schema
             return_dict = {"type": sorted([subtype["type"] for subtype in subtypes])}
         else:
Repository: vercel/next.js
Pull request: tests: Use pnpm dlx to install latest CLI version

Hopefully improve flakeyness

Changed files:
filename: test/production/deterministic-build/deployment-id.test.ts
patch: @@ -237,17 +237,16 @@ const FILES = {
           '.vercel/project.json': `{ "projectId": "prj_", "orgId": "team_", "settings": {} }`,
           ...FILES[test],
         },
-        dependencies: {
-          vercel: 'latest',
-        },
         packageJson: {
           scripts: {
             dev: 'next dev',
             build: 'next build',
             start: 'next start',
           },
         },
-        buildCommand: 'pnpm vercel build',
+        // We use NEXT_TEST_PREFER_OFFLINE, so just declaring `vercel: latest` as a dependency still
+        // doesn't force the latest version.
+        buildCommand: 'pnpm dlx vercel@latest build',
         env:
           mode === 'adapter'
             ? {
Repository: nodejs/node
Pull request: tools: fix daily wpt workflow nighly release version lookup

https://github.com/nodejs/node/pull/61903 updated the runner from x64 to arm, ever since we're at the mercy of jenkins to finish promoting the nighly arm release in time, this fixes that problem by selecting the last nightly for arm.

Changed files:
filename: .github/workflows/daily-wpt-fyi.yml
patch: @@ -49,7 +49,7 @@ jobs:
       # install a version and checkout
       - name: Get latest nightly
         if: matrix.node-version == 'latest-nightly'
-        run: echo "NIGHTLY=$(curl -s https://nodejs.org/download/nightly/index.json | jq -r '[.[] | select(.files[] | contains("linux-x64"))][0].version')" >> $GITHUB_ENV
+        run: echo "NIGHTLY=$(curl -s https://nodejs.org/download/nightly/index.json | jq -r '[.[] | select(.files[] | contains("linux-arm64"))][0].version')" >> $GITHUB_ENV
       - name: Install Node.js
         id: setup-node
         uses: actions/setup-node@6044e13b5dc448c55e2357c09f80417699197238  # v6.2.0
Repository: electron/electron
Pull request: ci: ignore test timeouts in audit

#### Description of Change

<!--
Thank you for your Pull Request. Please provide a description above and review
the requirements below.

Contributors guide: https://github.com/electron/electron/blob/main/CONTRIBUTING.md
-->

We don't want to get pinged for these flakes.

#### Checklist
<!-- Remove items that do not apply. For completed items, change [ ] to [x]. -->

- [x] PR description included

#### Release Notes

Notes: none <!-- Please add a one-line description for app developers to read in the release notes, or 'none' if no notes relevant to app developers. Examples and help on special cases: https://github.com/electron/clerk/blob/main/README.md#examples -->


Changed files:
filename: .github/workflows/audit-branch-ci.yml
patch: @@ -86,6 +86,7 @@ jobs:
                       !message.startsWith("Response status code does not indicate success") &&
                       !message.startsWith("The hosted runner lost communication with the server") &&
                       !message.startsWith("Dependabot encountered an error performing the update") &&
+                      !message.startsWith("The action 'Run Electron Tests' has timed out") &&
                       !/Unable to make request/.test(message) &&
                       !/The requested URL returned error/.test(message),
                   )
Repository: facebook/react
Pull request: [eprh] Type `configs.flat` more strictly

Addresses #34801 where `configs.flat` is possibly undefined as it was typed as a record of arbitrary string keys.

<img width="990" height="125" alt="Screenshot 2025-10-22 at 1 16 44 PM" src="https://github.com/user-attachments/assets/8b0d37b9-d7b0-4fc0-aa62-1b0968dae75f" />


Changed files:
filename: packages/eslint-plugin-react-hooks/src/index.ts
patch: @@ -71,7 +71,10 @@ const configs = {
     plugins,
     rules: recommendedLatestRuleConfigs,
   },
-  flat: {} as Record<string, ReactHooksFlatConfig>,
+  flat: {} as {
+    recommended: ReactHooksFlatConfig;
+    'recommended-latest': ReactHooksFlatConfig;
+  },
 };
 
 const plugin = {
Repository: ollama/ollama
Pull request: discovery: fix cuda overlap case

Recent refactoring introduced a regression for filtering cuda overlap to favor newest supported version.

In the context of NVIDIA Jetson Thor, both v12 and v13 enumerate the GPU, but v12 doesn't actually work at runtime.

Fixes #13033 

Changed files:
filename: discover/runner.go
patch: @@ -125,10 +125,20 @@ func GPUDevices(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.
 		supportedMu := sync.Mutex{}
 		supported := make(map[string]map[string]map[string]int) // [Library][libDir][ID] = pre-deletion devices index
 		for i := range devices {
+			libDir := devices[i].LibraryPath[len(devices[i].LibraryPath)-1]
 			if !devices[i].NeedsInitValidation() {
+				// No need to validate, add to the supported map
+				supportedMu.Lock()
+				if _, ok := supported[devices[i].Library]; !ok {
+					supported[devices[i].Library] = make(map[string]map[string]int)
+				}
+				if _, ok := supported[devices[i].Library][libDir]; !ok {
+					supported[devices[i].Library][libDir] = make(map[string]int)
+				}
+				supported[devices[i].Library][libDir][devices[i].ID] = i
+				supportedMu.Unlock()
 				continue
 			}
-			libDir := devices[i].LibraryPath[len(devices[i].LibraryPath)-1]
 			slog.Debug("verifying if device is supported", "library", libDir, "description", devices[i].Description, "compute", devices[i].Compute(), "id", devices[i].ID, "pci_id", devices[i].PCIID)
 			wg.Add(1)
 			go func(i int) {
Repository: huggingface/transformers
Pull request: Fix AssistantTracker.is_active() returning False after activation with empty lists

## Summary

Fixes a bug in `AssistantTracker.is_active()` in `chat_template_utils.py`.

After activation via `activate_tracker()`, `_rendered_blocks` and `_generation_indices` are set to list arguments which may be empty `[]`. The `is_active()` method checks truthiness (`return self._rendered_blocks or self._generation_indices`), which returns `False` for empty lists, incorrectly indicating the tracker is inactive.

This means calling `activate_tracker` with empty lists, then checking `is_active()`, returns `False` even though the tracker was activated. This breaks the re-entrance guard in `activate_tracker` which relies on `is_active()` to detect double activation.

```python
# Before:
def is_active(self) -> bool:
    return self._rendered_blocks or self._generation_indices

# After:
def is_active(self) -> bool:
    return self._rendered_blocks is not None or self._generation_indices is not None
```

## Test plan
- [x] Verified `_rendered_blocks` is initialized as `None` and set to list on activation
- [x] Verified `is_active()` is used as re-entrance guard in `activate_tracker`
- [ ] Existing tests should continue to pass


Changed files:
filename: src/transformers/utils/chat_template_utils.py
patch: @@ -439,7 +439,7 @@ def _generation_support(self, context: jinja2.nodes.EvalContext, caller: jinja2.
             return rv
 
         def is_active(self) -> bool:
-            return self._rendered_blocks or self._generation_indices
+            return self._rendered_blocks is not None or self._generation_indices is not None
 
         @contextmanager
         def activate_tracker(self, rendered_blocks: list[int], generation_indices: list[int]):
Repository: ollama/ollama
Pull request: deepseek2: upgrade to run v3+ models

the check for mla omits v3 and r1 which should not return unsupported. instead check the tokenizer for compatibility

Changed files:
filename: model/models/deepseek2/model.go
patch: @@ -236,11 +236,6 @@ type Model struct {
 }
 
 func New(c fs.Config) (model.Model, error) {
-	if c.Uint("attention.key_length_mla") == 0 {
-		// non-MLA models aren't yet supported
-		return nil, model.ErrUnsupportedModel
-	}
-
 	layers := make([]Layer, c.Uint("block_count"))
 
 	firstDenseLayerIndex := int(c.Uint("leading_dense_block_count"))
@@ -259,6 +254,30 @@ func New(c fs.Config) (model.Model, error) {
 	keyLength := int(cmp.Or(c.Uint("attention.key_length_mla"), c.Uint("attention.key_length")))
 	valueLength := int(cmp.Or(c.Uint("attention.value_length_mla"), c.Uint("attention.value_length")))
 
+	var pre []string
+	switch c.String("tokenizer.ggml.pre") {
+	case "deepseek-v3":
+		pre = []string{
+			// Split regex into multiple parts (according to DeepSeek3's regex)
+			"\\p{N}{1,3}",
+			`[一-龥぀-ゟ゠-ヿ]+`,
+			"[!\"#$%&'()*+,\\-./:;<=>?@\\[\\\\\\]^_`{|}~][A-Za-z]+|[^\r\n\\p{L}\\p{P}\\p{S}]?[\\p{L}\\p{M}]+| ?[\\p{P}\\p{S}]+[\r\n]*|\\s*[\r\n]+|\\s+(?!\\S)|\\s+",
+		}
+	case "deepseek-llm":
+		// TODO: these models haven't been vetted so skip for now
+		// pre = []string{
+		// 	"[\r\n]",
+		// 	"\\s?[A-Za-zµÀ-ÖØ-öø-ƺƼ-ƿǄ-ʓʕ-ʯͰ-ͳͶͷͻ-ͽͿΆΈ-ΊΌΎ-ΡΣ-ϵϷ-ҁҊ-ԯԱ-ՖႠ-ჅᎠ-Ᏽᏸ-ᏽᲐ-ᲺᲽ-Ჿᴀ-ᴫᵫ-ᵷᵹ-ᶚḀ-ἕἘ-Ἕἠ-ὅὈ-Ὅὐ-ὗὙὛὝὟ-ώᾀ-ᾴᾶ-ᾼιῂ-ῄῆ-ῌῐ-ΐῖ-Ίῠ-Ῥῲ-ῴῶ-ῼℂℇℊ-ℓℕℙ-ℝℤΩℨK-ℭℯ-ℴℹℼ-ℿⅅ-ⅉⅎↃↄⰀ-ⱻⱾ-ⳤⳫ-ⳮⳲⳳꙀ-ꙭꚀ-ꚛꜢ-ꝯꝱ-ꞇꞋ-ꞎꭰ-ꮿﬀ-ﬆﬓ-ﬗＡ-Ｚａ-ｚ𐐀-𐑏𐒰-𐓓𐓘-𐓻𐲀-𐲲𐳀-𐳲𑢠-𑣟𞤀-𞥃]+",
+		// 	"\\s?[!-/:-~！-／：-～‘-‟　-。]+",
+		// 	"\\s+$",
+		// 	"[一-龥ࠀ-一가-퟿]+",
+		// 	"[0-9]",
+		// }
+		fallthrough
+	default:
+		return nil, model.ErrUnsupportedTokenizer
+	}
+
 	m := Model{
 		BytePairEncoding: model.NewBytePairEncoding(
 			&model.Vocabulary{
@@ -273,10 +292,7 @@ func New(c fs.Config) (model.Model, error) {
 					c.Ints("tokenizer.ggml.eos_token_ids")...,
 				),
 			},
-			// Split regex into multiple parts (according to DeepSeek3's regex)
-			"\\p{N}{1,3}",
-			`[一-龥぀-ゟ゠-ヿ]+`,
-			"[!\"#$%&'()*+,\\-./:;<=>?@\\[\\\\\\]^_`{|}~][A-Za-z]+|[^\r\n\\p{L}\\p{P}\\p{S}]?[\\p{L}\\p{M}]+| ?[\\p{P}\\p{S}]+[\r\n]*|\\s*[\r\n]+|\\s+(?!\\S)|\\s+",
+			pre...,
 		),
 		Layers: layers,
 		Options: &Options{
Repository: facebook/react
Pull request: Switch to `export =` to fix eslint-plugin-react-hooks types

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  We appreciate you spending the time to work on these changes. Please provide enough information so that others can review your pull request. The three fields below are mandatory.

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## Summary

<!--
 Explain the **motivation** for making this change. What existing problem does the pull request solve?
-->

Resolve the type error with the types, according to [Are the types wrong?](https://arethetypeswrong.github.io/?p=eslint-plugin-react-hooks%407.0.0), as an additional reference to [the CodeSandbox reference](https://github.com/facebook/react/issues/34801#issuecomment-3433053067)

- Last attempt: https://github.com/facebook/react/pull/34746
- Original issue: https://github.com/facebook/react/issues/34745

## How did you test this change?

I edited `node_modules/eslint-plugin-react-hooks/index.d.ts` in my `"module": "Node16"` + `"type": "module"` project and my error went away:

- https://github.com/facebook/react/issues/34801#issuecomment-3433053067

cc @poteto @michaelfaith @andrewbranch 

<!--
  Demonstrate the code is solid. Example: The exact commands you ran and their output, screenshots / videos if the pull request changes the user interface.
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  If you leave this empty, your PR will very likely be closed.
-->


Changed files:
filename: packages/eslint-plugin-react-hooks/npm/index.d.ts
patch: @@ -5,4 +5,6 @@
  * LICENSE file in the root directory of this source tree.
  */
 
-export {default} from './cjs/eslint-plugin-react-hooks';
+import reactHooks from './cjs/eslint-plugin-react-hooks';
+
+export = reactHooks;
Repository: ollama/ollama
Pull request: nomic-embed: nomic-embed-text defaulted to ollama runner 

This PR makes all models with nomic bert architecture run on the Ollama engine

Changed files:
filename: fs/ggml/ggml.go
patch: @@ -251,6 +251,7 @@ func (kv KV) OllamaEngineRequired() bool {
 		"qwen3vl", "qwen3vlmoe",
 		"deepseekocr",
 		"deepseek2",
+		"nomic-bert",
 	}, kv.Architecture())
 }