Update README.md

README.md

@@ -56,106 +56,23 @@ Use the code below to get started with the model.
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-model = AutoModelForCausalLM.from_pretrained("nuvocare/NuvoChat")
-model = AutoModelForCausalLM.from_pretrained("nuvocare/NuvoChat")
+model = AutoModelForCausalLM.from_pretrained("nuvocare/NuvoChat", device = "auto")
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
 
+prompt = "[INST] Je suis un patient qui souhaite connaitre des informations sur la chirurgie de la cataracte [/INST]"
+
+input = tokenizer(prompt).to("cuda")
+
+answer = tokenizer.decode(model.generate(**input, max_new_tokens = 200, pad_token = tokenizer.eos_token)[0])
 ```
 
 ## Training Details
 
 ### Training Data
 
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
+You can check dataset card.
 
 ### Training Procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
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-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-1.04 kg CO2 using [this calculator](https://mlco2.github.io/impact/#compute)
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Model Card Contact
+Trained over 7000 steps with a total batch size of 32 (corresponding to a bit more than 1 epoch) and a sequence length of 2048.
 
-[More Information Needed]