Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,85 @@
+---
+base_model: Locutusque/gpt2-xl-conversational
+datasets:
+- Locutusque/InstructMix
+language:
+- en
+license: mit
+metrics:
+- bleu
+- perplexity
+- loss
+- accuracy
+pipeline_tag: text-generation
+tags:
+- llama-cpp
+- gguf-my-repo
+widget:
+- text: '<|USER|> Design a Neo4j database and Cypher function snippet to Display Extreme
+    Dental hygiene: Using Mouthwash for Analysis for Beginners. Implement if/else
+    or switch/case statements to handle different conditions related to the Consent.
+    Provide detailed comments explaining your control flow and the reasoning behind
+    each decision. <|ASSISTANT|> '
+- text: '<|USER|> Write me a story about a magical place. <|ASSISTANT|> '
+- text: '<|USER|> Write me an essay about the life of George Washington <|ASSISTANT|> '
+- text: '<|USER|> Solve the following equation 2x + 10 = 20 <|ASSISTANT|> '
+- text: '<|USER|> Craft me a list of some nice places to visit around the world. <|ASSISTANT|> '
+- text: '<|USER|> How to manage a lazy employee: Address the employee verbally. Don''t
+    allow an employee''s laziness or lack of enthusiasm to become a recurring issue.
+    Tell the employee you''re hoping to speak with them about workplace expectations
+    and performance, and schedule a time to sit down together. Question: To manage
+    a lazy employee, it is suggested to talk to the employee. True, False, or Neither?
+    <|ASSISTANT|> '
+inference:
+  parameters:
+    temperature: 0.8
+    do_sample: true
+    top_p: 0.14
+    top_k: 41
+    max_new_tokens: 250
+    repetition_penalty: 1.176
+---
+
+# antoste/gpt2-xl-conversational-Q4_K_M-GGUF
+This model was converted to GGUF format from [`Locutusque/gpt2-xl-conversational`](https://huggingface.co/Locutusque/gpt2-xl-conversational) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/Locutusque/gpt2-xl-conversational) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo antoste/gpt2-xl-conversational-Q4_K_M-GGUF --hf-file gpt2-xl-conversational-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo antoste/gpt2-xl-conversational-Q4_K_M-GGUF --hf-file gpt2-xl-conversational-q4_k_m.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo antoste/gpt2-xl-conversational-Q4_K_M-GGUF --hf-file gpt2-xl-conversational-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo antoste/gpt2-xl-conversational-Q4_K_M-GGUF --hf-file gpt2-xl-conversational-q4_k_m.gguf -c 2048
+```