Question Answering
Transformers
Safetensors
trl
sft
finance
accounting
ifrs
financial-services
rag
text-generation
domain-specific-llm
Instructions to use eliashasnat/ifrsllm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eliashasnat/ifrsllm with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="eliashasnat/ifrsllm")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eliashasnat/ifrsllm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from eliashasnat/ifrsllm: direct link, hf CLI and curl.
- Browser
- Download file 441 Bytes
-
https://huggingface.co/eliashasnat/ifrsllm/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://eliashasnat/ifrsllm/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/eliashasnat/ifrsllm/resolve/main/tokenizer_config.json
441 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<|im_start|>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "extra_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>" | |
| ], | |
| "is_local": true, | |
| "model_max_length": 2048, | |
| "pad_token": "<|im_end|>", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>", | |
| "vocab_size": 49152 | |
| } | |