reach-vb HF staff commited on
Commit
511f793
1 Parent(s): 00dc59f

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +6 -6
app.py CHANGED
@@ -19,7 +19,7 @@ from textwrap import dedent
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  HF_TOKEN = os.environ.get("HF_TOKEN")
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  def generate_importance_matrix(model_path, train_data_path):
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- imatrix_command = f"./imatrix -m ../{model_path} -f {train_data_path} -ngl 99 --output-frequency 10"
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  os.chdir("llama.cpp")
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@@ -146,9 +146,9 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
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  quantized_gguf_name = f"{model_name.lower()}-{imatrix_q_method.lower()}-imat.gguf" if use_imatrix else f"{model_name.lower()}-{q_method.lower()}.gguf"
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  quantized_gguf_path = quantized_gguf_name
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  if use_imatrix:
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- quantise_ggml = f"./llama.cpp/quantize --imatrix {imatrix_path} {fp16} {quantized_gguf_path} {imatrix_q_method}"
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  else:
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- quantise_ggml = f"./llama.cpp/quantize {fp16} {quantized_gguf_path} {q_method}"
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  result = subprocess.run(quantise_ggml, shell=True, capture_output=True)
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  if result.returncode != 0:
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  raise Exception(f"Error quantizing: {result.stderr}")
@@ -186,7 +186,7 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
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  ### CLI:
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  ```bash
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- llama --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -p "The meaning to life and the universe is"
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  ```
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  ### Server:
@@ -208,11 +208,11 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
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  Step 3: Run inference through the main binary.
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  ```
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- ./main --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -p "The meaning to life and the universe is"
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  ```
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  or
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  ```
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- ./server --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -c 2048
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  ```
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  """
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  )
 
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  HF_TOKEN = os.environ.get("HF_TOKEN")
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  def generate_importance_matrix(model_path, train_data_path):
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+ imatrix_command = f"./llama-imatrix -m ../{model_path} -f {train_data_path} -ngl 99 --output-frequency 10"
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  os.chdir("llama.cpp")
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  quantized_gguf_name = f"{model_name.lower()}-{imatrix_q_method.lower()}-imat.gguf" if use_imatrix else f"{model_name.lower()}-{q_method.lower()}.gguf"
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  quantized_gguf_path = quantized_gguf_name
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  if use_imatrix:
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+ quantise_ggml = f"./llama.cpp/llama-quantize --imatrix {imatrix_path} {fp16} {quantized_gguf_path} {imatrix_q_method}"
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  else:
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+ quantise_ggml = f"./llama.cpp/llama-quantize {fp16} {quantized_gguf_path} {q_method}"
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  result = subprocess.run(quantise_ggml, shell=True, capture_output=True)
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  if result.returncode != 0:
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  raise Exception(f"Error quantizing: {result.stderr}")
 
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  ### CLI:
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  ```bash
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+ llama-cli --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -p "The meaning to life and the universe is"
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  ```
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  ### Server:
 
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  Step 3: Run inference through the main binary.
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  ```
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+ ./llama-cli --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -p "The meaning to life and the universe is"
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  ```
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  or
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  ```
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+ ./llama-server --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -c 2048
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  ```
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  """
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  )