Researchers have developed a method using molecular simulation and language models to enhance protein function prediction, even with limited experimental data.

Release Notes: Added reasoning_effort support to custom models Tested using the following config: "language_models": { "openai": { "available_models": [ { "name": "g...

Did some bit cleanup of code for loading models for settings as that is not required as we are fetching all the models from openrouter so it's better to maintain one source of truth Release Notes: ...

Recently in this PR: #32248 github copilot settings was introduced. This had missing settings update which was leading to github copilot models not getting fetched. This had missing subscription to...

Hi @mahmutc , I am a student trying to learn the stuff. This snippet dint work for me for some reason. Here is the error log I received: Traceback (most recent call last): File “C:\Users\SS\Desktop\Camp_langchain_models\2.ChatModels\2_chatmodel_hf_api.py”, line 9, in print(llm.invoke(“What is the capital of Turkey”)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File “C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\langchain_core\language_models\llms.py”, line 387, in invoke self.generate_prompt( File “C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\langchain_core\language_models\llms.py”, line 764, in generate_prompt return self.generate(prompt_strings, stop=stop, callbacks=callbacks, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File “C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\langchain_core\language_models\llms.py”, line 971, in generate return self._generate_helper( ^^^^^^^^^^^^^^^^^^^^^^ File “C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\langchain_core\language_models\llms.py”, line 790, in _generate_helper self._generate( File “C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\langchain_core\language_models\llms.py”, line 1545, in _generate self._call(prompt, stop=stop, run_manager=run_manager, **kwargs) File “C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\langchain_huggingface\llms\huggingface_endpoint.py”, line 312, in _call response_text = self.client.text_generation( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File “C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\huggingface_hub\inference_client.py”, line 2297, in text_generation provider_helper = get_provider_helper(self.provider, task=“text-generation”, model=model_id) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\SS\Desktop\Camp_langchain_models\venv\Lib\site-packages\huggingface_hub\inference_providers__init__.py", line 169, in get_provider_helper raise ValueError( ValueError: Provider ‘featherless-ai’ not supported. Available values: ‘auto’ or any provider from ‘black-forest-labs’, ‘cerebras’, ‘cohere’, ‘fal-ai’, ‘fireworks-ai’, ‘hf-inference’, ‘hyperbolic’, ‘nebius’, ‘novita’, ‘openai’, ‘replicate’, ‘sambanova’, ‘together’].Passing ‘auto’ (default value) will automatically select the first provider available for the model, sorted by the user’s order in [Hugging Face – The AI community building the future.. I look forward to hearing from you. Thanks, SS

Omron SinicX is set to present groundbreaking research on language models at the prestigious NAACL2025 conference in New Mexico, showcasing advancements in knowledge extraction.

The AI Large Language Models market is experiencing significant growth, driven by the demand for chatbots, content generation, and advanced NLP capabilities across industries.

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