Instructions to use Kowsher/TokenTrails with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kowsher/TokenTrails with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Kowsher/TokenTrails", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Kowsher/TokenTrails", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("Kowsher/TokenTrails", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Kowsher/TokenTrails with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Kowsher/TokenTrails" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Kowsher/TokenTrails", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Kowsher/TokenTrails
- SGLang
How to use Kowsher/TokenTrails with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Kowsher/TokenTrails" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Kowsher/TokenTrails", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Kowsher/TokenTrails" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Kowsher/TokenTrails", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Kowsher/TokenTrails with Docker Model Runner:
docker model run hf.co/Kowsher/TokenTrails
Update ChatFalcon.py
Browse files- ChatFalcon.py +3 -3
ChatFalcon.py
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@@ -901,9 +901,9 @@ class FalconForCausalLM(FalconPreTrainedModel):
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return_dict = return_dict if return_dict is not None else self.config.use_return_dict
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print('working')
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print(input_ids)
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print(token_type_ids)
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transformer_outputs = self.transformer(
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input_ids,
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return_dict = return_dict if return_dict is not None else self.config.use_return_dict
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#print('working')
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#print(input_ids)
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#print(token_type_ids)
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transformer_outputs = self.transformer(
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input_ids,
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