Remove library name and Transformers code snippet

#2
by nielsr HF Staff - opened
Files changed (1) hide show
  1. README.md +0 -26
README.md CHANGED
@@ -1,7 +1,6 @@
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  ---
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  license: apache-2.0
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  pipeline_tag: text-generation
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- library_name: transformers
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  tags:
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  - text-generation
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  - causal-lm
@@ -98,31 +97,6 @@ Performance evaluation is ongoing. The model shows promising results in:
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  - Significantly improved needle-in-haystack task performance compared to pure RWKV architectures
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  - Competitive performance on standard language modeling benchmarks
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- ## Usage with Hugging Face Transformers
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-
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- This model can be loaded and used with the `transformers` library. Ensure you have `transformers` installed: `pip install transformers`.
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- When loading, remember to set `trust_remote_code=True` because of the custom architecture.
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-
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- ```python
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- from transformers import pipeline, AutoTokenizer
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- import torch
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-
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- model_name = "OpenMOSE/HRWKV7-Reka-Flash3-Preview" # Replace with the actual model ID if different
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- tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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- pipe = pipeline(
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- "text-generation",
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- model_name,
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- tokenizer=tokenizer,
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- torch_dtype=torch.bfloat16, # or torch.float16 depending on your GPU and model precision
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- device_map="auto",
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- trust_remote_code=True,
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- )
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-
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- text = "The quick brown fox jumps over the lazy "
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- result = pipe(text, max_new_tokens=20, do_sample=True, top_p=0.9, temperature=0.7)[0]["generated_text"]
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- print(result)
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- ```
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-
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  ## Run with RWKV-Infer (as provided by original authors)
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  - RWKV-Infer now support hxa079
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  ```bash
 
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  ---
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  license: apache-2.0
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  pipeline_tag: text-generation
 
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  tags:
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  - text-generation
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  - causal-lm
 
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  - Significantly improved needle-in-haystack task performance compared to pure RWKV architectures
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  - Competitive performance on standard language modeling benchmarks
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  ## Run with RWKV-Infer (as provided by original authors)
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  - RWKV-Infer now support hxa079
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  ```bash